Theoretical Study on Optoelectronic and Various Quantum Chemical Properties of Essential Amino Acids: A Comparative Study

Theoretical Study on Optoelectronic and Various Quantum Chemical Properties of Essential Amino Acids: A Comparative Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Theoretical Study on Optoelectronic and Various Quantum Chemical Properties of Essential Amino Acids: A Comparative Study Shradha Lakhera, Meenakshi Rana Rana, Kamal Devlal This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1603417/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract In the present work, a theoretical study has been performed targeting essential amino acids (EAA) Histidine , Isoleucine , Leucine , Lysine , Methionine , Phenylalanine , Threonine , Tryptophan , Valine , and predicted their different physical and chemical properties by using computational techniques. Amino acids (AA), a fundamental structural unit of protein are amino and carboxyl-rich compounds having electrophilic and nucleophilic regions in it. The reactivity of AA were determined by computing molecular electrostatic potential (MEP) surfaces, counter plots, dipole moment, band gap, global reactivity parameters, and polarizability parameters. Spectral analysis (UV-Vis, Raman) helps in studying their electronic and vibrational properties. The polarizability and first order hyperpolarizability parameters were also computed to detect the nonlinear optical (NLO) behavior of AA. The comparison done with reference NLO materials Urea, Phenyl urea, and 3-nitroaniline showed that Phenylalanine have higher hyperpolarizability and can better to be used as a potent NLO material. Essential amino acids Optimization Mulliken charges Chemical reactivity Spectral analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Nonlinear optical (NLO) activity accounts for the polarization behavior of any material under the applied electric field. NLO properties deal with the displacement of the propagation characteristics of light (Ray 2010). When phase, frequency, amplitude, polarization, etc. of the incident light changes under the applied electric field, the material possesses NLO behavior (Bairy et al. 2021). NLO is very emergent topic of the current research world, exhibiting great diversity. It can be considered as a multidisciplinary field of research as it has engineering and mechanical bias, and is a subject of physical sciences, and sometimes its applications can also be seen in chemical and biological science (Midgley et al. 2009; Lakhera et al. 2022). In today’s technology-dependent society, the need for efficient materials is increasing with every passing day. NLO materials have an extensive area of applications from uses in future integrated photonic technologies, telecommunications, sum, and difference frequency generation to microfabrication, optical rectification, frequency mixing wave generation, electro-optic modulation, frequency conversion, fluorescence imaging, etc (Ullah et al. 2020; Buriahi et al. 2020; Cheng et al. 2019). NLO materials have been explored from various materials like molecular chromophores, polymers, semiconductors, etc., and also artificially designed such as lithium niobate (LiNbO 3 ) and potassium dihydrogen phosphate (KH 2 PO 4 ) (Moroz and Maslovskaya 2021). The carbon is known to form different fascinating compounds. The basic reason is sp 2 hybridization of carbon that give rise to the immense quantity of delocalized π-electrons available for the ICT that makes it highly reactive with different elements. Thus, the carbon compounds like fullerenes and carbon nanotubes have been an attractive field of research for the researchers. The studies with the introduction of highly efficient NLO carbon compounds have been reported from the literature survey. Fullerenes like C 58 BN and C 60 Cl 30 were reported to have 105.01×10 –36 esu and 136.10×10 –36 esu values of first order hyperpolarizability ( Muhammad et al. 2013). The carbon nanotubes have also been reported to have high third-order mean polarizability amplitudes like zigzag arranged nanotube 48.60×10 –36 esu and an armchair arranged nanotube 43.52×10 –36 esu (Muhammad et al. 2016, Muhammad et al. 2013) [10,11]. The amino acids (AA), fall in the category of carbon compounds. The organic compound-based NLO materials are gaining much attention and preferred by most scientists worldwide because of their properties like high durability, high structural flexibility, high electronic susceptibility, short response time, easy availability, and synthesis. The innumerable stretchability and extensive response time make organic NLO materials more efficient than inorganic NLO materials (Naseema et al. 2020). Generally, the presence of π-electron conjugated moiety with electron donor and electron acceptor groups in organic molecules leads to remarkable NLO performance (Lee et al. 2021). Keeping this in mind, we have tried to detect the NLO behavior of AA. AA are the fundamental compound in protein formation. They consists of amino (–NH 2 ) and carboxyl (–COOH) functional groups. Nitrogen atoms present in the amino group constitute electron density to a greater extend. The higher the free electron pairs, the higher will be the availability of electrons for donation (Rana et al. 2019). The presence of the amino group also makes AA nucleophilic and carboxyl groups develop the electrophilic behavior. The oxygen atoms present in the carboxyl group are electronegative which draws electron cloud away from carbon making AA electrophilic (King et al. 2021). AA are generally divided into three main categories i.e., essentials (which cannot be synthesized by the body or must be consumed), non-essentials (which are self-synthesized in the body), and conditional AA (which are not necessarily required generally except the illness or deficiency) (Then et al. 2020; Lopez et al. 2021; Javier-Hila et al. 2021; Wang et al. 2021). In the current study, we have considered nine essential amino acids (EAA) ( Histidine , Isoleucine , Leucine , Lysine , Methionine , Phenylalanine , Threonine , Tryptophan , and Valine ) (Table 1 ). These AA are synthesized into our body by the breakdown of the consumed protein and thus leads to the growth and development of muscles and immunity (Soares et al. 2020). They are available in plenty and consumed by external sources like meat, eggs, and poultry and can lead to wider applications in pharmacological sciences (Christophersen and Haug 2011). Optimized structure for all nine EAA are presented in the Table 1 . The dipole moment and polarizability is the virtue by which the polarizing ability of any compound can be studied (Kuramochi et al. 2020). Mulliken charges and molecular electrostatic potential (MEP) surface have been done for all AA. Spectra like UV-Vis and Raman are also reported to check the spectral properties of the AA. The computed frontier molecular orbital (FMO) parameters are reported to justify the chemical reactivity of the compounds. The hyperpolarizability are the quantities by which the NLO behavior of any compound can be predicted (Lakhera et al. 2022). More the compound is polarizable, more it will show NLO behavior (Nazrin et al. 2019). The calculations for the polarizability parameters are also carried out to understand the NLO responses of the compound. 2. Computational Procedure And Calculation The structures of the EAA are downloaded from online database “PubChem” ( https://pubchem.ncbi.nlm.nih.gov/ ) (Table 1 ). All the computational calculations were carried out using Gaussian 09 software and the interpretation of the output is done with the help of graphic user interface Gauss View 5.0 (Frisch et al. 2009; Becke 1993; Becke 1997). Becke-3-Lee-Yang-Parr (B3) exchange function combined with (LYP) correlation is used for optimization (Dennington et al. 2007). The geometries of all the considered EAA are optimized using density functional theory (DFT) with the standard B3LYP/6-311G basis set. The optimized structure helps in obtaining the FMO energies. The rest of the parameters like ionization potential ( IP ), energy gap ( ΔE ), electron affinity ( EA ), chemical potential ( CP ), electronegativity ( χ ), softness ( S ), and hardness ( η ) are calculated with the help of these orbital energies. These parameters are calculated with the help of Koopman’s equations given below (Koopmans 1934): In Raman spectra analysis, Raman intensity is also calculated corresponding to high frequency modes. It was calculated by below given expression: where I refer to Raman intensity of the considered mode, f is a constant with value 10 − 12 , ν o has value 9398.5 cm − 1 . ν i and S i is the vibrational wavenumber and Raman activity of selected mode respectively. h is Planck constant with value 4.1357×10 − 15 eV K − 1 , c is speed of light with value 3×10 8 m/s, K is Boltzmann constant with value 8.6173×10 − 5 eV K − 1 , and T is temperature 293.5K. Polarizability parameters were calculated to understand the diffusion of the electron cloud in compound. The total dipole moment ( µ total ), total isotropic polarizability ( α total ) , anisotropy of polarizability (Δ α ), and first order hyperpolarizability ( β total ) can be given as (Rana and Chowdhury 2020; Bhatt et al. 2020; Rana et al. 2020; Huang et al. 2006). where µ x , µ y , and µ z are the tensor components dipole moment, α xx , α yy , and, α zz are the tensor components of polarizability and β xxx , β yyy , and β zzz are the tensor components of hyperpolarizability. 3. Results And Discussion 3.1 Structure Structures for all the considered AA were optimized to the ground state energy level and were listed in Table 1 . Optimized geometry helps in finding the net polarity of the molecule by the means of dipole moment. More the dipole moment, more the compound will be polarizable (Lakhera et al. 2021; Visscher and Geerke 2019; Rana et al. 2017). In the present case, the selected EAA Histidine (5.58 Debye) have the maximum dipole moment as compared to Isoleucine (1.65 Debye), Leucine (1.85 Debye), Lysine (0.88 Debye), Methionine (0.96 Debye), Phenylalanine (1.62 Debye), Threonine (2.50 Debye), Tryptophan (2.95 Debye), and Valine (1.31 Debye) (SD 1). The optimal bond lengths is inversely related to the bond strength and the stability of the bond. The lesser the bond lengths, more will be the stability of the bond. Although, the bond angle is inversely proportional to the bond length. Some selected bond lengths and bond angles for the optimized geometries corresponding to the charge transfer parts of the AA are mentioned in Tables 2 and 3 . All the AA possess non-planar geometries. The Histidine molecule have dihedral angles C8 – C6 – C7 – C9 and C8 – C6 – C7 – N4. It consists of a carboxyl group and an amino group and its side chain have a basic group containing an imidazole ring. The low values of bond lengths also result in the high bond dissociation energy. The 1O – 20H bond of the carboxyl group has the lowest bond length of 0.977 Å that showed the stability of the bond. The bond 7C – 6C of alkyl group has the maximum bond length (1.54 Å). Thus, this bond might possess low bond dissociation energy. The angle associated to the pyrrolidine ring 16H – 10C – 8C has the minimum bond angle of 29.29° that indicated the strength of the pyrrolidine ring. Isoleucine have carboxyl group and amino group connected to 5C atom. The carbon chain showed the non-planarity of the molecule. The angle between the 1O – 9C – 2O bond of carboxyl group is 122.65° and angle 20H – 3N – 21H of the amino group is 106.31°. The bond angle between the carboxyl group is comparatively higher than that between the amino group which shows the high probability of the amino bonds to get dissociated. The structure of Leucine is quite similar to Isoleucine having amino and carboxyl group attached to the 6C atom of carbon chain. The 22H – 1O bond of carboxyl group in Leucine have minimum bond length of 0.97 Å and bond 6C – 3N that connects the amino group with the geometry have the maximum bond length of 1.47 Å. Unlike Leucine , and Isoleucine (have single amino group), the Lysine have two amino groups connected to 8C and 9C atom and carboxyl connected to 10C atom. The molecule consists of a straight carbon chain without any branched alkanes. However, the bond between the oxygen and hydrogen of the carboxyl group has the minimum bond length of 0.97 Å. The minimal bond lengths showed the strength of these bonds and reflects the charge accepting behavior of the carboxyl group. The bonds between the nitrogen and hydrogen atoms of amino groups are close for both the amino groups and quite higher than the bond lengths associated to carboxyl group. The bond angle 1O – 10C – 2O (122 °) associated to the carboxyl group also shows the accepting nature of the carboxyl group. The amino and carboxyl group of the Methionine molecule are connected to 6C atom of carbon chain. Apart of amino and carboxyl groups, one sulphur atom 1S is also connected to 7C atom of carbon chain. Being both π- and σ-donor, 1S atom might impart in being the charge donating moiety. The bond length of 1S – 7C bond is 1.90 Å that was highest in all the bond length. The bond lengths corresponding to amino groups like 15H – 4N (1.01Å) and 16H – 4N (1.01 Å) are less than the bonds corresponding to the carboxyl group like 8C – 2O (1.38 Å). Phenylalanine has a benzene ring attached to 4C atom and one amino and carboxyl group were attached to 5C atom. Dihedral angle 6C – 4C – 5C – 3N is seen to be responsible for the non-planer geometry of Phenylalanine . The bond 5C – 9C bond of the carbon chain have the maximum bond length of 1.51 Å. The bonds 18H – 3N and 19H – 3N have high bond lengths of 1.00 Å and 1.01 Å respectively. These bond lengths are lower than the bond length 23H – 1O corresponding to the carboxyl group 0.97 Å. The higher bond length of amino group reveals the tendency of these bonds of getting easily dissociated. The amino and carboxyl group in the Threonine are attached to 6C atom. Apart of these two groups, one hydroxyl group is also attached to 5C atom. The bond length 17H – 2O (0.97 Å) and 16H – 1O (0.97 Å) associated to carboxyl group were less in magnitude than the bonds 14H – 4N (1.01 Å) and 15H – 4N (1.01 Å) associated to amino group. The bond angle 2O – 8C – 3O with magnitude 122.406° is also greater than bond angles 14H – 4N – 15H (111.48°) displays the high chances of dissociation of amino bonds. Tryptophan consists a benzene ring and a pyrrolidine ring mutually connected with 7C – 9C bond. The bonds 24H – 4N (1.01 Å) and 25H – 4N (1.01 Å) of amino group have higher bond lengths than the bond 1O – 27H (0.97 Å). Valine molecule comprises one amino and one carboxyl group attached to 5C atom. The 1O – 19H bond of carboxyl group has bond length 0.97 Å that is less than bond length of 17H – 3N (1.01 Å). The increasing order of electrostatic potential energies of the AA was Methionine < Tryptophan < Phenylalanine < Histidine < Lysine < Leucine < Isoleucine < Threonine < Valine (SD 1). Negative magnitudes of electrostatic potential reflect the tendency of the molecule to attract the charge density. The optimized structures of all the AA indicated that the bond lengths and bond angles corresponding to the amino groups are smaller than the bond lengths and bond angles corresponding to carboxyl groups that shows the enhanced chances of dissociations of amino bonds. This in turns, shows the possibility of intramolecular interactions within the molecules that reveals the reactivity of the AA. 3.2 Charge analysis Mulliken charge analysis helps in the understanding of the charge contribution corresponding to each and every atom of the systems (Senthilkumar et al. 2021). The charge plot of EAA shows the positive charge impact of H atoms and negative charge contribution of O atoms (Fig. 1). The charges corresponding to each atom of the Histidine molecule are plotted in Fig. 1( a ). 9C and 20H atoms of carboxyl group of Histidine showed the maximum positive charge of 0.54 e and 0.39 e respectively. The 3N and 5N atoms associated to pyrrolidine ring shows negative charge of -0.73 e and − 0.37 e respectively. The 4N, 17H and 18H atoms of the amino group has charge − 0.67 e, 0.30 e and 0.29 e respectively. The Mulliken charge distribution of Histidine showed the huge variation in charge between pyrrolidine ring and carboxyl and amino groups. The Mulliken charge plot of Isoleucine is shows in Fig. 1( b ). In Isoleucine , the charge variation is observed among the 1O (-0.55 e), 2O (-0.36 e), 9C (0.47 e) and 22H (0.38 e) atoms of carboxyl group and 3N (-0.64 e), 20H (0.29 e) and 21H (0.38 e) of amino group. Similar kind of variation of charge is observed in Leucine molecule in 1O (-0.55 e), 2O (-0.38 e), 9C (0.55 e) and 22H (0.38 e) atoms of carboxyl group and 3N (-0.69 e), 20H (0.29 e) and 21H (0.3 e) of amino group. Two amino groups in Lysine with atoms 3N (-0.66 e), 20H (0.29 e), 21H (0.29 e), and 4N (-0.71 e), 22H (0.28 e), 23H (0.28 e) and a carboxyl group with atoms 1O (-0.56 e), 2O (-0.36 e), 10C (0.45 e) and 24H (0.38 e) showed the immense charge variation. The Mulliken charge distribution of the atoms in Methionine is illustrated in Fig. 1( e ). Charge distribution predicts that 8C atom of carboxyl group shows the highest magnitude of positive charge equals to 0.48 e and 4N atom of amino group shows the negative charge of -0.72 e. Thus, these atoms reflects the major charge variation in the Methionine molecule. In Phenylalanine , 9C atom of amino group have the maximum positive charge and 3N atom of the carboxyl group have negative charge with maximum magnitude of -0.69 e. Mulliken charge distribution of the rest of the atoms of Phenylalanine is shown in Fig. 1( f ). The Threonine molecule have an –OH (hydroxyl) group connected to C5 atom of the carbon chain with atoms 1O and 16H with charge − 0.60 e and 0.36 e respectively (Fig. 1( g )). Apart of this, the 8C atom of carboxyl group has maximum positive charge of 0.53 e. The 4N atom of amino group of Threonine have charge − 0.68 e. Thus, the charge variations among the atoms of hydroxyl, carboxyl and amino group. The 3N atom connected to pyrrolidine ring in Tryptophan molecule have the highest magnitude of negative charge − 0.81 e. The 3C atom of carboxyl group have the highest positive charge 0.53 e (Fig. 1( h )). These atoms impart in the major charge variation in Tryptophan . In Valine , the 8C atom of carboxyl group shows the highest charge of 0.50 e and 3N atom of amino group have charge − 0.68 e. The rest of the Mulliken charge distribution for Valine is illustrated in Fig. 1( i ). The variation in charge is observed between the functional groups (say amino and carboxyl groups). This variation can be considered due to the delocalization of the charges from the carboxyl part to the amino part of the molecule. This may lead to enhanced intramolecular interactions within the molecule. Therefore, the AA can be considered as chemically reactive. 3.3 Chemical reactivity FMO theory is a practical model which describes the chemical reactivity of the molecule (Swartling et al. 2018). The energy corresponding to HOMO and LUMO are termed as FMO energies (Saito et al. 2020). HOMO is the electron donating orbital and LUMO is the electron accepting orbital (Rana et al. 2016). The HOMO-LUMO map of different probe systems are shown in Fig. 2, that represent the distribution of highest occupied orbitals throughout the geometry and the distribution of lowest occupied orbitals in the functional groups. There is a significant energy associated to these orbitals. The computed values of FMO parameters of all the AA are mentioned in Table 4 . The energy difference between the LUMO and HOMO energies is called band gap ( ΔE ). The low value of ΔE validates the easy excitation tendency of the free electron cloud from the lower states to the higher energy states. The value of ΔE for Histidine is 4.97 eV. This value is lower than Isoleucine (5.99 eV), Leucine (5.95 eV), Lysine (5.42 eV), Methionine (5.60 eV), Phenylalanine (5.82 eV), Threonine (6.02 eV), Tryptophan (5.11 eV), and Valine (5.93 eV). The values of ΔE for all the AA is found to be lower than the ΔE values of reference materials like Urea (7.43 eV) and KDP (6.83 eV). The low value of the energy gap shows the high possibility of the charge transfer within the molecule. The increasing order of ΔE values for AA is Histidine < Tryptophan < Lysine < Methionine < Phenylalanine < Valine < Leucine < Isoleucine < Threonine . The IP shows the potential that is needed to eject the electron from the nucleophilic atom. The values of IP for the Histidine , Isoleucine , Leucine , Methionine , Phenylalanine , Threonine and Valine are 6.20, 6.47, 6.39, 6.23, 6.34, 6.73, and 6.52 eV. These values are higher than IP for Lysine (5.94 eV) and Tryptophan (5.61 eV). The increasing order of IP was Tryptophan < Lysine < Histidine < Methionine < Phenylalanine < Leucine < Isoleucine < Valine < Threonine . This showed that Tryptophan has the better capability to donate the charge easily than the other AA. The EA is a measure of the magnitude of energy that is liberated while attracting the free charge cloud. The high values of EA shows that the molecule accepts the free charge cloud more easily. Histidine has the highest value of EA equals to 1.22 eV. The values of EA for other AA are Isoleucine (0.48 eV), Leucine (0.43 eV), Lysine (0.51 eV), Methionine (0.62 eV), Phenylalanine (0.52 eV), Threonine (0.70 eV), Tryptophan (0.50 eV), and Valine (0.59 eV). The increasing order of IP is Leucine < Isoleucine < Tryptophan < Lysine < Phenylalanine < Valine < Methionine < Threonine < Histidine . So, Histidine molecule has the maximum value of EA showing its enhanced capability of attracting the charge cloud. The values of CP in raising order are Threonine (-3.16 eV) < Histidine (-3.71 eV) < Valine (-3.55 eV) < Isoleucine (-3.48 eV) < Phenylalanine (-3.43 eV) < Methionine (-3.42 eV) < Leucine (-3.41 eV) < Lysine (-3.22 eV) < Tryptophan (-3.05 eV). As the lower CP are considered as the most stable one, the Threonine can be considered as the molecule undergoing the chemical process more easily with associating low amount of energy. Higher the value of χ , more strongly the electrophilic it will be able to pull the free charges towards itself. Threonine has the highest value of χ which shows that it can strongly attract the shared electrons. The χ is minimum for Tryptophan (3.05 eV) and the value raised in order: Tryptophan < Lysine < Leucine < Methionine < Phenylalanine < Isoleucine < Valine < Histidine < Threonine . The η gives the extent of the chemical hardness of the molecule or it accounts the resistance of the molecule towards deformity after undergoing a chemical reaction. The molecules with higher values of η can be considered more chemically stable. Threonine has the highest η equals to 3.01 eV as compared to the other AA. In contrary, the S is the opposite of η and was used to show the receptivity of the molecules. The molecules with high values of softness are easily deformed or get dissociated while involving in chemical reaction. Thus, low values of S are considered good for a chemically reactive molecule. The S is in order: Isoleucine = Threonine < Leucine < Valine < Phenylalanine < Methionine < Lysine < Tryptophan < Histidine . It is observed that Isoleucine and Leucine have the equally lowest values of S that shows their chemical stability than other AA by the virtue of S . However, the difference between the magnitudes of FMO parameters of other AA is not such observable. Thus, it can be said that the AA are chemically reactive in nature and they can give involvement on chemical reactions. The settlement of the HOMO-LUMO surfaces for AA is illustrated in Fig. 2. These surfaces basically show the location of the orbitals in molecular orbital wave function, respectively. The HOMO shows the donor orbitals (positive) and LUMO shows the acceptor orbitals (negative). The HOMO-LUMO surfaces of Histidine molecule (Fig. 2( a )) are seen to get drifted from pyrrolidine ring towards the amino and carboxyl group. Similar kind of surface dislocation is seen in Lysine (Fig. 2( d )), Methionine (Fig. 2( e )) and Tryptophan (Fig. 2( h )). In Lysine , the positive and negative surfaces are settled over amino group in HOMO and get drifted over carboxyl group in LUMO. This shows the displacement of charge cloud from amino to carboxyl group in Lysine . Methionine has positive and negative surfaces settled over S1 atom in HOMO while they are settled over functional groups in LUMO. In Tryptophan , the positive and negative surfaces shift from benzene ring and pyrrolidine ring towards amino and carboxyl group. The shifting of the surfaces shows the direction of the shifting of the charge cloud. The shifting of orbitals in rest of the AA was not that much far as in the former described AA. The orbitals in Isoleucine (Fig. 2( b )), Leucine (Fig. 2( c )), Phenylalanine (Fig. 2( f )), Threonine (Fig. 2( g )) and Valine (Fig. 2( i )) are uniformly distributed over the geometries and are locally shifted. The orbitals in Isoleucine and Leucine are seemed to shift among the functional groups. That means, red colored surface seems to be replaced by green and vice versa. This shows that the charge transfer occurred in between the atoms of the respective amino and carboxyl groups of Isoleucine and Leucine . In Phenylalanine , red color surface appeared over the amino and carboxyl group in HOMO surface that transited to red surface in LUMO surface. Similar kind of shifting of positive and negative orbitals is observed in Threonine and Valine . Thus, it is observed that the presence of functional groups induces the shifting of donor and acceptor surfaces in AA. This shifting can be considered due to the dislocation of the charge cloud. Thus, the dislocation of the charge cloud give rise to immense ICT within the title molecule. Moreover, it can be said that the FMO parameters and HOMO-LUMO surfaces showed the enhanced possibility of ICT within the AA and makes them chemically reactive molecules. 3.4 Molecular Electrostatic Potential (MEP) analysis The displacement of the charge cloud is provided by the MEP surface color code. The red and yellow color of the MEP is due to the nucleophilic atoms (Sheikhi et al. 2019). Mainly the nitrogen molecules are responsible for the red color of the MEP (Khnifira et al. 2021). The O atoms being highly electronegative imparts the blue color of the MEP surface (Pathade and Jagdale 2020). The MEP surface of all the AA are illustrated in Fig. 3. This surface indicates the availability and location of the nucleophilic and electrophilic regions of the AA. This surface basically shows the displacement of the charge cloud from the positive part towards the negative part of the AA. For Histidine molecule, the variation of the charge is seen among the 1O, 2O, 9C, and 20H atoms of carboxyl group and 4N, 17H, and 18H atoms of amino group. Being highly resonating, the amino group imparts in donating the free electron cloud. The carboxyl group, on the other hand acts as electron withdrawing group due to the high electronegativity of the oxygen atoms. Thus, these groups give rise to the nucleophilic and electrophilic regions in the MEP. Moreover, the pyrrolidine ring attached to the carbon chain imparts the red color to the MEP surface due the presence of 3N and 5N atoms. Thus, the ICT is seen from the pyrrolidine ring and amino group towards the carboxyl group. The MEP’s counter plots were also used for the representation of the regions having electrostatic field of AA. The area with dense counter lines is the area with stronger electrostatic field (Idouhli et al. 2021). The field lines are found denser near the 2O atom of carboxyl group and 5N atom of pyrrolidine ring. The regions near 4N, 5N and 2O atoms have high electrostatic field (Fig. 4 (a) ). The bonds falling in the region of the aligned electrostatic field undergoes the simultaneous shortening and elongation of the bond. Therefore, this process leads to the weakening in the bonds, and ultimately breaking of the bond. Thus, the bonds surrounded with dense electrostatic field counter lines are weak enough to get dissociate. This leads to the formation and displacement of free electron cloud which is a key of ICT. The Histidine molecule, therefore, have the field lines largely accumulated near the carboxyl group, amino group, and pyrrolidine ring that validates the ICT between the functional groups as stated from Mulliken charge distribution and MEP surface. In the MEP surface of AA like Isoleucine (Fig. 3(b) ), Leucine (Fig. 3(c) ), Lysine (Fig. 3(d) ), Methionine (Fig. 3(e) ), Phenylalanine (Fig. 3(f) ), Threonine (Fig. 3(g) ), and Valine (Fig. 3(i) ), the carboxyl group show immense high electronegativity giving rise to blue color of MEP surface and amino group imparts to the yellow color indicating the nucleophilic region. The ICT in these molecules was seen to be dislocated from the amino group towards carboxyl group. The counter plots of the Isoleucine (Fig. 4(b) ), Leucine (Fig. 4(c) ), Lysine (Fig. 4(d) ), Methionine (Fig. 4(e) ), Phenylalanine (Fig. 4(f) ), Threonine (Fig. 4(g) ), and Valine (Fig. 4(i) ) are highly accumulated near the functional groups in the respective molecules. This validates the ICT predicted by MEP surface. The bonds of the functional groups have electrostatic field counter lines nearby that will lead to the weakening and dissociation of the bonds. This, in turns, can be considered the main reason of the evolution of the charge cloud from these functional groups and inducing ICT within the AA. The MEP surface of Tryptophan AA is illustrated in Fig. 3 (h) ). Similar to the Histidine , the Tryptophan also has a pyrrolidine ring that acted as a nucleophilic part. The yellow color is uniformly spread over the benzene ring connected to pyrrolidine ring showing the negativity of the benzene ring. The 4N, 24H, and 25H of the phenol group, and 1O, 2O, 13C, and 27H atoms of carboxyl group, however, imparts the blue color indicating the donation of charge cloud from these regions. Thus, the ICT in Tryptophan is seen from pyrrolidine ring, carboxyl and amino group towards the benzene ring. The counter plot of Tryptophan is illustrated in Fig. 4( h ). Alike the other AA, the counter plot lines in Tryptophan are finely spread over the carboxyl and amino group showing the evolution of the charge cloud from these regions. Thus, the presence of nucleophilic and electrophilic regions validates the high degree of electrostatic interactions within the molecule. This show that there is a possibility of charge transfer from nucleophilic region to the electrophilic region. Thus, the variation of the electronic distributions within the molecule gives a possibility of the molecule being highly reactive molecule. 3.5 Vibrational analysis The Raman modes are investigated for AA to study about its vibrational features. The Raman spectra helps in the studying the polarizing ability of the compound as the polarizability of any compound is proportional to the Raman intensity, which in turns leads to the NLO behavior of the compound (John et al. 2020; Prettre and Pullman 1987). The computed Raman spectra for all the AA is shown in Fig. 5. High frequency vibrations are observed for AA in range of 1000–2000 cm − 1 and 2500–4000 cm − 1 . The vibrational modes with high peaks with their corresponding Raman intensities are mentioned in SD 2. For Histidine molecule, the symmetric stretching (ν OH ) mode is observed at 3637.7 cm − 1 . The 17H – 4N – 18H atoms of amino group show ν NH mode at 3516.02 cm − 1 . The ν CH modes of the Histidine showed three major peaks at 3012.7 (ν 6C−12H and ν 6C−13H ), 3098.73 (ν 6C−12H and ν 6C−13H ) and 3271.1 cm − 1 (ν 10C−16H and ν 11C−19H ). The 8C = 10C bond of the benzene ring shows ν CC mode at frequency 1602.72 cm − 1 . The torsional bending of C – H bond on the plane (δ CH ) mode shows the bending of the bond between 6C – 12H and 7C – 14H bonds in the plane. However, these modes corresponding to carbon chain have the maximum Raman intensity equal to 1631.56. Figure 5( a ) illustrated the computed Raman spectra of Histidine . For Isoleucine , the ν OH mode is observed at 3583.26 cm − 1 . The 17H – 4N – 18H atoms of amino group show ν NH and asymmetric linear stretching (α NH ) mode at 3436.4 and 3515.96 cm − 1 respectively. The ν CH mode of the Isoleucine has a major peak at 2992.93 cm − 1 leading the stretching of the hydrogens bonded with 6C, 7C and 8C atoms of carbon chain. The asymmetric stretching of C – H bonds have two major peaks, one at 3023.95 cm − 1 (α 5C−11H ) and another at 3055.33 cm − 1 (C–H bonds attached to 7C and 8C). The δ CH modes shows the bending of the bond between 1143.7 to 1528.86 cm − 1 . The stretching between 4C – 6C atoms of carbon chain shows mode at 793 cm − 1 . Figure 5( b ) illustrated the computed Raman spectra of Isoleucine . The Leucine molecule has α NH mode of 3N – 20H and 3N – 21H at frequency 3641.67 cm − 1 . The stretching between 1O – 22H of the carboxyl group is observed at 3623.64 cm − 1 . ν NH mode of amino group bonds 3N – 20H and 3N – 21H is observed at frequency 3641.67 cm − 1 . Three sharp peaks are observed for stretching of C – H bonds at 2978.01, 3016.4 and 3081.21 cm − 1 . Twenty modes of bending of C – H bonds was observed in range 975.95-1529.85 cm − 1 . High Raman intensity of 1637.03 is observed for C – C bond of the carbon chain for mode 782.41 cm − 1 . The computed Raman spectra of Leucine is illustrated in Fig. 5( c ). The Raman spectra of Lysine (Fig. 5( d )) has three high intensity peaks at 2906.07, 2984.77, and 3051.01 cm − 1 showing ν CH modes of 8C – 6C – 5C – 7C – 9C chain. The 10C = 2O bond of carboxyl chain showed ν CO mode at 1711.01 cm − 1 . The δ CH mode shows the bending modes from 1000.04 to 1528.41 cm − 1 . The 2O – 20H bond of carboxyl group of Methionine vibrates linearly at 3623.06 cm − 1 . The 16H – 4N – 15H bond of amino group in Methionine shows ν NH vibrational mode at 3499.93 cm − 1 . There are two high intensity peaks observed for C – H linear stretching. The vibration of 17H, 18H 19H attached to 9C bound to 1S atom have ν CH mode at 3048.77 cm − 1 . The α CH for 13H and 14H attached to 7C atom was observed at 3145.22 cm − 1 . The ν CO mode between 8C = 3O of carboxyl group is at frequency 1709.03 cm − 1 . The δ CH modes are observed between 1214.06 to 1495.78 cm − 1 . The vibration of 1S bonded between 7C and 9C has high intensity of 4042.93 cm − 1 at frequency 655.69 cm − 1 . The ν CH at 588.04 cm − 1 has the highest Raman intensity of 9103.99 cm − 1 . The other modes are illustrated in Fig. 5(e). The computed Raman spectra of Phenylalanine is shown in Fig. 5( f ). The spectra highlighted the high frequency mode α NH of amino group at 3654.76 cm − 1 and ν NH mode at 3529.77 cm − 1 . The 1O – 23H atoms of carboxyl group showed ν OH mode at 3654.03 cm − 1 . The ν CH vibrations gave the sharp peaks in between frequency 3023.73 cm − 1 and 3194.86 cm − 1 . The δ CH modes were observed between 1030.89 cm − 1 to 1520.44 cm − 1 . The ν CC mode between 5C and 9C have vibration at 762.06 cm − 1 and δ CC mode of benzene ring occurs at 653.65 cm − 1 . The computed Raman spectra of Threonine was shown in Fig. 5( g ). There are two high frequency peaks for ν OH modes of O – H bonds. The ν OH mode for 1O – 16H bond of hydroxyl group exists for frequency 3667.96 cm − 1 . The 4N, 14H and 15H atoms of amino group has frequency equals to 3518 cm − 1 for ν NH and 1726.8 cm − 1 for δ NH mode. The 2O – 17H bond of carboxyl group have ν OH mode at 3629.16 cm − 1 . The 7C atom of carbon chain has two different modes, first ν CH 3038.87 cm − 1 and second α CH at 3119.98 cm − 1 . The δ CH modes are observed between 746.85 to 1537.8 cm − 1 . However, the δ CH mode at frequency 746.85 cm − 1 has the highest intensity of 2012.59 cm − 1 . The Tryptophan has one pyrrolidine ring attached to carbon chain and benzene ring. The 3N – 20H bond of the pyrrolidine ring have ν NH mode at 3684.64 cm − 1 . The ν NH mode corresponding to amino bonds 4N – 25H and 4N – 25H has frequency 3496.44 cm − 1 . The 1O – 27H bond of carboxyl group has mode ν CH at 3621.77 cm − 1 . The α CH mode is for the stretching of C – H bonds of benzene rings (11C – 21H, 12C – 22H and 14C – 23H). The 11C, 12C, 14C and 15C atoms of benzene ring vibrates simultaneously and leads the highest intensity mode for C – H bonds with frequency 3195.34 cm − 1 . The δ CH modes has multiple peaks between 775.11 to 1659.72 cm − 1 . However, the δ CH mode at 1587.6 cm − 1 is reported as the highest Raman intensity mode with magnitude 2423.57 cm − 1 . The computed spectra of Tryptophan is illustrated in Fig. 5( h ). The computed Raman modes of Valine are shown in Fig. 5( i ). The 1O – 19H bond of carboxyl group has stretching mode ν OH at 3619.89 cm − 1 . The ν NH mode between amino group 3N – 17H and 3N – 18H bond exists for frequency 3508.35 cm − 1 . ν CH modes has two sharp peaks for C – H vibrations of carbon chain at frequency 3025.1 cm − 1 and 3085.17 cm − 1 . For δ CH , the highest frequency mode is at 1527.06 cm − 1 . The 1O – 19H bond of carboxyl group has frequency 1285.89 cm − 1 . The stretching between 4C – 5C is observed at 946.09 cm − 1 . The highest Raman intensity of 1193.34 cm − 1 is observed for ν CC . the spectral analysis done for the AA showed the high Raman intensity for the modes associated to the functional groups present in the AA that showed the high chemical reactivity of these groups. All the above mentioned Raman modes reveals strong activity of the AA. Thus, the active Raman modes leads to the polarizability enhancement of the AA making them active and potent NLO materials. 3.6 UV-Vis spectral analysis To understand the electronic transitions of the AA, the UV-Vis absorption peak is computed (Fig. 6). The electronic absorption spectra was calculated using time dependent-DFT method (TD-DFT) based on B3LYP/6-311G level optimization. The obtained spectra provide the information about the vertical excitation energies ( E ), oscillator strengths ( f ), and the wavelength ( λ ) at which the transitions occur. A broad and strong absorption band of the Histidine molecule is recorded within the 200–350 nm range (Fig. 6( a )). The π-π* and n-π* electronic transitions occurring at highest wavelengths are represented by transitions S 0 →S 1 , S 2 , S 3 (SD 3). The transition S 0 →S 1 was observed at 294.59 nm with oscillator strength 0.0028. The excitation energy for this transition is observed as 4.20eV. The excitation energy of the electrons in transition S 0 →S 2 was observed as 4.65 eV at 266.54 nm wavelength and 0.0229 oscillator strength. This gave the peak of the spectra and is responsible for the formation of the spectra. The excitation energy of S 0 →S 2 transition is nearly equal to the value of ΔE (say 4.97eV) we have obtained in HOMO-LUMO analysis. Generally, the band gap computed from FMO analysis represents the transition of the electrons from lower energy level to the higher energy level. So, the similarity of these values validates the results and shows the stability of the molecule. The electrons associated to the transition S 0 →S 3 have excitation energy equals to 5.08 eV and oscillator strength 0.0024. This transition is observed at wavelength 243.98 nm. Similar to Histidine , Lysine (Fig. 6( d )), Methionine (Fig. 6( e )), Phenylalanine (Fig. 6( f )) and Tryptophan (Fig. 6( h )) also have single broad absorption band with peaks at 250, 251, 226 and 260 nm respectively. The transition S 0 →S 1 that majorly imparts in the formation of the absorption band in these molecules have excitation energies 4.95, 4.93, 4.82 and 4.38 eV respectively. Similar to Histidine , the excitation of these AA coincides with the ΔE obtained from FMO analysis. The details of the other transition are mentioned in SD 3. Isoleucine has broad band ranging from 175–300 nm having peak at 197.96 nm and 6.26 eV excitation energy and a local-maxima near 252.42 nm with 5.57 eV excitation energy (Fig. 6( b )). These two transitions majorly impart in the formation of the absorption spectra. Two absorption peaks are observed for the AA Leucine (Fig. 6( c )), Threonine (Fig. 6( g )) and Valine (Fig. 6( i )). These bands show the electronic transitions from ground state to an excited state. The S 0 →S 1 transition of Leucine exists at wavelength 255.46 nm with excitation energy 4.85 eV. This transition leads to the formation of the second absorption peak of the Leucine ’s UV-Vis spectra. The first peak of Leucine is observed at wavelength 199.32 nm with excitation energy 6.22 eV. The excitation energy of the S 0 →S 2 transition is close to the HOMO-LUMO band gap. For Threonine , two sharp peaks are observed at wavelength 207.87 nm and 250.8 nm with excitation energies 5.57 eV and 4.94 eV respectively (Fig. 6( g )). Valine has two absorption peaks, first at 196.42 nm with excitation energy 6.31 eV undergoing S 0 →S 3 transition and second at 253.14 nm with excitation energy 4.89 eV undergoing S 0 →S 1 transition. Moreover, the HOMO-LUMO band gap too coincides with the excitation energy of S 0 →S 2 transition. The excitation energies of electronic transitions for the AA are relatively close to the values of ΔE obtained from FMO analysis of the respective AA. These transitions show the enhanced intramolecular interactions between the lone pair (n) electrons and the π electron and also impart in molecule’s unsaturation (Fleck and Petrosyan 2010). Thus, it can be said that the AA are highly reactive in nature. Moreover, the S 0 →S 1 transition for Histidine and Tryptophan AA has highest wavelengths compared to the transitions of other AA. Thus, Histidine and Tryptophan can be considered more chemically reactive. 3.8 NLO analysis Theoretical NLO calculation is most important part in identifying a potential NLO active molecule. The characterization of the behavior of the material in the presence of an applied electric field is accounted by phenomenon of polarization (Rana et al. 2018). Polarization simply tells us about the correlation between the interaction between the electron and nucleus. The multi-atom systems, such as molecules with large number of atoms have high number of electrons available as a charge cloud. The large the charge cloud is, the larger will be the possibility of charge dislocation. The highly raised values of the polarizability parameters are the result of the charge displacement. The literature survey revealed high optical nonlinearity among many organic and semi organic NLO materials. Thus, it is assumed that the materials having higher optical nonlinearity must be highly NLO active. The µ total , α total , Δ α and β total is computed for all the EAA and is listed in Table 5 . These parameters are basically expressed as the coefficients of standard Taylor series expansion of energy when the material interacts with weak and homogeneous externally applied electric field. Dipole moment is the first parameter in the list of polar properties as it accounts the polar nature of the molecule. The value of µ total for AA are Histidine (2.19 Debye), Isoleucine (0.49 Debye), Leucine (0.73 Debye), Lysine (0.34 Debye), Methionine (0.37 Debye), Phenylalanine (0.63 Debye), Threonine (0.98 Debye), Tryptophan (1.16 Debye), and Valine (0.51 Debye). The electronic communication between acceptor and donor groups leads to high ICT. This results in the high values of polarizability and hyperpolarizability of the molecule. Thus, the transfer of the electron cloud from donor group towards acceptor group leads to the high value of the β total . The first order hyperpolarizability has been computed using finite field theory approach (Kirtman et al. 1998). The computed values of α total are Histidine (12.60×10 − 24 esu), Isoleucine (11.60×10 − 24 esu), Leucine (11.63×10 − 24 esu), Lysine (12.95×10 − 24 esu), Methionine (12.78×10 − 24 esu), Phenylalanine (15.40×10 − 24 esu), Threonine (8.85×10 − 24 esu), Tryptophan (9.46×10 − 24 esu), and Valine (10.04×10 − 24 esu). All these values are higher than α total of Urea (5.66×10 − 24 esu). Among all the AA, Phenylalanine has the highest value of α total . It was thrice the α total of Urea. The computed values of Δ α are Histidine (26.77×10 − 24 esu), Isoleucine (21.53×10 − 24 esu), Leucine (18.14×10 − 24 esu), Lysine (27.35×10 − 24 esu), Methionine (27.07×10 − 24 esu), Phenylalanine (32.23×10 − 24 esu), Threonine (15.56×10 − 24 esu), Tryptophan (14.58×10 − 24 esu), and Valine (17.68×10 − 24 esu). These values are also higher than Δ α of Urea (6.30×10 − 24 esu). Again, the Δ α of Phenylalanine was found five times higher than Δ α of Urea. The value of β total for Histidine (1.92×10 − 30 esu), Isoleucine (1.23×10 − 30 esu), Leucine (1.4×10 − 30 esu), Lysine (2.06×10 − 30 esu), Methionine (1.37×10 − 30 esu), Phenylalanine (3.11×10 − 30 esu), Threonine (0.94×10 − 30 esu), Tryptophan (1.85×10 − 30 esu), and Valine (1.75×10 − 30 esu) is higher than β total of Urea (0.78×10 − 30 esu). But the value of β total of Phenylalanine is approximately four times higher than that of Urea. For the validation of the results, the β total of the Phenylalanine is also compared with some such NLO materials that have already been worked on and gave better results. The β total of Phenylalanine is also found two and a half times higher than β total of Phenyl urea (2.04×10 − 30 esu) (Marappan et al. 2019) and approximately one and a half times higher than β total of 3-nitroaniline (1.34×10 − 30 esu) (Krishnakumar and Nagalakshmi 2008). So, it simply suggests that Phenylalanine has the highest magnitude of the NLO parameters among all the AA. Thus, the comparative study shows that Phenylalanine have the high capability to act as a potent NLO responsive molecule. 4. Conclusion In the presented work, the comparison of optoelectronic and quantum chemical features have been performed for all the EAA. This was done with the help of ground state structure optimization and TD-DFT calculations. The variation in the bond lengths and bond angles of the AA presented that the regions near the functional groups present in the respective AA is the region with high chances of being chemically reactive. The Mulliken charge analysis is done to see the actual charge transfer among the AA. The variation in the charge between the amino and carboxyl group highlighted these regions as the most reactive regions. The global reactivity parameters and MEP surfaces also verified the reactivity of the AA. The π-π* and n-π* electronic transitions are found to be occurring at highest wavelengths in computed absorption spectra. High Raman intensity modes are obtained for the AA from computed vibrational spectra. The Raman modes and electronic transitions obtained in the spectra validates the high polarizability of the AA molecules. For validating the high polarizability of the AA, the polarizability parameters ( µ total , α total , Δα and β total ) were computed. The β total of Phenylalanine was found higher was found higher than all the other AA and reference materials Urea, Phenyl urea and 3-nitroaniline. The comparison was sufficiently high enough to validate the NLO candidature of Phenylalanine . By this study, we can conclude that Phenylalanine is the most active EAA among all the others and it can be used for experimental validations in future. There is a strong possibility to use it in NLO applications. Declarations Author’s contribution Shradha Lakhera: Data curation, Writing-Original draft preparation, Visualization, Investigation, Software, Validation. Meenakshi Rana: Conceptualization, Methodology, Writing-Reviewing and Editing, Supervision Kamal Devlal: Conceptualization, Writing- Reviewing and Editing Conflict of interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. 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Struct. 1226 , 129354 (2021). https://doi.org/10.1016/j.molstruc.2020.129354 Sheikhi, M., Shahab, S., Alnajjar, R., Ahmadianarog, M.: Adsorption Properties of the New Anti-Cancer Drug Alectinib on CNT (6,6-6) Nanotube: Geometry Optimization, Molecular Structure, Spectroscopic (NMR, UV/Vis, Excited State), FMO, MEP and HOMO–LUMO Investigations. J Clust Sci. 30 , 83–96 (2019). https://doi.org/10.1007/s10876-018-1460-9 Swartling, D. J., Coonce, J. G., Cashman, D. J.: Using Balloons to Model Pi-Conjugated Systems and to Teach Frontier Molecular Orbital Theory, World J. Chem. Educ. 6 , 102-106 (2018). https://doi.org/10.12691/wjce-6-2-5 Soares, J. D. P., Scott, H. L., Teixeira, F. J., Gustavo, P. D.: Dietary Amino Acids and Immunonutrition Supplementation in Cancer-Induced Skeletal Muscle Mass Depletion: A Mini-Review Curr. Pharm. Des. 26 970-978 (2020). https://doi.org/10.2174/1381612826666200218100420 Then, A., Mácha, K., Ibrahim, B.: A novel method for achieving an optimal classification of the proteinogenic amino acids. Sci Rep. 10 15321 (2020). https://doi.org/10.1038/s41598-020-72174-5 Ullah, F., Kosar, N., Ali, A., Maria, Mahmood, T., Ayub, K.: Alkaline earth metal decorated phosphide nanoclusters for potential applications as high performance NLO materials, A first principle study, Phys. E: Low-Dimens. Syst. Nanostructures. 118 113906 (2020). https://doi.org/10.1016/j.physe.2019.113906 Visscher, K. M., Geerke, D. P.: Deriving Force-Field Parameters from First Principles Using a Polarizable and Higher Order Dispersion Model J. Chem. Theory Comput. 15 , 1875–1883 (2019). https://doi.org/10.1021/acs.jctc.8b01105 Wang, H., Xi, Q., Liang, P., Zheng, L., Hong, Y., Zuo, Y.: IHEC_RAAC: an online platform for identifying human enzyme classes via reduced amino acid cluster strategy. Amino Acids. 53 , 239–251(2021). https://doi.org/10.1007/s00726-021-02941-9 Tables Table 1. Optimized structures of EAA by standard B3LYP/6-311G basis set with PubChem IDs and chemical formulas. Table 2. Bond lengths corresponding to functional groups of the optimized structures of EAA (Bond length is in Å). Bond Bond length Bond Bond length Histidine 1O – 9C 1.37 4N – 17H 1.01 2O = 9C 1.23 4N – 18H 1.01 20H – 1O 0.97 3N – 11C 1.37 C8 = C10 1.37 5N – 11C 1.33 Isoleucine 22H – 1O 0.98 20H – 3N 1.01 1O – 9C 1.35 21H – 3N 1.01 9C = 2O 1.22 5C – 3N 1.46 Leucine 22H – 1O 0.97 20H – 3N 1.00 1O – 9C 1.37 21H – 3N 1.01 9C = 2O 1.23 6C – 3N 1.47 Lysine 1O – 24H 0.97 20H – 3N 1.01 1O – 10C 1.38 21H – 3N 1.01 10C = 2O 1.23 22H – 4N 1.01 10C – 8C 1.52 23H – 4N 1.01 Methionine 3O = 8C 1.23 15H – 4N 1.01 8C – 2O 1.38 16H – 4N 1.01 2O – 20H 0.97 1S – 7C 1.90 Phenylalanine 23H – 1O 0.97 18H – 3N 1.00 1O – 9C 1.37 19H – 3N 1.01 9C = 2O 1.23 5C – 9C 1.51 Threonine 17H – 2O 0.97 14H – 4N 1.01 2O -8C 1.38 15H – 4N 1.01 8C = 3O 1.23 4N – 6C 1.45 16H – 1O 0.97 8C – 6C 1.51 Tryptophan 1O – 27H 0.97 24H – 4N 1.01 1O – 13C 1.37 25H – 4N 1.01 13C = 2O 1.23 3N – 20H 1.00 10C – 3N 1.39 9C – 3N 1.38 Valine 1O – 19H 0.97 17H – 3N 1.01 8C = 2O 1.23 18H – 3N 1.01 Table 3. Bond angles corresponding to functional groups of the optimized structures of EAA (Bond angle is in °). Bond Bond angle Bond Bond angle Histidine 20H – 1O – 9C 111.07 8C – 3N – 15H 123.62 1O – 9C – 2O 121.32 15H – 3N – 11C 128.47 2O – 9C – 7C 127.31 11C – 5N – 10C 105.46 Isoleucine 22H– 1O – 9C 111.87 21H – 3N – 20H 106.31 1O – 9C – 2O 122.65 3N – 5C – 9C 105.61 Leucine 22H– 1O – 9C 110.37 21H – 3N – 20H 113.01 1O – 9C – 2O 122.07 3N – 6C – 9C 104.87 Lysine 22H – 4N – 23H 111.32 24H – 1O – 10C 110.69 20H – 3N – 21H 110.66 1O – 10C – 2O 122.00 Methionine 20H – 2O – 8C 110.65 15H – 4N – 16H 110.37 2O – 8C – 3O 121.64 7C – 1S – 9C 99.56 Phenylalanine 23H – 10 – 9C 110.59 18H – 3N – 19H 113.56 1O – 9C – 2O 122.44 18H – 3N – 5C 115.26 Threonine 17H – 2O – 8C 110.92 14H – 4N – 15H 111.48 2O – 8C – 3O 122.40 16H – 1O – 5C 111.14 Tryptophan 27H – 1O – 13C 110.74 24H – 4N – 25H 111.22 1O – 13C – 2O 122.22 9C – 3N – 20H 125.58 9C – 3N – 10C 109.16 10C – 3N – 20H 125.24 Valine 19H – 1O – 8C 110.49 17H – 3N – 18H 110.74 1O – 8C – 2O 121.62 2O – 8C – 5C 125.49 Table 4. Values of global reactivity parameters for AA (all values are in eV and S is in (eV) -1 ). Molecular property Histidine Isoleucine Leucine Lysine Methionine Phenylalanine Threonine Tryptophan Valine HOMO -6.20 -6.47 -6.39 -5.94 -6.23 -6.34 -6.73 -5.61 -6.52 LUMO -1.22 -0.48 -0.43 -0.51 -0.62 -0.52 -0.70 -0.50 -0.59 Energy gap ( ΔE ) 4.97 5.99 5.95 5.42 5.60 5.82 6.02 5.11 5.93 Ionization potential ( IP ) 6.20 6.47 6.39 5.94 6.23 6.34 6.73 5.61 6.52 Electron affinity ( EA ) 1.22 0.48 0.43 0.51 0.62 0.52 0.70 0.50 0.59 Chemical potential ( CP ) -3.71 -3.48 -3.41 -3.22 -3.42 -3.43 -3.71 -3.05 -3.55 Electronegativity ( χ ) 3.71 3.48 3.41 3.22 3.42 3.43 3.71 3.05 3.55 Hardness ( η ) 2.48 2.99 2.97 2.71 2.80 2.91 3.01 2.55 2.96 Softness ( S ) 0.40 0.33 0.33 0.36 0.35 0.34 0.33 0.39 0.33 Table 5. Computed values of total dipole moment ( m total ), total isotropic polarizability ( a total ), anisotropy of polarizability (Δ a ), and first order hyperpolarizability ( b total ) of AA (dipole moment in Debye and m total , a total , Δ a and b total in esu). AA μ α total Δα β Histidine 2.19 12.60×10 -24 26.77×10 -24 1.99×10 -30 Isoleucine 0.64 11.60×10 -24 21.53×10 -24 1.23×10 -30 Leucine 0.73 11.63×10 -24 18.14×10 -24 1.4×10 -30 Lysine 0.34 12.95×10 -24 27.35×10 -24 2.06×10 -30 Methionine 0.37 12.78×10 -24 27.07×10 -24 1.37×10 -30 Phenylalanine 0.63 15.40×10 -24 32.23×10 -24 3.11×10 -30 Threonine 0.98 8.85×10 -24 15.56×10 -24 0.94×10 -30 Tryptophan 1.16 9.46×10 -24 14.58×10 -24 1.85×10 -30 Valine 0.51 10.04×10 -24 17.68×10 -24 1.75×10 -30 Supplementary Files GraphicalAbstract.pdf supportingdocument.docx ResearchHighlight.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Minor revisions 31 Jul, 2022 Reviewers agreed at journal 23 Jun, 2022 Reviewers invited by journal 23 Jun, 2022 Editor invited by journal 03 May, 2022 Editor assigned by journal 28 Apr, 2022 First submitted to journal 27 Apr, 2022 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1603417","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":115792649,"identity":"425d7aa9-ff8e-4612-ac03-210b66b9ea99","order_by":0,"name":"Shradha Lakhera","email":"","orcid":"","institution":"Uttarakhand Open University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shradha","middleName":"","lastName":"Lakhera","suffix":""},{"id":115792650,"identity":"5e18b5c1-fb78-4315-a74d-2efd5132e3ca","order_by":1,"name":"Meenakshi Rana Rana","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAoklEQVRIiWNgGAWjYNCCChjDgGgtZ0jWwthGtOFAoDv78LMHP+cdljM4wPzwA0PBHcJazM6lmRv2bjtsbHCAzViCweAZEVrOMJhJ8G47nLjhAIMZ0C+HidHC/k3y7xyQFvZvxGrhMZPmbQBp4SHaFp4yaZlj6caSh3mKJRKIdNg2yTc11nJ8x9s3fvjwhwgtCMAMxAmkaBgFo2AUjIJRgBsAANb6NapwfcthAAAAAElFTkSuQmCC","orcid":"","institution":"Uttarakhand Open University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Meenakshi","middleName":"Rana","lastName":"Rana","suffix":""},{"id":115792651,"identity":"b915e3ac-4233-47b3-af19-23b34208a613","order_by":2,"name":"Kamal Devlal","email":"","orcid":"","institution":"Uttarakhand Open University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Kamal","middleName":"","lastName":"Devlal","suffix":""}],"badges":[],"createdAt":"2022-04-28 06:11:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1603417/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1603417/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":23341934,"identity":"4bf73bab-1720-4498-93a5-0388da888383","added_by":"auto","created_at":"2022-07-01 19:20:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":103479,"visible":true,"origin":"","legend":"\u003cp\u003eMulliken charge plot for EAA showing positive charge impact of hydrogen atoms and negative impact of nitrogen and oxygen atoms.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-1603417/v1/61a614b978c7b0e87ff91c87.png"},{"id":23341935,"identity":"bbe03d59-4b98-41c5-b919-3e7ef31b3eaf","added_by":"auto","created_at":"2022-07-01 19:20:25","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":415645,"visible":true,"origin":"","legend":"\u003cp\u003eHOMO-LUMO map for AA.\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-1603417/v1/7fdfba8b4262a3efdfde7380.png"},{"id":23342065,"identity":"9860aea6-eb6f-47f3-91e2-a1ea61efb40d","added_by":"auto","created_at":"2022-07-01 19:25:25","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":525679,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular electrostatic potential surface of essential amino acids illustrating electrophilic region in blue and nucleophilic region in red colour.\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-1603417/v1/ec7ce0e8844ff15f438c8d0b.png"},{"id":23342068,"identity":"38e063a2-9357-40c6-8fd6-8fa039af7401","added_by":"auto","created_at":"2022-07-01 19:25:26","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":318756,"visible":true,"origin":"","legend":"\u003cp\u003eCounter plots showing high electrostatic field of the AA.\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-1603417/v1/a38ca35b3dc49e2a4bd8e943.png"},{"id":23341942,"identity":"5a5623bb-e932-4f08-b11c-cd18fde801c8","added_by":"auto","created_at":"2022-07-01 19:20:26","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":101272,"visible":true,"origin":"","legend":"\u003cp\u003eComputational Raman spectra of EAA showing different modes with maximum frequency (ν- symmetric stretching, α- asymmetric stretching, δ- torsional bending of the mode).\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-1603417/v1/a2a40bed839619b83c8079f8.png"},{"id":23342066,"identity":"cd981fef-e606-4d8d-918f-ed982823eea7","added_by":"auto","created_at":"2022-07-01 19:25:25","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":85126,"visible":true,"origin":"","legend":"\u003cp\u003eComputational UV-Vis spectra of AA showing oscillator strength for three highest peaks of absorption bands.\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-1603417/v1/45b10c59d47c23065a08525f.png"},{"id":23342297,"identity":"0dfeade5-edaa-42de-bf17-a405f7b7a585","added_by":"auto","created_at":"2022-07-01 19:30:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2668839,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1603417/v1/91b45c1d-e461-48ca-ad3f-b26ca8affe7d.pdf"},{"id":23341937,"identity":"46c03d6d-77ec-4e73-8d3b-c24dc377327a","added_by":"auto","created_at":"2022-07-01 19:20:25","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":405765,"visible":true,"origin":"","legend":"","description":"","filename":"GraphicalAbstract.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1603417/v1/e4bedb35a7b1521f681ec74e.pdf"},{"id":23341940,"identity":"20c44114-f6c3-40d4-aace-080eb6971640","added_by":"auto","created_at":"2022-07-01 19:20:26","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":35898,"visible":true,"origin":"","legend":"","description":"","filename":"supportingdocument.docx","url":"https://assets-eu.researchsquare.com/files/rs-1603417/v1/c34e6c975f2440d2f9028f6e.docx"},{"id":23342296,"identity":"b51b0a2a-cb16-471a-a016-4ff397cfd528","added_by":"auto","created_at":"2022-07-01 19:30:25","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":13923,"visible":true,"origin":"","legend":"","description":"","filename":"ResearchHighlight.docx","url":"https://assets-eu.researchsquare.com/files/rs-1603417/v1/11ff6ea589756fd3015d673b.docx"}],"financialInterests":"","formattedTitle":"Theoretical Study on Optoelectronic and Various Quantum Chemical Properties of Essential Amino Acids: A Comparative Study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eNonlinear optical (NLO) activity accounts for the polarization behavior of any material under the applied electric field. NLO properties deal with the displacement of the propagation characteristics of light (Ray 2010). When phase, frequency, amplitude, polarization, etc. of the incident light changes under the applied electric field, the material possesses NLO behavior (Bairy et al. 2021). NLO is very emergent topic of the current research world, exhibiting great diversity. It can be considered as a multidisciplinary field of research as it has engineering and mechanical bias, and is a subject of physical sciences, and sometimes its applications can also be seen in chemical and biological science (Midgley et al. 2009; Lakhera et al. 2022). In today\u0026rsquo;s technology-dependent society, the need for efficient materials is increasing with every passing day. NLO materials have an extensive area of applications from uses in future integrated photonic technologies, telecommunications, sum, and difference frequency generation to microfabrication, optical rectification, frequency mixing wave generation, electro-optic modulation, frequency conversion, fluorescence imaging, etc (Ullah et al. 2020; Buriahi et al. 2020; Cheng et al. 2019). NLO materials have been explored from various materials like molecular chromophores, polymers, semiconductors, etc., and also artificially designed such as lithium niobate (LiNbO\u003csub\u003e3\u003c/sub\u003e) and potassium dihydrogen phosphate (KH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e) (Moroz and Maslovskaya 2021). The carbon is known to form different fascinating compounds. The basic reason is sp\u003csup\u003e2\u003c/sup\u003e hybridization of carbon that give rise to the immense quantity of delocalized \u0026pi;-electrons available for the ICT that makes it highly reactive with different elements. Thus, the carbon compounds like fullerenes and carbon nanotubes have been an attractive field of research for the researchers. The studies with the introduction of highly efficient NLO carbon compounds have been reported from the literature survey. Fullerenes like C\u003csub\u003e58\u003c/sub\u003eBN and C\u003csub\u003e60\u003c/sub\u003eCl\u003csub\u003e30\u003c/sub\u003e were reported to have 105.01\u0026times;10\u003csup\u003e\u0026ndash;36\u003c/sup\u003e esu and 136.10\u0026times;10\u003csup\u003e\u0026ndash;36\u003c/sup\u003e esu values of first order hyperpolarizability \u003cstrong\u003e(\u003c/strong\u003eMuhammad et al. 2013). The carbon nanotubes have also been reported to have high third-order mean polarizability amplitudes like zigzag arranged nanotube 48.60\u0026times;10\u003csup\u003e\u0026ndash;36\u003c/sup\u003e esu and an armchair arranged nanotube 43.52\u0026times;10\u003csup\u003e\u0026ndash;36\u003c/sup\u003e esu (Muhammad et al. 2016, Muhammad et al. 2013) [10,11]. The amino acids (AA), fall in the category of carbon compounds. The organic compound-based NLO materials are gaining much attention and preferred by most scientists worldwide because of their properties like high durability, high structural flexibility, high electronic susceptibility, short response time, easy availability, and synthesis. The innumerable stretchability and extensive response time make organic NLO materials more efficient than inorganic NLO materials (Naseema et al. 2020). Generally, the presence of \u0026pi;-electron conjugated moiety with electron donor and electron acceptor groups in organic molecules leads to remarkable NLO performance (Lee et al. 2021). Keeping this in mind, we have tried to detect the NLO behavior of AA. AA are the fundamental compound in protein formation. They consists of amino (\u0026ndash;NH\u003csub\u003e2\u003c/sub\u003e) and carboxyl (\u0026ndash;COOH) functional groups. Nitrogen atoms present in the amino group constitute electron density to a greater extend. The higher the free electron pairs, the higher will be the availability of electrons for donation (Rana et al. 2019). The presence of the amino group also makes AA nucleophilic and carboxyl groups develop the electrophilic behavior. The oxygen atoms present in the carboxyl group are electronegative which draws electron cloud away from carbon making AA electrophilic (King et al. 2021). AA are generally divided into three main categories i.e., essentials (which cannot be synthesized by the body or must be consumed), non-essentials (which are self-synthesized in the body), and conditional AA (which are not necessarily required generally except the illness or deficiency) (Then et al. 2020; Lopez et al. 2021; Javier-Hila et al. 2021; Wang et al. 2021).\u003c/p\u003e\n\u003cp\u003eIn the current study, we have considered nine essential amino acids (EAA) (\u003cstrong\u003eHistidine\u003c/strong\u003e, \u003cstrong\u003eIsoleucine\u003c/strong\u003e, \u003cstrong\u003eLeucine\u003c/strong\u003e, \u003cstrong\u003eLysine\u003c/strong\u003e, \u003cstrong\u003eMethionine\u003c/strong\u003e, \u003cstrong\u003ePhenylalanine\u003c/strong\u003e, \u003cstrong\u003eThreonine\u003c/strong\u003e, \u003cstrong\u003eTryptophan\u003c/strong\u003e, and \u003cstrong\u003eValine\u003c/strong\u003e) (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). These AA are synthesized into our body by the breakdown of the consumed protein and thus leads to the growth and development of muscles and immunity (Soares et al. 2020). They are available in plenty and consumed by external sources like meat, eggs, and poultry and can lead to wider applications in pharmacological sciences (Christophersen and Haug 2011).\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cdiv align=\"left\" class=\"colspec\"\u003eOptimized structure for all nine EAA are presented in the Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The dipole moment and polarizability is the virtue by which the polarizing ability of any compound can be studied (Kuramochi et al. 2020). Mulliken charges and molecular electrostatic potential (MEP) surface have been done for all AA. Spectra like UV-Vis and Raman are also reported to check the spectral properties of the AA. The computed frontier molecular orbital (FMO) parameters are reported to justify the chemical reactivity of the compounds. The hyperpolarizability are the quantities by which the NLO behavior of any compound can be predicted (Lakhera et al. 2022). More the compound is polarizable, more it will show NLO behavior (Nazrin et al. 2019). The calculations for the polarizability parameters are also carried out to understand the NLO responses of the compound.\u003c/div\u003e\n\u003cp\u003e\u003c/p\u003e"},{"header":"2. Computational Procedure And Calculation","content":"\u003cp\u003eThe structures of the EAA are downloaded from online database \u0026ldquo;PubChem\u0026rdquo; (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubchem.ncbi.nlm.nih.gov/\u003c/span\u003e\u003c/span\u003e) (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). All the computational calculations were carried out using Gaussian 09 software and the interpretation of the output is done with the help of graphic user interface Gauss View 5.0 (Frisch et al. 2009; Becke 1993; Becke 1997). Becke-3-Lee-Yang-Parr (B3) exchange function combined with (LYP) correlation is used for optimization (Dennington et al. 2007). The geometries of all the considered EAA are optimized using density functional theory (DFT) with the standard B3LYP/6-311G basis set. The optimized structure helps in obtaining the FMO energies. The rest of the parameters like ionization potential (\u003cem\u003eIP\u003c/em\u003e), energy gap (\u003cem\u003e\u0026Delta;E\u003c/em\u003e), electron affinity (\u003cem\u003eEA\u003c/em\u003e), chemical potential (\u003cem\u003eCP\u003c/em\u003e), electronegativity (\u003cem\u003e\u0026chi;\u003c/em\u003e), softness (\u003cem\u003eS\u003c/em\u003e), and hardness (\u003cem\u003e\u0026eta;\u003c/em\u003e) are calculated with the help of these orbital energies. These parameters are calculated with the help of Koopman\u0026rsquo;s equations given below (Koopmans 1934):\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003cp\u003eIn Raman spectra analysis, Raman intensity is also calculated corresponding to high frequency modes. It was calculated by below given expression:\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/p\u003e\n\u003cp\u003ewhere \u003cem\u003eI\u003c/em\u003e refer to Raman intensity of the considered mode, \u003cem\u003ef\u003c/em\u003e is a constant with value 10\u003csup\u003e\u0026minus;\u0026thinsp;12\u003c/sup\u003e, \u0026nu;\u003csub\u003eo\u003c/sub\u003e has value 9398.5 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. \u0026nu;\u003csub\u003ei\u003c/sub\u003e and S\u003csub\u003ei\u003c/sub\u003e is the vibrational wavenumber and Raman activity of selected mode respectively. h is Planck constant with value 4.1357\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;15\u003c/sup\u003eeV K\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, c is speed of light with value 3\u0026times;10\u003csup\u003e8\u003c/sup\u003em/s, K is Boltzmann constant with value 8.6173\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e eV K\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, and T is temperature 293.5K. Polarizability parameters were calculated to understand the diffusion of the electron cloud in compound. The total dipole moment (\u003cem\u003e\u0026micro;\u003c/em\u003e\u003csub\u003e\u003cem\u003etotal\u003c/em\u003e\u003c/sub\u003e), total isotropic polarizability (\u003cem\u003e\u0026alpha;\u003c/em\u003e\u003csub\u003e\u003cem\u003etotal\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e, anisotropy of polarizability (\u0026Delta;\u003cem\u003e\u0026alpha;\u003c/em\u003e), and first order hyperpolarizability (\u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003etotal\u003c/em\u003e\u003c/sub\u003e) can be given as (Rana and Chowdhury 2020; Bhatt et al. 2020; Rana et al. 2020; Huang et al. 2006).\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003cp\u003ewhere \u003cem\u003e\u0026micro;\u003c/em\u003e\u003csub\u003e\u003cem\u003ex\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003e\u0026micro;\u003c/em\u003e\u003csub\u003e\u003cem\u003ey\u003c/em\u003e\u003c/sub\u003e, and \u003cem\u003e\u0026micro;\u003c/em\u003e\u003csub\u003e\u003cem\u003ez\u003c/em\u003e\u003c/sub\u003e are the tensor components dipole moment, \u003cem\u003e\u0026alpha;\u003c/em\u003e\u003csub\u003e\u003cem\u003exx\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003e\u0026alpha;\u003c/em\u003e\u003csub\u003e\u003cem\u003eyy\u003c/em\u003e\u003c/sub\u003e, and, \u003cem\u003e\u0026alpha;\u003c/em\u003e\u003csub\u003e\u003cem\u003ezz\u003c/em\u003e\u003c/sub\u003e are the tensor components of polarizability and \u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003exxx\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003eyyy\u003c/em\u003e\u003c/sub\u003e, and \u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003ezzz\u003c/em\u003e\u003c/sub\u003e are the tensor components of hyperpolarizability.\u003c/p\u003e"},{"header":"3. Results And Discussion","content":"\u003cdiv class=\"Section2\" id=\"Sec4\"\u003e\n \u003ch2\u003e3.1 Structure\u003c/h2\u003e\n \u003cp\u003eStructures for all the considered AA were optimized to the ground state energy level and were listed in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. Optimized geometry helps in finding the net polarity of the molecule by the means of dipole moment. More the dipole moment, more the compound will be polarizable (Lakhera et al. 2021; Visscher and Geerke 2019; Rana et al. 2017). In the present case, the selected EAA \u003cstrong\u003eHistidine\u003c/strong\u003e (5.58 Debye) have the maximum dipole moment as compared to \u003cstrong\u003eIsoleucine\u003c/strong\u003e (1.65 Debye), \u003cstrong\u003eLeucine\u003c/strong\u003e (1.85 Debye), \u003cstrong\u003eLysine\u003c/strong\u003e (0.88 Debye), \u003cstrong\u003eMethionine\u003c/strong\u003e (0.96 Debye), \u003cstrong\u003ePhenylalanine\u003c/strong\u003e (1.62 Debye), \u003cstrong\u003eThreonine\u003c/strong\u003e (2.50 Debye), \u003cstrong\u003eTryptophan\u003c/strong\u003e (2.95 Debye), and \u003cstrong\u003eValine\u003c/strong\u003e (1.31 Debye) (SD 1). The optimal bond lengths is inversely related to the bond strength and the stability of the bond. The lesser the bond lengths, more will be the stability of the bond. Although, the bond angle is inversely proportional to the bond length. Some selected bond lengths and bond angles for the optimized geometries corresponding to the charge transfer parts of the AA are mentioned in Tables 2 and \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. All the AA possess non-planar geometries. The \u003cstrong\u003eHistidine\u003c/strong\u003e molecule have dihedral angles C8 \u0026ndash; C6 \u0026ndash; C7 \u0026ndash; C9 and C8 \u0026ndash; C6 \u0026ndash; C7 \u0026ndash; N4. It consists of a carboxyl group and an amino group and its side chain have a basic group containing an imidazole ring. The low values of bond lengths also result in the high bond dissociation energy. The 1O \u0026ndash; 20H bond of the carboxyl group has the lowest bond length of 0.977 \u0026Aring; that showed the stability of the bond. The bond 7C \u0026ndash; 6C of alkyl group has the maximum bond length (1.54 \u0026Aring;). Thus, this bond might possess low bond dissociation energy. The angle associated to the pyrrolidine ring 16H \u0026ndash; 10C \u0026ndash; 8C has the minimum bond angle of 29.29\u0026deg; that indicated the strength of the pyrrolidine ring. \u003cstrong\u003eIsoleucine\u003c/strong\u003e have carboxyl group and amino group connected to 5C atom. The carbon chain showed the non-planarity of the molecule. The angle between the 1O \u0026ndash; 9C \u0026ndash; 2O bond of carboxyl group is 122.65\u0026deg; and angle 20H \u0026ndash; 3N \u0026ndash; 21H of the amino group is 106.31\u0026deg;. The bond angle between the carboxyl group is comparatively higher than that between the amino group which shows the high probability of the amino bonds to get dissociated.\u003c/p\u003e\n \u003cp\u003eThe structure of \u003cstrong\u003eLeucine\u003c/strong\u003e is quite similar to \u003cstrong\u003eIsoleucine\u003c/strong\u003e having amino and carboxyl group attached to the 6C atom of carbon chain. The 22H \u0026ndash; 1O bond of carboxyl group in \u003cstrong\u003eLeucine\u003c/strong\u003e have minimum bond length of 0.97 \u0026Aring; and bond 6C \u0026ndash; 3N that connects the amino group with the geometry have the maximum bond length of 1.47 \u0026Aring;.\u003c/p\u003e\n \u003cp\u003eUnlike \u003cstrong\u003eLeucine\u003c/strong\u003e, and \u003cstrong\u003eIsoleucine\u003c/strong\u003e (have single amino group), the \u003cstrong\u003eLysine\u003c/strong\u003e have two amino groups connected to 8C and 9C atom and carboxyl connected to 10C atom. The molecule consists of a straight carbon chain without any branched alkanes. However, the bond between the oxygen and hydrogen of the carboxyl group has the minimum bond length of 0.97 \u0026Aring;. The minimal bond lengths showed the strength of these bonds and reflects the charge accepting behavior of the carboxyl group. The bonds between the nitrogen and hydrogen atoms of amino groups are close for both the amino groups and quite higher than the bond lengths associated to carboxyl group. The bond angle 1O \u0026ndash; 10C \u0026ndash; 2O (122 \u0026deg;) associated to the carboxyl group also shows the accepting nature of the carboxyl group.\u003c/p\u003e\n \u003cp\u003eThe amino and carboxyl group of the \u003cstrong\u003eMethionine\u003c/strong\u003e molecule are connected to 6C atom of carbon chain. Apart of amino and carboxyl groups, one sulphur atom 1S is also connected to 7C atom of carbon chain. Being both \u0026pi;- and \u0026sigma;-donor, 1S atom might impart in being the charge donating moiety. The bond length of 1S \u0026ndash; 7C bond is 1.90 \u0026Aring; that was highest in all the bond length. The bond lengths corresponding to amino groups like 15H \u0026ndash; 4N (1.01\u0026Aring;) and 16H \u0026ndash; 4N (1.01 \u0026Aring;) are less than the bonds corresponding to the carboxyl group like 8C \u0026ndash; 2O (1.38 \u0026Aring;).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ePhenylalanine\u003c/strong\u003e has a benzene ring attached to 4C atom and one amino and carboxyl group were attached to 5C atom. Dihedral angle 6C \u0026ndash; 4C \u0026ndash; 5C \u0026ndash; 3N is seen to be responsible for the non-planer geometry of \u003cstrong\u003ePhenylalanine\u003c/strong\u003e. The bond 5C \u0026ndash; 9C bond of the carbon chain have the maximum bond length of 1.51 \u0026Aring;. The bonds 18H \u0026ndash; 3N and 19H \u0026ndash; 3N have high bond lengths of 1.00 \u0026Aring; and 1.01 \u0026Aring; respectively. These bond lengths are lower than the bond length 23H \u0026ndash; 1O corresponding to the carboxyl group 0.97 \u0026Aring;. The higher bond length of amino group reveals the tendency of these bonds of getting easily dissociated.\u003c/p\u003e\n \u003cp\u003eThe amino and carboxyl group in the \u003cstrong\u003eThreonine\u003c/strong\u003e are attached to 6C atom. Apart of these two groups, one hydroxyl group is also attached to 5C atom. The bond length 17H \u0026ndash; 2O (0.97 \u0026Aring;) and 16H \u0026ndash; 1O (0.97 \u0026Aring;) associated to carboxyl group were less in magnitude than the bonds 14H \u0026ndash; 4N (1.01 \u0026Aring;) and 15H \u0026ndash; 4N (1.01 \u0026Aring;) associated to amino group. The bond angle 2O \u0026ndash; 8C \u0026ndash; 3O with magnitude 122.406\u0026deg; is also greater than bond angles 14H \u0026ndash; 4N \u0026ndash; 15H (111.48\u0026deg;) displays the high chances of dissociation of amino bonds.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTryptophan\u003c/strong\u003e consists a benzene ring and a pyrrolidine ring mutually connected with 7C \u0026ndash; 9C bond. The bonds 24H \u0026ndash; 4N (1.01 \u0026Aring;) and 25H \u0026ndash; 4N (1.01 \u0026Aring;) of amino group have higher bond lengths than the bond 1O \u0026ndash; 27H (0.97 \u0026Aring;).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eValine\u003c/strong\u003e molecule comprises one amino and one carboxyl group attached to 5C atom. The 1O \u0026ndash; 19H bond of carboxyl group has bond length 0.97 \u0026Aring; that is less than bond length of 17H \u0026ndash; 3N (1.01 \u0026Aring;). The increasing order of electrostatic potential energies of the AA was \u003cstrong\u003eMethionine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eTryptophan\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003ePhenylalanine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eHistidine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eLysine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eLeucine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eIsoleucine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eThreonine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eValine\u003c/strong\u003e (SD 1). Negative magnitudes of electrostatic potential reflect the tendency of the molecule to attract the charge density. The optimized structures of all the AA indicated that the bond lengths and bond angles corresponding to the amino groups are smaller than the bond lengths and bond angles corresponding to carboxyl groups that shows the enhanced chances of dissociations of amino bonds. This in turns, shows the possibility of intramolecular interactions within the molecules that reveals the reactivity of the AA.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec5\"\u003e\n \u003ch2\u003e3.2 Charge analysis\u003c/h2\u003e\n \u003cp\u003eMulliken charge analysis helps in the understanding of the charge contribution corresponding to each and every atom of the systems (Senthilkumar et al. 2021). The charge plot of EAA shows the positive charge impact of H atoms and negative charge contribution of O atoms (Fig. 1). The charges corresponding to each atom of the \u003cstrong\u003eHistidine\u003c/strong\u003e molecule are plotted in Fig. 1(\u003cstrong\u003ea\u003c/strong\u003e). 9C and 20H atoms of carboxyl group of \u003cstrong\u003eHistidine\u003c/strong\u003e showed the maximum positive charge of 0.54 e and 0.39 e respectively. The 3N and 5N atoms associated to pyrrolidine ring shows negative charge of -0.73 e and \u0026minus;\u0026thinsp;0.37 e respectively. The 4N, 17H and 18H atoms of the amino group has charge \u0026minus;\u0026thinsp;0.67 e, 0.30 e and 0.29 e respectively. The Mulliken charge distribution of \u003cstrong\u003eHistidine\u003c/strong\u003e showed the huge variation in charge between pyrrolidine ring and carboxyl and amino groups. The Mulliken charge plot of \u003cstrong\u003eIsoleucine\u003c/strong\u003e is shows in Fig. 1(\u003cstrong\u003eb\u003c/strong\u003e). In \u003cstrong\u003eIsoleucine\u003c/strong\u003e, the charge variation is observed among the 1O (-0.55 e), 2O (-0.36 e), 9C (0.47 e) and 22H (0.38 e) atoms of carboxyl group and 3N (-0.64 e), 20H (0.29 e) and 21H (0.38 e) of amino group. Similar kind of variation of charge is observed in \u003cstrong\u003eLeucine\u003c/strong\u003e molecule in 1O (-0.55 e), 2O (-0.38 e), 9C (0.55 e) and 22H (0.38 e) atoms of carboxyl group and 3N (-0.69 e), 20H (0.29 e) and 21H (0.3 e) of amino group. Two amino groups in \u003cstrong\u003eLysine\u003c/strong\u003e with atoms 3N (-0.66 e), 20H (0.29 e), 21H (0.29 e), and 4N (-0.71 e), 22H (0.28 e), 23H (0.28 e) and a carboxyl group with atoms 1O (-0.56 e), 2O (-0.36 e), 10C (0.45 e) and 24H (0.38 e) showed the immense charge variation. The Mulliken charge distribution of the atoms in \u003cstrong\u003eMethionine\u003c/strong\u003e is illustrated in Fig. 1(\u003cstrong\u003ee\u003c/strong\u003e). Charge distribution predicts that 8C atom of carboxyl group shows the highest magnitude of positive charge equals to 0.48 e and 4N atom of amino group shows the negative charge of -0.72 e. Thus, these atoms reflects the major charge variation in the \u003cstrong\u003eMethionine\u003c/strong\u003e molecule. In \u003cstrong\u003ePhenylalanine\u003c/strong\u003e, 9C atom of amino group have the maximum positive charge and 3N atom of the carboxyl group have negative charge with maximum magnitude of -0.69 e. Mulliken charge distribution of the rest of the atoms of \u003cstrong\u003ePhenylalanine\u003c/strong\u003e is shown in Fig. 1(\u003cstrong\u003ef\u003c/strong\u003e). The \u003cstrong\u003eThreonine\u003c/strong\u003e molecule have an \u0026ndash;OH (hydroxyl) group connected to C5 atom of the carbon chain with atoms 1O and 16H with charge \u0026minus;\u0026thinsp;0.60 e and 0.36 e respectively (Fig. 1(\u003cstrong\u003eg\u003c/strong\u003e)). Apart of this, the 8C atom of carboxyl group has maximum positive charge of 0.53 e. The 4N atom of amino group of \u003cstrong\u003eThreonine\u003c/strong\u003e have charge \u0026minus;\u0026thinsp;0.68 e. Thus, the charge variations among the atoms of hydroxyl, carboxyl and amino group. The 3N atom connected to pyrrolidine ring in \u003cstrong\u003eTryptophan\u003c/strong\u003e molecule have the highest magnitude of negative charge \u0026minus;\u0026thinsp;0.81 e. The 3C atom of carboxyl group have the highest positive charge 0.53 e (Fig. 1(\u003cstrong\u003eh\u003c/strong\u003e)). These atoms impart in the major charge variation in \u003cstrong\u003eTryptophan\u003c/strong\u003e. In \u003cstrong\u003eValine\u003c/strong\u003e, the 8C atom of carboxyl group shows the highest charge of 0.50 e and 3N atom of amino group have charge \u0026minus;\u0026thinsp;0.68 e. The rest of the Mulliken charge distribution for \u003cstrong\u003eValine\u003c/strong\u003e is illustrated in Fig. 1(\u003cstrong\u003ei\u003c/strong\u003e). The variation in charge is observed between the functional groups (say amino and carboxyl groups). This variation can be considered due to the delocalization of the charges from the carboxyl part to the amino part of the molecule. This may lead to enhanced intramolecular interactions within the molecule. Therefore, the AA can be considered as chemically reactive.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec6\"\u003e\n \u003ch2\u003e3.3 Chemical reactivity\u003c/h2\u003e\n \u003cp\u003eFMO theory is a practical model which describes the chemical reactivity of the molecule (Swartling et al. 2018). The energy corresponding to HOMO and LUMO are termed as FMO energies (Saito et al. 2020). HOMO is the electron donating orbital and LUMO is the electron accepting orbital (Rana et al. 2016). The HOMO-LUMO map of different probe systems are shown in Fig. 2, that represent the distribution of highest occupied orbitals throughout the geometry and the distribution of lowest occupied orbitals in the functional groups. There is a significant energy associated to these orbitals. The computed values of FMO parameters of all the AA are mentioned in Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e. The energy difference between the LUMO and HOMO energies is called band gap (\u003cem\u003e\u0026Delta;E\u003c/em\u003e). The low value of \u003cem\u003e\u0026Delta;E\u003c/em\u003e validates the easy excitation tendency of the free electron cloud from the lower states to the higher energy states. The value of \u003cem\u003e\u0026Delta;E\u003c/em\u003e for \u003cstrong\u003eHistidine\u003c/strong\u003e is 4.97 eV. This value is lower than \u003cstrong\u003eIsoleucine\u003c/strong\u003e (5.99 eV), \u003cstrong\u003eLeucine\u003c/strong\u003e (5.95 eV), \u003cstrong\u003eLysine\u003c/strong\u003e (5.42 eV), \u003cstrong\u003eMethionine\u003c/strong\u003e (5.60 eV), \u003cstrong\u003ePhenylalanine\u003c/strong\u003e (5.82 eV), \u003cstrong\u003eThreonine\u003c/strong\u003e (6.02 eV), \u003cstrong\u003eTryptophan\u003c/strong\u003e (5.11 eV), and \u003cstrong\u003eValine\u003c/strong\u003e (5.93 eV). The values of \u003cem\u003e\u0026Delta;E\u003c/em\u003e for all the \u003cstrong\u003eAA\u003c/strong\u003e is found to be lower than the \u003cem\u003e\u0026Delta;E\u003c/em\u003e values of reference materials like Urea (7.43 eV) and KDP (6.83 eV). The low value of the energy gap shows the high possibility of the charge transfer within the molecule. The increasing order of \u003cem\u003e\u0026Delta;E\u003c/em\u003e values for AA is \u003cstrong\u003eHistidine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eTryptophan\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eLysine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eMethionine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003ePhenylalanine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eValine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eLeucine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eIsoleucine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eThreonine\u003c/strong\u003e. The \u003cem\u003eIP\u003c/em\u003e shows the potential that is needed to eject the electron from the nucleophilic atom. The values of \u003cem\u003eIP\u003c/em\u003e for the \u003cstrong\u003eHistidine\u003c/strong\u003e, \u003cstrong\u003eIsoleucine\u003c/strong\u003e, \u003cstrong\u003eLeucine\u003c/strong\u003e, \u003cstrong\u003eMethionine\u003c/strong\u003e, \u003cstrong\u003ePhenylalanine\u003c/strong\u003e, \u003cstrong\u003eThreonine\u003c/strong\u003e and \u003cstrong\u003eValine\u003c/strong\u003e are 6.20, 6.47, 6.39, 6.23, 6.34, 6.73, and 6.52 eV. These values are higher than \u003cem\u003eIP\u003c/em\u003e for \u003cstrong\u003eLysine\u003c/strong\u003e (5.94 eV) and \u003cstrong\u003eTryptophan\u003c/strong\u003e (5.61 eV). The increasing order of \u003cem\u003eIP\u003c/em\u003e was \u003cstrong\u003eTryptophan\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eLysine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eHistidine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eMethionine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003ePhenylalanine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eLeucine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eIsoleucine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eValine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eThreonine\u003c/strong\u003e. This showed that \u003cstrong\u003eTryptophan\u003c/strong\u003e has the better capability to donate the charge easily than the other AA. The \u003cem\u003eEA\u003c/em\u003e is a measure of the magnitude of energy that is liberated while attracting the free charge cloud. The high values of \u003cem\u003eEA\u003c/em\u003e shows that the molecule accepts the free charge cloud more easily. \u003cstrong\u003eHistidine\u003c/strong\u003e has the highest value of \u003cem\u003eEA\u003c/em\u003e equals to 1.22 eV. The values of \u003cem\u003eEA\u003c/em\u003e for other AA are \u003cstrong\u003eIsoleucine\u003c/strong\u003e (0.48 eV), \u003cstrong\u003eLeucine\u003c/strong\u003e (0.43 eV), \u003cstrong\u003eLysine\u003c/strong\u003e (0.51 eV), \u003cstrong\u003eMethionine\u003c/strong\u003e (0.62 eV), \u003cstrong\u003ePhenylalanine\u003c/strong\u003e (0.52 eV), \u003cstrong\u003eThreonine\u003c/strong\u003e (0.70 eV), \u003cstrong\u003eTryptophan\u003c/strong\u003e (0.50 eV), and \u003cstrong\u003eValine\u003c/strong\u003e (0.59 eV). The increasing order of \u003cem\u003eIP\u003c/em\u003e is \u003cstrong\u003eLeucine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eIsoleucine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eTryptophan\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eLysine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003ePhenylalanine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eValine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eMethionine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eThreonine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eHistidine\u003c/strong\u003e. So, \u003cstrong\u003eHistidine\u003c/strong\u003e molecule has the maximum value of \u003cem\u003eEA\u003c/em\u003e showing its enhanced capability of attracting the charge cloud. The values of \u003cem\u003eCP\u003c/em\u003e in raising order are \u003cstrong\u003eThreonine\u003c/strong\u003e (-3.16 eV)\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eHistidine\u003c/strong\u003e (-3.71 eV)\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eValine\u003c/strong\u003e (-3.55 eV)\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eIsoleucine\u003c/strong\u003e (-3.48 eV)\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003ePhenylalanine\u003c/strong\u003e (-3.43 eV)\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eMethionine\u003c/strong\u003e (-3.42 eV)\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eLeucine\u003c/strong\u003e (-3.41 eV)\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eLysine\u003c/strong\u003e (-3.22 eV)\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eTryptophan\u003c/strong\u003e (-3.05 eV). As the lower \u003cem\u003eCP\u003c/em\u003e are considered as the most stable one, the \u003cstrong\u003eThreonine\u003c/strong\u003e can be considered as the molecule undergoing the chemical process more easily with associating low amount of energy. Higher the value of \u003cem\u003e\u0026chi;\u003c/em\u003e, more strongly the electrophilic it will be able to pull the free charges towards itself. \u003cstrong\u003eThreonine\u003c/strong\u003e has the highest value of \u003cem\u003e\u0026chi;\u003c/em\u003e which shows that it can strongly attract the shared electrons. The \u003cem\u003e\u0026chi;\u003c/em\u003e is minimum for \u003cstrong\u003eTryptophan\u003c/strong\u003e (3.05 eV) and the value raised in order: \u003cstrong\u003eTryptophan\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eLysine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eLeucine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eMethionine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003ePhenylalanine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eIsoleucine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eValine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eHistidine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eThreonine\u003c/strong\u003e. The \u003cem\u003e\u0026eta;\u003c/em\u003e gives the extent of the chemical hardness of the molecule or it accounts the resistance of the molecule towards deformity after undergoing a chemical reaction. The molecules with higher values of \u003cem\u003e\u0026eta;\u003c/em\u003e can be considered more chemically stable. \u003cstrong\u003eThreonine\u003c/strong\u003e has the highest \u003cem\u003e\u0026eta;\u003c/em\u003e equals to 3.01 eV as compared to the other AA. In contrary, the \u003cem\u003eS\u003c/em\u003e is the opposite of \u003cem\u003e\u0026eta;\u003c/em\u003e and was used to show the receptivity of the molecules. The molecules with high values of softness are easily deformed or get dissociated while involving in chemical reaction. Thus, low values of \u003cem\u003eS\u003c/em\u003e are considered good for a chemically reactive molecule. The \u003cem\u003eS\u003c/em\u003e is in order: \u003cstrong\u003eIsoleucine\u003c/strong\u003e\u0026thinsp;=\u0026thinsp;\u003cstrong\u003eThreonine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eLeucine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eValine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003ePhenylalanine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eMethionine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eLysine\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eTryptophan\u003c/strong\u003e\u0026thinsp;\u0026lt;\u0026thinsp;\u003cstrong\u003eHistidine\u003c/strong\u003e. It is observed that \u003cstrong\u003eIsoleucine\u003c/strong\u003e and \u003cstrong\u003eLeucine\u003c/strong\u003e have the equally lowest values of \u003cem\u003eS\u003c/em\u003e that shows their chemical stability than other AA by the virtue of \u003cem\u003eS\u003c/em\u003e. However, the difference between the magnitudes of FMO parameters of other AA is not such observable. Thus, it can be said that the AA are chemically reactive in nature and they can give involvement on chemical reactions.\u003c/p\u003e\n \u003cp\u003eThe settlement of the HOMO-LUMO surfaces for AA is illustrated in Fig. 2. These surfaces basically show the location of the orbitals in molecular orbital wave function, respectively. The HOMO shows the donor orbitals (positive) and LUMO shows the acceptor orbitals (negative). The HOMO-LUMO surfaces of \u003cstrong\u003eHistidine\u003c/strong\u003e molecule (Fig. 2(\u003cstrong\u003ea\u003c/strong\u003e)) are seen to get drifted from pyrrolidine ring towards the amino and carboxyl group. Similar kind of surface dislocation is seen in \u003cstrong\u003eLysine\u003c/strong\u003e (Fig. 2(\u003cstrong\u003ed\u003c/strong\u003e)), \u003cstrong\u003eMethionine\u003c/strong\u003e (Fig. 2(\u003cstrong\u003ee\u003c/strong\u003e)) and \u003cstrong\u003eTryptophan\u003c/strong\u003e (Fig. 2(\u003cstrong\u003eh\u003c/strong\u003e)). In \u003cstrong\u003eLysine\u003c/strong\u003e, the positive and negative surfaces are settled over amino group in HOMO and get drifted over carboxyl group in LUMO. This shows the displacement of charge cloud from amino to carboxyl group in \u003cstrong\u003eLysine\u003c/strong\u003e. \u003cstrong\u003eMethionine\u003c/strong\u003e has positive and negative surfaces settled over S1 atom in HOMO while they are settled over functional groups in LUMO. In \u003cstrong\u003eTryptophan\u003c/strong\u003e, the positive and negative surfaces shift from benzene ring and pyrrolidine ring towards amino and carboxyl group. The shifting of the surfaces shows the direction of the shifting of the charge cloud. The shifting of orbitals in rest of the AA was not that much far as in the former described AA. The orbitals in \u003cstrong\u003eIsoleucine\u003c/strong\u003e (Fig. 2(\u003cstrong\u003eb\u003c/strong\u003e)), \u003cstrong\u003eLeucine\u003c/strong\u003e (Fig. 2(\u003cstrong\u003ec\u003c/strong\u003e)), \u003cstrong\u003ePhenylalanine\u003c/strong\u003e (Fig. 2(\u003cstrong\u003ef\u003c/strong\u003e)), \u003cstrong\u003eThreonine\u003c/strong\u003e (Fig. 2(\u003cstrong\u003eg\u003c/strong\u003e)) and \u003cstrong\u003eValine\u003c/strong\u003e (Fig. 2(\u003cstrong\u003ei\u003c/strong\u003e)) are uniformly distributed over the geometries and are locally shifted. The orbitals in \u003cstrong\u003eIsoleucine\u003c/strong\u003e and \u003cstrong\u003eLeucine\u003c/strong\u003e are seemed to shift among the functional groups. That means, red colored surface seems to be replaced by green and vice versa. This shows that the charge transfer occurred in between the atoms of the respective amino and carboxyl groups of \u003cstrong\u003eIsoleucine\u003c/strong\u003e and \u003cstrong\u003eLeucine\u003c/strong\u003e. In \u003cstrong\u003ePhenylalanine\u003c/strong\u003e, red color surface appeared over the amino and carboxyl group in HOMO surface that transited to red surface in LUMO surface. Similar kind of shifting of positive and negative orbitals is observed in \u003cstrong\u003eThreonine\u003c/strong\u003e and \u003cstrong\u003eValine\u003c/strong\u003e. Thus, it is observed that the presence of functional groups induces the shifting of donor and acceptor surfaces in AA. This shifting can be considered due to the dislocation of the charge cloud. Thus, the dislocation of the charge cloud give rise to immense ICT within the title molecule. Moreover, it can be said that the FMO parameters and HOMO-LUMO surfaces showed the enhanced possibility of ICT within the AA and makes them chemically reactive molecules.\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec7\"\u003e\n \u003ch2\u003e3.4 Molecular Electrostatic Potential (MEP) analysis\u003c/h2\u003e\n \u003cp\u003eThe displacement of the charge cloud is provided by the MEP surface color code. The red and yellow color of the MEP is due to the nucleophilic atoms (Sheikhi et al. 2019). Mainly the nitrogen molecules are responsible for the red color of the MEP (Khnifira et al. 2021). The O atoms being highly electronegative imparts the blue color of the MEP surface (Pathade and Jagdale 2020). The MEP surface of all the AA are illustrated in Fig.\u0026nbsp;3. This surface indicates the availability and location of the nucleophilic and electrophilic regions of the AA. This surface basically shows the displacement of the charge cloud from the positive part towards the negative part of the AA.\u003c/p\u003e\n \u003cp\u003eFor \u003cstrong\u003eHistidine\u003c/strong\u003e molecule, the variation of the charge is seen among the 1O, 2O, 9C, and 20H atoms of carboxyl group and 4N, 17H, and 18H atoms of amino group. Being highly resonating, the amino group imparts in donating the free electron cloud. The carboxyl group, on the other hand acts as electron withdrawing group due to the high electronegativity of the oxygen atoms. Thus, these groups give rise to the nucleophilic and electrophilic regions in the MEP. Moreover, the pyrrolidine ring attached to the carbon chain imparts the red color to the MEP surface due the presence of 3N and 5N atoms. Thus, the ICT is seen from the pyrrolidine ring and amino group towards the carboxyl group. The MEP\u0026rsquo;s counter plots were also used for the representation of the regions having electrostatic field of AA. The area with dense counter lines is the area with stronger electrostatic field (Idouhli et al. 2021). The field lines are found denser near the 2O atom of carboxyl group and 5N atom of pyrrolidine ring. The regions near 4N, 5N and 2O atoms have high electrostatic field (Fig. 4\u003cstrong\u003e(a)\u003c/strong\u003e). The bonds falling in the region of the aligned electrostatic field undergoes the simultaneous shortening and elongation of the bond. Therefore, this process leads to the weakening in the bonds, and ultimately breaking of the bond. Thus, the bonds surrounded with dense electrostatic field counter lines are weak enough to get dissociate. This leads to the formation and displacement of free electron cloud which is a key of ICT. The \u003cstrong\u003eHistidine\u003c/strong\u003e molecule, therefore, have the field lines largely accumulated near the carboxyl group, amino group, and pyrrolidine ring that validates the ICT between the functional groups as stated from Mulliken charge distribution and MEP surface.\u003c/p\u003e\n \u003cp\u003eIn the MEP surface of AA like \u003cstrong\u003eIsoleucine (Fig.\u0026nbsp;3(b)\u003c/strong\u003e), \u003cstrong\u003eLeucine (Fig.\u0026nbsp;3(c)\u003c/strong\u003e), \u003cstrong\u003eLysine (Fig.\u0026nbsp;3(d)\u003c/strong\u003e), \u003cstrong\u003eMethionine (Fig.\u0026nbsp;3(e)\u003c/strong\u003e), \u003cstrong\u003ePhenylalanine (Fig.\u0026nbsp;3(f)\u003c/strong\u003e), \u003cstrong\u003eThreonine (Fig.\u0026nbsp;3(g)\u003c/strong\u003e), and \u003cstrong\u003eValine (Fig.\u0026nbsp;3(i)\u003c/strong\u003e), the carboxyl group show immense high electronegativity giving rise to blue color of MEP surface and amino group imparts to the yellow color indicating the nucleophilic region. The ICT in these molecules was seen to be dislocated from the amino group towards carboxyl group. The counter plots of the \u003cstrong\u003eIsoleucine (Fig.\u0026nbsp;4(b)\u003c/strong\u003e), \u003cstrong\u003eLeucine (Fig.\u0026nbsp;4(c)\u003c/strong\u003e), \u003cstrong\u003eLysine (Fig.\u0026nbsp;4(d)\u003c/strong\u003e), \u003cstrong\u003eMethionine (Fig.\u0026nbsp;4(e)\u003c/strong\u003e), \u003cstrong\u003ePhenylalanine (Fig.\u0026nbsp;4(f)\u003c/strong\u003e), \u003cstrong\u003eThreonine (Fig.\u0026nbsp;4(g)\u003c/strong\u003e), and \u003cstrong\u003eValine (Fig.\u0026nbsp;4(i)\u003c/strong\u003e) are highly accumulated near the functional groups in the respective molecules. This validates the ICT predicted by MEP surface. The bonds of the functional groups have electrostatic field counter lines nearby that will lead to the weakening and dissociation of the bonds. This, in turns, can be considered the main reason of the evolution of the charge cloud from these functional groups and inducing ICT within the AA. The MEP surface of \u003cstrong\u003eTryptophan\u003c/strong\u003e AA is illustrated in Fig. 3\u003cstrong\u003e(h)\u003c/strong\u003e). Similar to the \u003cstrong\u003eHistidine\u003c/strong\u003e, the Tryptophan also has a pyrrolidine ring that acted as a nucleophilic part. The yellow color is uniformly spread over the benzene ring connected to pyrrolidine ring showing the negativity of the benzene ring. The 4N, 24H, and 25H of the phenol group, and 1O, 2O, 13C, and 27H atoms of carboxyl group, however, imparts the blue color indicating the donation of charge cloud from these regions. Thus, the ICT in \u003cstrong\u003eTryptophan\u003c/strong\u003e is seen from pyrrolidine ring, carboxyl and amino group towards the benzene ring. The counter plot of \u003cstrong\u003eTryptophan\u003c/strong\u003e is illustrated in Fig. 4(\u003cstrong\u003eh\u003c/strong\u003e). Alike the other AA, the counter plot lines in \u003cstrong\u003eTryptophan\u003c/strong\u003e are finely spread over the carboxyl and amino group showing the evolution of the charge cloud from these regions. Thus, the presence of nucleophilic and electrophilic regions validates the high degree of electrostatic interactions within the molecule. This show that there is a possibility of charge transfer from nucleophilic region to the electrophilic region. Thus, the variation of the electronic distributions within the molecule gives a possibility of the molecule being highly reactive molecule.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec8\"\u003e\n \u003ch2\u003e3.5 Vibrational analysis\u003c/h2\u003e\n \u003cp\u003eThe Raman modes are investigated for AA to study about its vibrational features. The Raman spectra helps in the studying the polarizing ability of the compound as the polarizability of any compound is proportional to the Raman intensity, which in turns leads to the NLO behavior of the compound (John et al. 2020; Prettre and Pullman 1987). The computed Raman spectra for all the AA is shown in Fig.\u0026nbsp;5. High frequency vibrations are observed for AA in range of 1000\u0026ndash;2000 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 2500\u0026ndash;4000 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The vibrational modes with high peaks with their corresponding Raman intensities are mentioned in SD 2.\u003c/p\u003e\n \u003cp\u003eFor \u003cstrong\u003eHistidine\u003c/strong\u003e molecule, the symmetric stretching (\u0026nu;\u003csub\u003eOH\u003c/sub\u003e) mode is observed at 3637.7 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The 17H \u0026ndash; 4N \u0026ndash; 18H atoms of amino group show \u0026nu;\u003csub\u003eNH\u003c/sub\u003e mode at 3516.02 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The \u0026nu;\u003csub\u003eCH\u003c/sub\u003e modes of the \u003cstrong\u003eHistidine\u003c/strong\u003e showed three major peaks at 3012.7 (\u0026nu;\u003csub\u003e6C\u0026minus;12H\u003c/sub\u003e and \u0026nu;\u003csub\u003e6C\u0026minus;13H\u003c/sub\u003e), 3098.73 (\u0026nu;\u003csub\u003e6C\u0026minus;12H\u003c/sub\u003e and \u0026nu;\u003csub\u003e6C\u0026minus;13H\u003c/sub\u003e) and 3271.1 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (\u0026nu;\u003csub\u003e10C\u0026minus;16H\u003c/sub\u003e and \u0026nu;\u003csub\u003e11C\u0026minus;19H\u003c/sub\u003e). The 8C\u0026thinsp;=\u0026thinsp;10C bond of the benzene ring shows \u0026nu;\u003csub\u003eCC\u003c/sub\u003e mode at frequency 1602.72 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The torsional bending of C \u0026ndash; H bond on the plane (\u0026delta;\u003csub\u003eCH\u003c/sub\u003e) mode shows the bending of the bond between 6C \u0026ndash; 12H and 7C \u0026ndash; 14H bonds in the plane. However, these modes corresponding to carbon chain have the maximum Raman intensity equal to 1631.56. Figure\u0026nbsp;5(\u003cstrong\u003ea\u003c/strong\u003e) illustrated the computed Raman spectra of \u003cstrong\u003eHistidine\u003c/strong\u003e.\u003c/p\u003e\n \u003cp\u003eFor \u003cstrong\u003eIsoleucine\u003c/strong\u003e, the \u0026nu;\u003csub\u003eOH\u003c/sub\u003e mode is observed at 3583.26 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The 17H \u0026ndash; 4N \u0026ndash; 18H atoms of amino group show \u0026nu;\u003csub\u003eNH\u003c/sub\u003e and asymmetric linear stretching (\u0026alpha;\u003csub\u003eNH\u003c/sub\u003e) mode at 3436.4 and 3515.96 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e respectively. The \u0026nu;\u003csub\u003eCH\u003c/sub\u003e mode of the \u003cstrong\u003eIsoleucine\u003c/strong\u003e has a major peak at 2992.93 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e leading the stretching of the hydrogens bonded with 6C, 7C and 8C atoms of carbon chain. The asymmetric stretching of C \u0026ndash; H bonds have two major peaks, one at 3023.95 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (\u0026alpha;\u003csub\u003e5C\u0026minus;11H\u003c/sub\u003e) and another at 3055.33 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (C\u0026ndash;H bonds attached to 7C and 8C). The \u0026delta;\u003csub\u003eCH\u003c/sub\u003e modes shows the bending of the bond between 1143.7 to 1528.86 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The stretching between 4C \u0026ndash; 6C atoms of carbon chain shows mode at 793 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Figure\u0026nbsp;5(\u003cstrong\u003eb\u003c/strong\u003e) illustrated the computed Raman spectra of \u003cstrong\u003eIsoleucine\u003c/strong\u003e.\u003c/p\u003e\n \u003cp\u003eThe \u003cstrong\u003eLeucine\u003c/strong\u003e molecule has \u0026alpha;\u003csub\u003eNH\u003c/sub\u003e mode of 3N \u0026ndash; 20H and 3N \u0026ndash; 21H at frequency 3641.67 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The stretching between 1O \u0026ndash; 22H of the carboxyl group is observed at 3623.64 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. \u0026nu;\u003csub\u003eNH\u003c/sub\u003e mode of amino group bonds 3N \u0026ndash; 20H and 3N \u0026ndash; 21H is observed at frequency 3641.67 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Three sharp peaks are observed for stretching of C \u0026ndash; H bonds at 2978.01, 3016.4 and 3081.21 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Twenty modes of bending of C \u0026ndash; H bonds was observed in range 975.95-1529.85 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. High Raman intensity of 1637.03 is observed for C \u0026ndash; C bond of the carbon chain for mode 782.41 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The computed Raman spectra of \u003cstrong\u003eLeucine\u003c/strong\u003e is illustrated in Fig. 5(\u003cstrong\u003ec\u003c/strong\u003e).\u003c/p\u003e\n \u003cp\u003eThe Raman spectra of \u003cstrong\u003eLysine\u003c/strong\u003e (Fig. 5(\u003cstrong\u003ed\u003c/strong\u003e)) has three high intensity peaks at 2906.07, 2984.77, and 3051.01 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e showing \u0026nu;\u003csub\u003eCH\u003c/sub\u003e modes of 8C \u0026ndash; 6C \u0026ndash; 5C \u0026ndash; 7C \u0026ndash; 9C chain. The 10C\u0026thinsp;=\u0026thinsp;2O bond of carboxyl chain showed \u0026nu;\u003csub\u003eCO\u003c/sub\u003e mode at 1711.01 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The \u0026delta;\u003csub\u003eCH\u003c/sub\u003e mode shows the bending modes from 1000.04 to 1528.41 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eThe 2O \u0026ndash; 20H bond of carboxyl group of \u003cstrong\u003eMethionine\u003c/strong\u003e vibrates linearly at 3623.06 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The 16H \u0026ndash; 4N \u0026ndash; 15H bond of amino group in \u003cstrong\u003eMethionine\u003c/strong\u003e shows \u0026nu;\u003csub\u003eNH\u003c/sub\u003e vibrational mode at 3499.93 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. There are two high intensity peaks observed for C \u0026ndash; H linear stretching. The vibration of 17H, 18H 19H attached to 9C bound to 1S atom have \u0026nu;\u003csub\u003eCH\u003c/sub\u003e mode at 3048.77 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The \u0026alpha;\u003csub\u003eCH\u003c/sub\u003e for 13H and 14H attached to 7C atom was observed at 3145.22 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The \u0026nu;\u003csub\u003eCO\u003c/sub\u003e mode between 8C\u0026thinsp;=\u0026thinsp;3O of carboxyl group is at frequency 1709.03 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The \u0026delta;\u003csub\u003eCH\u003c/sub\u003e modes are observed between 1214.06 to 1495.78 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The vibration of 1S bonded between 7C and 9C has high intensity of 4042.93 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e at frequency 655.69 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The \u0026nu;\u003csub\u003eCH\u003c/sub\u003e at 588.04 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e has the highest Raman intensity of 9103.99 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The other modes are illustrated in Fig.\u0026nbsp;5(e).\u003c/p\u003e\n \u003cp\u003eThe computed Raman spectra of \u003cstrong\u003ePhenylalanine\u003c/strong\u003e is shown in Fig. 5(\u003cstrong\u003ef\u003c/strong\u003e). The spectra highlighted the high frequency mode \u0026alpha;\u003csub\u003eNH\u003c/sub\u003e of amino group at 3654.76 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and \u0026nu;\u003csub\u003eNH\u003c/sub\u003e mode at 3529.77 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The 1O \u0026ndash; 23H atoms of carboxyl group showed \u0026nu;\u003csub\u003eOH\u003c/sub\u003e mode at 3654.03 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The \u0026nu;\u003csub\u003eCH\u003c/sub\u003e vibrations gave the sharp peaks in between frequency 3023.73 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 3194.86 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The \u0026delta;\u003csub\u003eCH\u003c/sub\u003e modes were observed between 1030.89 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e to 1520.44 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The \u0026nu;\u003csub\u003eCC\u003c/sub\u003e mode between 5C and 9C have vibration at 762.06 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and \u0026delta;\u003csub\u003eCC\u003c/sub\u003e mode of benzene ring occurs at 653.65 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eThe computed Raman spectra of \u003cstrong\u003eThreonine\u003c/strong\u003e was shown in Fig. 5(\u003cstrong\u003eg\u003c/strong\u003e). There are two high frequency peaks for \u0026nu;\u003csub\u003eOH\u003c/sub\u003e modes of O \u0026ndash; H bonds. The \u0026nu;\u003csub\u003eOH\u003c/sub\u003e mode for 1O \u0026ndash; 16H bond of hydroxyl group exists for frequency 3667.96 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The 4N, 14H and 15H atoms of amino group has frequency equals to 3518 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for \u0026nu;\u003csub\u003eNH\u003c/sub\u003e and 1726.8 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for \u0026delta;\u003csub\u003eNH\u003c/sub\u003e mode. The 2O \u0026ndash; 17H bond of carboxyl group have \u0026nu;\u003csub\u003eOH\u003c/sub\u003e mode at 3629.16 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The 7C atom of carbon chain has two different modes, first \u0026nu;\u003csub\u003eCH\u003c/sub\u003e 3038.87 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and second \u0026alpha;\u003csub\u003eCH\u003c/sub\u003e at 3119.98 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The \u0026delta;\u003csub\u003eCH\u003c/sub\u003e modes are observed between 746.85 to 1537.8 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. However, the \u0026delta;\u003csub\u003eCH\u003c/sub\u003e mode at frequency 746.85 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e has the highest intensity of 2012.59 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eThe \u003cstrong\u003eTryptophan\u003c/strong\u003e has one pyrrolidine ring attached to carbon chain and benzene ring. The 3N \u0026ndash; 20H bond of the pyrrolidine ring have \u0026nu;\u003csub\u003eNH\u003c/sub\u003e mode at 3684.64 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The \u0026nu;\u003csub\u003eNH\u003c/sub\u003e mode corresponding to amino bonds 4N \u0026ndash; 25H and 4N \u0026ndash; 25H has frequency 3496.44 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The 1O \u0026ndash; 27H bond of carboxyl group has mode \u0026nu;\u003csub\u003eCH\u003c/sub\u003e at 3621.77 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The \u0026alpha;\u003csub\u003eCH\u003c/sub\u003e mode is for the stretching of C \u0026ndash; H bonds of benzene rings (11C \u0026ndash; 21H, 12C \u0026ndash; 22H and 14C \u0026ndash; 23H). The 11C, 12C, 14C and 15C atoms of benzene ring vibrates simultaneously and leads the highest intensity mode for C \u0026ndash; H bonds with frequency 3195.34 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The \u0026delta;\u003csub\u003eCH\u003c/sub\u003e modes has multiple peaks between 775.11 to 1659.72 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. However, the \u0026delta;\u003csub\u003eCH\u003c/sub\u003e mode at 1587.6 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e is reported as the highest Raman intensity mode with magnitude 2423.57 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The computed spectra of Tryptophan is illustrated in Fig.\u0026nbsp;5(\u003cstrong\u003eh\u003c/strong\u003e).\u003c/p\u003e\n \u003cp\u003eThe computed Raman modes of \u003cstrong\u003eValine\u003c/strong\u003e are shown in Fig. 5(\u003cstrong\u003ei\u003c/strong\u003e). The 1O \u0026ndash; 19H bond of carboxyl group has stretching mode \u0026nu;\u003csub\u003eOH\u003c/sub\u003e at 3619.89 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The \u0026nu;\u003csub\u003eNH\u003c/sub\u003e mode between amino group 3N \u0026ndash; 17H and 3N \u0026ndash; 18H bond exists for frequency 3508.35 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. \u0026nu;\u003csub\u003eCH\u003c/sub\u003e modes has two sharp peaks for C \u0026ndash; H vibrations of carbon chain at frequency 3025.1 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 3085.17 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. For \u0026delta;\u003csub\u003eCH\u003c/sub\u003e, the highest frequency mode is at 1527.06 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The 1O \u0026ndash; 19H bond of carboxyl group has frequency 1285.89 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The stretching between 4C \u0026ndash; 5C is observed at 946.09 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The highest Raman intensity of 1193.34 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e is observed for \u0026nu;\u003csub\u003eCC\u003c/sub\u003e. the spectral analysis done for the AA showed the high Raman intensity for the modes associated to the functional groups present in the AA that showed the high chemical reactivity of these groups. All the above mentioned Raman modes reveals strong activity of the AA. Thus, the active Raman modes leads to the polarizability enhancement of the AA making them active and potent NLO materials.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec9\"\u003e\n \u003ch2\u003e3.6 UV-Vis spectral analysis\u003c/h2\u003e\n \u003cp\u003eTo understand the electronic transitions of the AA, the UV-Vis absorption peak is computed (Fig.\u0026nbsp;6). The electronic absorption spectra was calculated using time dependent-DFT method (TD-DFT) based on B3LYP/6-311G level optimization. The obtained spectra provide the information about the vertical excitation energies (\u003cem\u003eE\u003c/em\u003e), oscillator strengths (\u003cem\u003ef\u003c/em\u003e), and the wavelength (\u003cem\u003e\u0026lambda;\u003c/em\u003e) at which the transitions occur. A broad and strong absorption band of the \u003cstrong\u003eHistidine\u003c/strong\u003e molecule is recorded within the 200\u0026ndash;350 nm range (Fig. 6(\u003cstrong\u003ea\u003c/strong\u003e)). The \u0026pi;-\u0026pi;* and n-\u0026pi;* electronic transitions occurring at highest wavelengths are represented by transitions S\u003csub\u003e0\u003c/sub\u003e \u0026rarr;S\u003csub\u003e1\u003c/sub\u003e, S\u003csub\u003e2\u003c/sub\u003e, S\u003csub\u003e3\u003c/sub\u003e (SD 3). The transition S\u003csub\u003e0\u003c/sub\u003e \u0026rarr;S\u003csub\u003e1\u003c/sub\u003e was observed at 294.59 nm with oscillator strength 0.0028. The excitation energy for this transition is observed as 4.20eV. The excitation energy of the electrons in transition S\u003csub\u003e0\u003c/sub\u003e \u0026rarr;S\u003csub\u003e2\u003c/sub\u003e was observed as 4.65 eV at 266.54 nm wavelength and 0.0229 oscillator strength. This gave the peak of the spectra and is responsible for the formation of the spectra. The excitation energy of S\u003csub\u003e0\u003c/sub\u003e \u0026rarr;S\u003csub\u003e2\u003c/sub\u003e transition is nearly equal to the value of \u003cem\u003e\u0026Delta;E\u003c/em\u003e (say 4.97eV) we have obtained in HOMO-LUMO analysis. Generally, the band gap computed from FMO analysis represents the transition of the electrons from lower energy level to the higher energy level. So, the similarity of these values validates the results and shows the stability of the molecule. The electrons associated to the transition S\u003csub\u003e0\u003c/sub\u003e \u0026rarr;S\u003csub\u003e3\u003c/sub\u003e have excitation energy equals to 5.08 eV and oscillator strength 0.0024. This transition is observed at wavelength 243.98 nm. Similar to \u003cstrong\u003eHistidine\u003c/strong\u003e, \u003cstrong\u003eLysine\u003c/strong\u003e (Fig. 6(\u003cstrong\u003ed\u003c/strong\u003e)), \u003cstrong\u003eMethionine\u003c/strong\u003e (Fig. 6(\u003cstrong\u003ee\u003c/strong\u003e)), \u003cstrong\u003ePhenylalanine\u003c/strong\u003e (Fig. 6(\u003cstrong\u003ef\u003c/strong\u003e)) and \u003cstrong\u003eTryptophan\u003c/strong\u003e (Fig. 6(\u003cstrong\u003eh\u003c/strong\u003e)) also have single broad absorption band with peaks at 250, 251, 226 and 260 nm respectively. The transition S\u003csub\u003e0\u003c/sub\u003e \u0026rarr;S\u003csub\u003e1\u003c/sub\u003e that majorly imparts in the formation of the absorption band in these molecules have excitation energies 4.95, 4.93, 4.82 and 4.38 eV respectively. Similar to \u003cstrong\u003eHistidine\u003c/strong\u003e, the excitation of these AA coincides with the \u003cem\u003e\u0026Delta;E\u003c/em\u003e obtained from FMO analysis. The details of the other transition are mentioned in SD 3. \u003cstrong\u003eIsoleucine\u003c/strong\u003e has broad band ranging from 175\u0026ndash;300 nm having peak at 197.96 nm and 6.26 eV excitation energy and a local-maxima near 252.42 nm with 5.57 eV excitation energy (Fig. 6(\u003cstrong\u003eb\u003c/strong\u003e)). These two transitions majorly impart in the formation of the absorption spectra. Two absorption peaks are observed for the AA \u003cstrong\u003eLeucine\u003c/strong\u003e (Fig. 6(\u003cstrong\u003ec\u003c/strong\u003e)), \u003cstrong\u003eThreonine\u003c/strong\u003e (Fig. 6(\u003cstrong\u003eg\u003c/strong\u003e)) and \u003cstrong\u003eValine\u003c/strong\u003e (Fig. 6(\u003cstrong\u003ei\u003c/strong\u003e)). These bands show the electronic transitions from ground state to an excited state. The S\u003csub\u003e0\u003c/sub\u003e \u0026rarr;S\u003csub\u003e1\u003c/sub\u003e transition of \u003cstrong\u003eLeucine\u003c/strong\u003e exists at wavelength 255.46 nm with excitation energy 4.85 eV. This transition leads to the formation of the second absorption peak of the \u003cstrong\u003eLeucine\u003c/strong\u003e\u0026rsquo;s UV-Vis spectra. The first peak of \u003cstrong\u003eLeucine\u003c/strong\u003e is observed at wavelength 199.32 nm with excitation energy 6.22 eV. The excitation energy of the S\u003csub\u003e0\u003c/sub\u003e \u0026rarr;S\u003csub\u003e2\u003c/sub\u003e transition is close to the HOMO-LUMO band gap. For \u003cstrong\u003eThreonine\u003c/strong\u003e, two sharp peaks are observed at wavelength 207.87 nm and 250.8 nm with excitation energies 5.57 eV and 4.94 eV respectively (Fig.\u0026nbsp;6(\u003cstrong\u003eg\u003c/strong\u003e)). \u003cstrong\u003eValine\u003c/strong\u003e has two absorption peaks, first at 196.42 nm with excitation energy 6.31 eV undergoing S\u003csub\u003e0\u003c/sub\u003e \u0026rarr;S\u003csub\u003e3\u003c/sub\u003e transition and second at 253.14 nm with excitation energy 4.89 eV undergoing S\u003csub\u003e0\u003c/sub\u003e \u0026rarr;S\u003csub\u003e1\u003c/sub\u003e transition. Moreover, the HOMO-LUMO band gap too coincides with the excitation energy of S\u003csub\u003e0\u003c/sub\u003e \u0026rarr;S\u003csub\u003e2\u003c/sub\u003e transition. The excitation energies of electronic transitions for the AA are relatively close to the values of \u003cem\u003e\u0026Delta;E\u003c/em\u003e obtained from FMO analysis of the respective AA. These transitions show the enhanced intramolecular interactions between the lone pair (n) electrons and the \u0026pi; electron and also impart in molecule\u0026rsquo;s unsaturation (Fleck and Petrosyan 2010). Thus, it can be said that the AA are highly reactive in nature. Moreover, the S\u003csub\u003e0\u003c/sub\u003e \u0026rarr;S\u003csub\u003e1\u003c/sub\u003e transition for \u003cstrong\u003eHistidine\u003c/strong\u003e and \u003cstrong\u003eTryptophan\u003c/strong\u003e AA has highest wavelengths compared to the transitions of other AA. Thus, \u003cstrong\u003eHistidine\u003c/strong\u003e and \u003cstrong\u003eTryptophan\u003c/strong\u003e can be considered more chemically reactive.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec10\"\u003e\n \u003ch2\u003e3.8 NLO analysis\u003c/h2\u003e\n \u003cp\u003eTheoretical NLO calculation is most important part in identifying a potential NLO active molecule. The characterization of the behavior of the material in the presence of an applied electric field is accounted by phenomenon of polarization (Rana et al. 2018). Polarization simply tells us about the correlation between the interaction between the electron and nucleus. The multi-atom systems, such as molecules with large number of atoms have high number of electrons available as a charge cloud. The large the charge cloud is, the larger will be the possibility of charge dislocation. The highly raised values of the polarizability parameters are the result of the charge displacement. The literature survey revealed high optical nonlinearity among many organic and semi organic NLO materials. Thus, it is assumed that the materials having higher optical nonlinearity must be highly NLO active. The \u003cem\u003e\u0026micro;\u003c/em\u003e\u003csub\u003e\u003cem\u003etotal\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003e\u0026alpha;\u003c/em\u003e\u003csub\u003e\u003cspan class=\"BoldItalic\" name=\"Emphasis\" type=\"BoldItalic\"\u003etotal\u003c/span\u003e\u003c/sub\u003e, \u0026Delta;\u003cem\u003e\u0026alpha;\u003c/em\u003e and \u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003etotal\u003c/em\u003e\u003c/sub\u003e is computed for all the EAA and is listed in Table \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e. These parameters are basically expressed as the coefficients of standard Taylor series expansion of energy when the material interacts with weak and homogeneous externally applied electric field. Dipole moment is the first parameter in the list of polar properties as it accounts the polar nature of the molecule. The value of \u003cem\u003e\u0026micro;\u003c/em\u003e\u003csub\u003e\u003cem\u003etotal\u003c/em\u003e\u003c/sub\u003e for AA are \u003cstrong\u003eHistidine\u003c/strong\u003e (2.19 Debye), \u003cstrong\u003eIsoleucine\u003c/strong\u003e (0.49 Debye), \u003cstrong\u003eLeucine\u003c/strong\u003e (0.73 Debye), \u003cstrong\u003eLysine\u003c/strong\u003e (0.34 Debye), \u003cstrong\u003eMethionine\u003c/strong\u003e (0.37 Debye), \u003cstrong\u003ePhenylalanine\u003c/strong\u003e (0.63 Debye), \u003cstrong\u003eThreonine\u003c/strong\u003e (0.98 Debye), \u003cstrong\u003eTryptophan\u003c/strong\u003e (1.16 Debye), and \u003cstrong\u003eValine\u003c/strong\u003e (0.51 Debye). The electronic communication between acceptor and donor groups leads to high ICT. This results in the high values of polarizability and hyperpolarizability of the molecule. Thus, the transfer of the electron cloud from donor group towards acceptor group leads to the high value of the \u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003etotal\u003c/em\u003e\u003c/sub\u003e. The first order hyperpolarizability has been computed using finite field theory approach (Kirtman et al. 1998). The computed values of \u003cem\u003e\u0026alpha;\u003c/em\u003e\u003csub\u003e\u003cem\u003etotal\u003c/em\u003e\u003c/sub\u003e are \u003cstrong\u003eHistidine\u003c/strong\u003e (12.60\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;24\u003c/sup\u003eesu), \u003cstrong\u003eIsoleucine\u003c/strong\u003e (11.60\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;24\u003c/sup\u003eesu), \u003cstrong\u003eLeucine\u003c/strong\u003e (11.63\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;24\u003c/sup\u003eesu), \u003cstrong\u003eLysine\u003c/strong\u003e (12.95\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;24\u003c/sup\u003eesu), \u003cstrong\u003eMethionine\u003c/strong\u003e (12.78\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;24\u003c/sup\u003eesu), \u003cstrong\u003ePhenylalanine\u003c/strong\u003e (15.40\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;24\u003c/sup\u003eesu), \u003cstrong\u003eThreonine\u003c/strong\u003e (8.85\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;24\u003c/sup\u003eesu), \u003cstrong\u003eTryptophan\u003c/strong\u003e (9.46\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;24\u003c/sup\u003eesu), and \u003cstrong\u003eValine\u003c/strong\u003e (10.04\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;24\u003c/sup\u003eesu). All these values are higher than \u003cem\u003e\u0026alpha;\u003c/em\u003e\u003csub\u003e\u003cem\u003etotal\u003c/em\u003e\u003c/sub\u003e of Urea (5.66\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;24\u003c/sup\u003eesu). Among all the AA, \u003cstrong\u003ePhenylalanine\u003c/strong\u003e has the highest value of \u003cem\u003e\u0026alpha;\u003c/em\u003e\u003csub\u003e\u003cem\u003etotal\u003c/em\u003e\u003c/sub\u003e. It was thrice the \u003cem\u003e\u0026alpha;\u003c/em\u003e\u003csub\u003e\u003cem\u003etotal\u003c/em\u003e\u003c/sub\u003e of Urea. The computed values of \u0026Delta;\u003cem\u003e\u0026alpha;\u003c/em\u003e are \u003cstrong\u003eHistidine\u003c/strong\u003e (26.77\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;24\u003c/sup\u003eesu), \u003cstrong\u003eIsoleucine\u003c/strong\u003e (21.53\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;24\u003c/sup\u003eesu), \u003cstrong\u003eLeucine\u003c/strong\u003e (18.14\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;24\u003c/sup\u003eesu), \u003cstrong\u003eLysine\u003c/strong\u003e (27.35\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;24\u003c/sup\u003eesu), \u003cstrong\u003eMethionine\u003c/strong\u003e (27.07\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;24\u003c/sup\u003eesu), \u003cstrong\u003ePhenylalanine\u003c/strong\u003e (32.23\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;24\u003c/sup\u003eesu), \u003cstrong\u003eThreonine\u003c/strong\u003e (15.56\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;24\u003c/sup\u003eesu), \u003cstrong\u003eTryptophan\u003c/strong\u003e (14.58\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;24\u003c/sup\u003eesu), and \u003cstrong\u003eValine\u003c/strong\u003e (17.68\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;24\u003c/sup\u003eesu). These values are also higher than \u0026Delta;\u003cem\u003e\u0026alpha;\u003c/em\u003e of Urea (6.30\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;24\u003c/sup\u003eesu). Again, the \u0026Delta;\u003cem\u003e\u0026alpha;\u003c/em\u003e of \u003cstrong\u003ePhenylalanine\u003c/strong\u003e was found five times higher than \u0026Delta;\u003cem\u003e\u0026alpha;\u003c/em\u003e of Urea. The value of \u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003etotal\u003c/em\u003e\u003c/sub\u003e for Histidine (1.92\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;30\u003c/sup\u003e esu), \u003cstrong\u003eIsoleucine\u003c/strong\u003e (1.23\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;30\u003c/sup\u003e esu), \u003cstrong\u003eLeucine\u003c/strong\u003e (1.4\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;30\u003c/sup\u003eesu), \u003cstrong\u003eLysine\u003c/strong\u003e (2.06\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;30\u003c/sup\u003e esu), \u003cstrong\u003eMethionine\u003c/strong\u003e (1.37\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;30\u003c/sup\u003e esu), \u003cstrong\u003ePhenylalanine\u003c/strong\u003e (3.11\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;30\u003c/sup\u003e esu), \u003cstrong\u003eThreonine\u003c/strong\u003e (0.94\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;30\u003c/sup\u003e esu), \u003cstrong\u003eTryptophan\u003c/strong\u003e (1.85\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;30\u003c/sup\u003e esu), and \u003cstrong\u003eValine\u003c/strong\u003e (1.75\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;30\u003c/sup\u003e esu) is higher than \u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003etotal\u003c/em\u003e\u003c/sub\u003e of Urea (0.78\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;30\u003c/sup\u003e esu). But the value of \u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003etotal\u003c/em\u003e\u003c/sub\u003e of \u003cstrong\u003ePhenylalanine\u003c/strong\u003e is approximately four times higher than that of Urea. For the validation of the results, the \u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003etotal\u003c/em\u003e\u003c/sub\u003e of the \u003cstrong\u003ePhenylalanine\u003c/strong\u003e is also compared with some such NLO materials that have already been worked on and gave better results. The \u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003etotal\u003c/em\u003e\u003c/sub\u003e of Phenylalanine is also found two and a half times higher than \u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003etotal\u003c/em\u003e\u003c/sub\u003e of Phenyl urea (2.04\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;30\u003c/sup\u003e esu) (Marappan et al. 2019) and approximately one and a half times higher than \u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003etotal\u003c/em\u003e\u003c/sub\u003e of 3-nitroaniline (1.34\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;30\u003c/sup\u003e esu) (Krishnakumar and Nagalakshmi 2008). So, it simply suggests that \u003cstrong\u003ePhenylalanine\u003c/strong\u003e has the highest magnitude of the NLO parameters among all the AA. Thus, the comparative study shows that \u003cstrong\u003ePhenylalanine\u003c/strong\u003e have the high capability to act as a potent NLO responsive molecule.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eIn the presented work, the comparison of optoelectronic and quantum chemical features have been performed for all the EAA. This was done with the help of ground state structure optimization and TD-DFT calculations. The variation in the bond lengths and bond angles of the AA presented that the regions near the functional groups present in the respective AA is the region with high chances of being chemically reactive. The Mulliken charge analysis is done to see the actual charge transfer among the AA. The variation in the charge between the amino and carboxyl group highlighted these regions as the most reactive regions. The global reactivity parameters and MEP surfaces also verified the reactivity of the AA. The π-π* and n-π* electronic transitions are found to be occurring at highest wavelengths in computed absorption spectra. High Raman intensity modes are obtained for the AA from computed vibrational spectra. The Raman modes and electronic transitions obtained in the spectra validates the high polarizability of the AA molecules. For validating the high polarizability of the AA, the polarizability parameters (\u003cem\u003e\u0026micro;\u003c/em\u003e\u003csub\u003e\u003cem\u003etotal\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003eα\u003c/em\u003e\u003csub\u003e\u003cem\u003etotal\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003eΔα\u003c/em\u003e and \u003cem\u003eβ\u003c/em\u003e\u003csub\u003e\u003cem\u003etotal\u003c/em\u003e\u003c/sub\u003e) were computed. The \u003cem\u003eβ\u003c/em\u003e\u003csub\u003e\u003cem\u003etotal\u003c/em\u003e\u003c/sub\u003e of \u003cb\u003ePhenylalanine\u003c/b\u003e was found higher was found higher than all the other AA and reference materials Urea, Phenyl urea and 3-nitroaniline. The comparison was sufficiently high enough to validate the NLO candidature of \u003cb\u003ePhenylalanine\u003c/b\u003e. By this study, we can conclude that \u003cb\u003ePhenylalanine\u003c/b\u003e is the most active EAA among all the others and it can be used for experimental validations in future. There is a strong possibility to use it in NLO applications.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eShradha Lakhera:\u0026nbsp;\u003c/strong\u003eData curation, Writing-Original draft preparation, Visualization, Investigation, Software, Validation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeenakshi Rana:\u0026nbsp;\u003c/strong\u003eConceptualization, Methodology, Writing-Reviewing and Editing, Supervision\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKamal Devlal:\u0026nbsp;\u003c/strong\u003eConceptualization, Writing- Reviewing and Editing\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBairy, R., Jayarama, A., Kulkarni, S. 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Amino Acids. \u003cstrong\u003e53\u003c/strong\u003e, 239\u0026ndash;251(2021). https://doi.org/10.1007/s00726-021-02941-9\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eOptimized structures of EAA by standard B3LYP/6-311G basis set with PubChem IDs and chemical formulas.\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Bond lengths corresponding to functional groups of the optimized structures of EAA\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e(Bond length is in \u0026Aring;).\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e\u003cstrong\u003eBond\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e\u003cstrong\u003eBond length\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e\u003cstrong\u003eBond\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e\u003cstrong\u003eBond length\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistidine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1O \u0026ndash; 9C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e4N \u0026ndash; 17H\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e2O = 9C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e4N \u0026ndash; 18H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e20H \u0026ndash; 1O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e3N \u0026ndash; 11C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003eC8 = C10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e5N \u0026ndash; 11C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003e\u003cstrong\u003eIsoleucine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e22H \u0026ndash; 1O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e20H \u0026ndash; 3N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1O \u0026ndash; 9C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e21H \u0026ndash; 3N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e9C = 2O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e5C \u0026ndash; 3N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLeucine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e22H \u0026ndash; 1O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e20H \u0026ndash; 3N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1O \u0026ndash; 9C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e21H \u0026ndash; 3N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e9C = 2O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e6C \u0026ndash; 3N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLysine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1O \u0026ndash; 24H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e20H \u0026ndash; 3N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1O \u0026ndash; 10C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e21H \u0026ndash; 3N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e10C = 2O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e22H \u0026ndash; 4N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e10C \u0026ndash; 8C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e23H \u0026ndash; 4N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMethionine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e3O = 8C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e15H \u0026ndash; 4N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e8C \u0026ndash; 2O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e16H \u0026ndash; 4N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e2O \u0026ndash; 20H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e1S \u0026ndash; 7C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhenylalanine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e23H \u0026ndash; 1O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e18H \u0026ndash; 3N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1O \u0026ndash; 9C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e19H \u0026ndash; 3N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e9C = 2O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e5C \u0026ndash; 9C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003e\u003cstrong\u003eThreonine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e17H \u0026ndash; 2O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e14H \u0026ndash; 4N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e2O -8C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e15H \u0026ndash; 4N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e8C = 3O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e4N \u0026ndash; 6C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e16H \u0026ndash; 1O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e8C \u0026ndash; 6C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTryptophan\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1O \u0026ndash; 27H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e24H \u0026ndash; 4N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1O \u0026ndash; 13C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e25H \u0026ndash; 4N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e13C = 2O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e3N \u0026ndash; 20H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e10C \u0026ndash; 3N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e9C \u0026ndash; 3N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003e\u003cstrong\u003eValine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1O \u0026ndash; 19H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e\u0026nbsp; 17H \u0026ndash; 3N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026nbsp;1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e8C = 2O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.458874458874458%\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.19047619047619%\"\u003e\n \u003cp\u003e18H \u0026ndash; 3N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.89177489177489%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e Bond angles corresponding to functional groups of the optimized structures of EAA (Bond angle is in \u0026deg;).\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e\u003cstrong\u003eBond\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e\u003cstrong\u003eBond angle\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e\u003cstrong\u003eBond\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e\u003cstrong\u003eBond angle\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistidine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e20H \u0026ndash; 1O \u0026ndash; 9C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e111.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e8C \u0026ndash; 3N \u0026ndash; 15H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e123.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e1O \u0026ndash; 9C \u0026ndash; 2O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e121.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e15H \u0026ndash; 3N \u0026ndash; 11C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e128.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e2O \u0026ndash; 9C \u0026ndash; 7C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e127.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e11C \u0026ndash; 5N \u0026ndash; 10C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e105.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003e\u003cstrong\u003eIsoleucine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e22H\u0026ndash; 1O \u0026ndash; 9C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e111.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e21H \u0026ndash; 3N \u0026ndash; 20H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e106.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e1O \u0026ndash; 9C \u0026ndash; 2O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e122.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e3N \u0026ndash; 5C \u0026ndash; 9C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e105.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLeucine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e22H\u0026ndash; 1O \u0026ndash; 9C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e110.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e21H \u0026ndash; 3N \u0026ndash; 20H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e113.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e1O \u0026ndash; 9C \u0026ndash; 2O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e122.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e3N \u0026ndash; 6C \u0026ndash; 9C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e104.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLysine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e22H \u0026ndash; 4N \u0026ndash; 23H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e111.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e24H \u0026ndash; 1O \u0026ndash; 10C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e110.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e20H \u0026ndash; 3N \u0026ndash; 21H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e110.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e1O \u0026ndash; 10C \u0026ndash; 2O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e122.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMethionine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e20H \u0026ndash; 2O \u0026ndash; 8C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e110.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e15H \u0026ndash; 4N \u0026ndash; 16H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e110.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e2O \u0026ndash; 8C \u0026ndash; 3O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e121.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e7C \u0026ndash; 1S \u0026ndash; 9C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e99.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhenylalanine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e23H \u0026ndash; 10 \u0026ndash; 9C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e110.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e18H \u0026ndash; 3N \u0026ndash; 19H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e113.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e1O \u0026ndash; 9C \u0026ndash; 2O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e122.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e18H \u0026ndash; 3N \u0026ndash; 5C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e115.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003e\u003cstrong\u003eThreonine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e17H \u0026ndash; 2O \u0026ndash; 8C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e110.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e14H \u0026ndash; 4N \u0026ndash; 15H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e111.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e2O \u0026ndash; 8C \u0026ndash; 3O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e122.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e16H \u0026ndash; 1O \u0026ndash; 5C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e111.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTryptophan\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e27H \u0026ndash; 1O \u0026ndash; 13C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e110.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e24H \u0026ndash; 4N \u0026ndash; 25H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e111.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e1O \u0026ndash; 13C \u0026ndash; 2O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e122.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e9C \u0026ndash; 3N \u0026ndash; 20H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e125.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e9C \u0026ndash; 3N \u0026ndash; 10C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e109.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e10C \u0026ndash; 3N \u0026ndash; 20H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e125.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003e\u003cstrong\u003eValine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e19H \u0026ndash; 1O \u0026ndash; 8C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e110.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e17H \u0026ndash; 3N \u0026ndash; 18H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e110.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e1O \u0026ndash; 8C \u0026ndash; 2O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e121.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e2O \u0026ndash; 8C \u0026ndash; 5C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e125.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u0026nbsp;\u003c/strong\u003eValues of global reactivity parameters for AA\u0026nbsp;(all values are in eV and S is in (eV)\u003csup\u003e-1\u003c/sup\u003e).\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"15.2073732718894%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMolecular property\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.870967741935484%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistidine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.56221198156682%\"\u003e\n \u003cp\u003e\u003cstrong\u003eIsoleucine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.949308755760368%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLeucine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.912442396313364%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLysine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.714285714285714%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMethionine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.903225806451612%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhenylalanine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.90783410138249%\"\u003e\n \u003cp\u003e\u003cstrong\u003eThreonine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.175115207373272%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTryptophan\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.797235023041475%\"\u003e\n \u003cp\u003e\u003cstrong\u003eValine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"15.2073732718894%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHOMO\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.870967741935484%\"\u003e\n \u003cp\u003e-6.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.56221198156682%\"\u003e\n \u003cp\u003e-6.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.949308755760368%\"\u003e\n \u003cp\u003e-6.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.912442396313364%\"\u003e\n \u003cp\u003e-5.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.714285714285714%\"\u003e\n \u003cp\u003e-6.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.903225806451612%\"\u003e\n \u003cp\u003e-6.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.90783410138249%\"\u003e\n \u003cp\u003e-6.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.175115207373272%\"\u003e\n \u003cp\u003e-5.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.797235023041475%\"\u003e\n \u003cp\u003e-6.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"15.2073732718894%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLUMO\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.870967741935484%\"\u003e\n \u003cp\u003e-1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.56221198156682%\"\u003e\n \u003cp\u003e-0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.949308755760368%\"\u003e\n \u003cp\u003e-0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.912442396313364%\"\u003e\n \u003cp\u003e-0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.714285714285714%\"\u003e\n \u003cp\u003e-0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.903225806451612%\"\u003e\n \u003cp\u003e-0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.90783410138249%\"\u003e\n \u003cp\u003e-0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.175115207373272%\"\u003e\n \u003cp\u003e-0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.797235023041475%\"\u003e\n \u003cp\u003e-0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"15.2073732718894%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEnergy gap\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(\u003cem\u003e\u0026Delta;E\u003c/em\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.870967741935484%\"\u003e\n \u003cp\u003e4.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.56221198156682%\"\u003e\n \u003cp\u003e5.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.949308755760368%\"\u003e\n \u003cp\u003e5.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.912442396313364%\"\u003e\n \u003cp\u003e5.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.714285714285714%\"\u003e\n \u003cp\u003e5.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.903225806451612%\"\u003e\n \u003cp\u003e5.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.90783410138249%\"\u003e\n \u003cp\u003e6.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.175115207373272%\"\u003e\n \u003cp\u003e5.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.797235023041475%\"\u003e\n \u003cp\u003e5.93\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"15.2073732718894%\"\u003e\n \u003cp\u003e\u003cstrong\u003eIonization potential (\u003cem\u003eIP\u003c/em\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.870967741935484%\"\u003e\n \u003cp\u003e6.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.56221198156682%\"\u003e\n \u003cp\u003e6.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.949308755760368%\"\u003e\n \u003cp\u003e6.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.912442396313364%\"\u003e\n \u003cp\u003e5.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.714285714285714%\"\u003e\n \u003cp\u003e6.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.903225806451612%\"\u003e\n \u003cp\u003e6.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.90783410138249%\"\u003e\n \u003cp\u003e6.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.175115207373272%\"\u003e\n \u003cp\u003e5.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.797235023041475%\"\u003e\n \u003cp\u003e6.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"15.2073732718894%\"\u003e\n \u003cp\u003e\u003cstrong\u003eElectron affinity (\u003cem\u003eEA\u003c/em\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.870967741935484%\"\u003e\n \u003cp\u003e1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.56221198156682%\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.949308755760368%\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.912442396313364%\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.714285714285714%\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.903225806451612%\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.90783410138249%\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.175115207373272%\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.797235023041475%\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"15.2073732718894%\"\u003e\n \u003cp\u003e\u003cstrong\u003eChemical potential (\u003cem\u003eCP\u003c/em\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.870967741935484%\"\u003e\n \u003cp\u003e-3.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.56221198156682%\"\u003e\n \u003cp\u003e-3.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.949308755760368%\"\u003e\n \u003cp\u003e-3.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.912442396313364%\"\u003e\n \u003cp\u003e-3.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.714285714285714%\"\u003e\n \u003cp\u003e-3.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.903225806451612%\"\u003e\n \u003cp\u003e-3.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.90783410138249%\"\u003e\n \u003cp\u003e-3.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.175115207373272%\"\u003e\n \u003cp\u003e-3.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.797235023041475%\"\u003e\n \u003cp\u003e-3.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"15.2073732718894%\"\u003e\n \u003cp\u003e\u003cstrong\u003eElectronegativity\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(\u003cem\u003e\u0026chi;\u003c/em\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.870967741935484%\"\u003e\n \u003cp\u003e3.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.56221198156682%\"\u003e\n \u003cp\u003e3.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.949308755760368%\"\u003e\n \u003cp\u003e3.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.912442396313364%\"\u003e\n \u003cp\u003e3.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.714285714285714%\"\u003e\n \u003cp\u003e3.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.903225806451612%\"\u003e\n \u003cp\u003e3.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.90783410138249%\"\u003e\n \u003cp\u003e3.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.175115207373272%\"\u003e\n \u003cp\u003e3.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.797235023041475%\"\u003e\n \u003cp\u003e3.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"15.2073732718894%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHardness (\u003cem\u003e\u0026eta;\u003c/em\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.870967741935484%\"\u003e\n \u003cp\u003e2.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.56221198156682%\"\u003e\n \u003cp\u003e2.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.949308755760368%\"\u003e\n \u003cp\u003e2.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.912442396313364%\"\u003e\n \u003cp\u003e2.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.714285714285714%\"\u003e\n \u003cp\u003e2.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.903225806451612%\"\u003e\n \u003cp\u003e2.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.90783410138249%\"\u003e\n \u003cp\u003e3.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.175115207373272%\"\u003e\n \u003cp\u003e2.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.797235023041475%\"\u003e\n \u003cp\u003e2.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"15.2073732718894%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSoftness (\u003cem\u003eS\u003c/em\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.870967741935484%\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.56221198156682%\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.949308755760368%\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.912442396313364%\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.714285714285714%\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.903225806451612%\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.90783410138249%\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.175115207373272%\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.797235023041475%\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5.\u003c/strong\u003e Computed values of total dipole moment (\u003cem\u003em\u003c/em\u003e\u003cem\u003e\u003csub\u003etotal\u003c/sub\u003e\u003c/em\u003e), total isotropic polarizability (\u003cem\u003ea\u003c/em\u003e\u003cem\u003e\u003csub\u003etotal\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e),\u003c/em\u003e anisotropy of polarizability (\u0026Delta;\u003cem\u003ea\u003c/em\u003e), and first order hyperpolarizability (\u003cem\u003eb\u003c/em\u003e\u003cem\u003e\u003csub\u003etotal\u003c/sub\u003e\u003c/em\u003e)\u0026nbsp;of AA\u0026nbsp;(dipole moment in Debye and\u0026nbsp;\u003cem\u003em\u003c/em\u003e\u003cem\u003e\u003csub\u003etotal\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e,\u0026nbsp;\u003c/em\u003e\u003cem\u003ea\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e\u003csub\u003etotal\u003c/sub\u003e\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e,\u003csub\u003e\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e\u003c/strong\u003e\u0026Delta;\u003cem\u003ea\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003eand\u0026nbsp;\u003cem\u003eb\u003c/em\u003e\u003cem\u003e\u003csub\u003etotal\u003c/sub\u003e\u003c/em\u003e in esu).\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"32.03883495145631%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.268608414239482%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026mu;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.79935275080906%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026alpha;\u003csub\u003etotal\u003c/sub\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.79935275080906%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026Delta;\u0026alpha;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.093851132686083%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"32.03883495145631%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistidine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.268608414239482%\"\u003e\n \u003cp\u003e2.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.79935275080906%\"\u003e\n \u003cp\u003e12.60\u0026times;10\u003csup\u003e-24\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.79935275080906%\"\u003e\n \u003cp\u003e26.77\u0026times;10\u003csup\u003e-24\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.093851132686083%\"\u003e\n \u003cp\u003e1.99\u0026times;10\u003csup\u003e-30\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"32.03883495145631%\"\u003e\n \u003cp\u003e\u003cstrong\u003eIsoleucine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.268608414239482%\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.79935275080906%\"\u003e\n \u003cp\u003e11.60\u0026times;10\u003csup\u003e-24\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.79935275080906%\"\u003e\n \u003cp\u003e21.53\u0026times;10\u003csup\u003e-24\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.093851132686083%\"\u003e\n \u003cp\u003e1.23\u0026times;10\u003csup\u003e-30\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"32.03883495145631%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLeucine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.268608414239482%\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.79935275080906%\"\u003e\n \u003cp\u003e11.63\u0026times;10\u003csup\u003e-24\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.79935275080906%\"\u003e\n \u003cp\u003e18.14\u0026times;10\u003csup\u003e-24\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.093851132686083%\"\u003e\n \u003cp\u003e1.4\u0026times;10\u003csup\u003e-30\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"32.03883495145631%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLysine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.268608414239482%\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.79935275080906%\"\u003e\n \u003cp\u003e12.95\u0026times;10\u003csup\u003e-24\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.79935275080906%\"\u003e\n \u003cp\u003e27.35\u0026times;10\u003csup\u003e-24\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.093851132686083%\"\u003e\n \u003cp\u003e2.06\u0026times;10\u003csup\u003e-30\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"32.03883495145631%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMethionine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.268608414239482%\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.79935275080906%\"\u003e\n \u003cp\u003e12.78\u0026times;10\u003csup\u003e-24\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.79935275080906%\"\u003e\n \u003cp\u003e27.07\u0026times;10\u003csup\u003e-24\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.093851132686083%\"\u003e\n \u003cp\u003e1.37\u0026times;10\u003csup\u003e-30\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"32.03883495145631%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhenylalanine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.268608414239482%\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.79935275080906%\"\u003e\n \u003cp\u003e15.40\u0026times;10\u003csup\u003e-24\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.79935275080906%\"\u003e\n \u003cp\u003e32.23\u0026times;10\u003csup\u003e-24\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.093851132686083%\"\u003e\n \u003cp\u003e3.11\u0026times;10\u003csup\u003e-30\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"32.03883495145631%\"\u003e\n \u003cp\u003e\u003cstrong\u003eThreonine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.268608414239482%\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.79935275080906%\"\u003e\n \u003cp\u003e8.85\u0026times;10\u003csup\u003e-24\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.79935275080906%\"\u003e\n \u003cp\u003e15.56\u0026times;10\u003csup\u003e-24\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.093851132686083%\"\u003e\n \u003cp\u003e0.94\u0026times;10\u003csup\u003e-30\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"32.03883495145631%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTryptophan\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.268608414239482%\"\u003e\n \u003cp\u003e1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.79935275080906%\"\u003e\n \u003cp\u003e9.46\u0026times;10\u003csup\u003e-24\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.79935275080906%\"\u003e\n \u003cp\u003e14.58\u0026times;10\u003csup\u003e-24\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.093851132686083%\"\u003e\n \u003cp\u003e1.85\u0026times;10\u003csup\u003e-30\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"32.03883495145631%\"\u003e\n \u003cp\u003e\u003cstrong\u003eValine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.268608414239482%\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.79935275080906%\"\u003e\n \u003cp\u003e10.04\u0026times;10\u003csup\u003e-24\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.79935275080906%\"\u003e\n \u003cp\u003e17.68\u0026times;10\u003csup\u003e-24\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.093851132686083%\"\u003e\n \u003cp\u003e1.75\u0026times;10\u003csup\u003e-30\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"optical-and-quantum-electronics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"oqel","sideBox":"Learn more about [Optical and Quantum Electronics](https://www.springer.com/journal/11082)","snPcode":"11082","submissionUrl":"https://submission.nature.com/new-submission/11082/3","title":"Optical and Quantum Electronics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Essential amino acids, Optimization, Mulliken charges, Chemical reactivity, Spectral analysis","lastPublishedDoi":"10.21203/rs.3.rs-1603417/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1603417/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn the present work, a theoretical study has been performed targeting essential amino acids (EAA) \u003cb\u003eHistidine\u003c/b\u003e, \u003cb\u003eIsoleucine\u003c/b\u003e, \u003cb\u003eLeucine\u003c/b\u003e, \u003cb\u003eLysine\u003c/b\u003e, \u003cb\u003eMethionine\u003c/b\u003e, \u003cb\u003ePhenylalanine\u003c/b\u003e, \u003cb\u003eThreonine\u003c/b\u003e, \u003cb\u003eTryptophan\u003c/b\u003e, \u003cb\u003eValine\u003c/b\u003e, and predicted their different physical and chemical properties by using computational techniques. Amino acids (AA), a fundamental structural unit of protein are amino and carboxyl-rich compounds having electrophilic and nucleophilic regions in it. The reactivity of AA were determined by computing molecular electrostatic potential (MEP) surfaces, counter plots, dipole moment, band gap, global reactivity parameters, and polarizability parameters. Spectral analysis (UV-Vis, Raman) helps in studying their electronic and vibrational properties. The polarizability and first order hyperpolarizability parameters were also computed to detect the nonlinear optical (NLO) behavior of AA. The comparison done with reference NLO materials Urea, Phenyl urea, and 3-nitroaniline showed that \u003cb\u003ePhenylalanine\u003c/b\u003e have higher hyperpolarizability and can better to be used as a potent NLO material.\u003c/p\u003e","manuscriptTitle":"Theoretical Study on Optoelectronic and Various Quantum Chemical Properties of Essential Amino Acids: A Comparative Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-07-01 19:20:23","doi":"10.21203/rs.3.rs-1603417/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Minor revisions","date":"2022-08-01T00:25:31+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2022-06-23T13:50:53+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2022-06-23T09:29:32+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Optical and Quantum Electronics","date":"2022-05-03T16:53:21+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-04-29T02:56:10+00:00","index":"","fulltext":""},{"type":"submitted","content":"Optical and Quantum Electronics","date":"2022-04-28T02:09:47+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"optical-and-quantum-electronics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"oqel","sideBox":"Learn more about [Optical and Quantum Electronics](https://www.springer.com/journal/11082)","snPcode":"11082","submissionUrl":"https://submission.nature.com/new-submission/11082/3","title":"Optical and Quantum Electronics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"77d669c4-d5c4-4487-98d7-ef3a88b05ef7","owner":[],"postedDate":"July 1st, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2022-08-16T05:04:32+00:00","versionOfRecord":[],"versionCreatedAt":"2022-07-01 19:20:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1603417","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1603417","identity":"rs-1603417","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}