Repositioning randomly selected Drugs as Antidepressants by computational and Invivo methods

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Naveena, Swathi konda This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4686166/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 3 You are reading this latest preprint version Abstract Drug repositioning is also known as drug repurposing, drug refilling. Drug repositioning is one of the most preferred field in current research. The drugs with different adverse effect and the drugs which are shelved can be used for the treatment of other diseases. Thus it helps in finding new therapeutic index for already existing drugs. The main advantage of this drug reposioning is it decreases the investment in drug discovery and optimization, and all the pharmacokinetics studies will be readily available as their profiles are already established. In recent times one of the most useful strategies for repositioning the drug of the therapeutic activity towards other new target is done by computational screening. The deeper knowledge about pathogenesis of depression helps us to develop or discover the new drug moieties through drug repositioning to treat the disease condition of depression. In this study we have selected randomly some available drugs and repurposed them as potent anti depressant agents using Insilico and Invivo studies. Antidepressant Insilico studies Docking ADMET MMGBSA Simulation studies Invivo studies. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 1. Introduction Depression is an intense normal response but usually of relatively brief duration to loss and disappointment, it is a prominent feature of several mood disorders. Depression is characterized by feelings on intense sadness or worry, agitation, self deprecation, physical changes like insomnia,anorexia, loss of enthusiasm and mental slowing. Endogenous depression occurs due to the concentration of various biogenic amines and other modulators of nervous transmission at neuronal level. According to monoamine hypothesis, depression is due to decreased or functional deficiency of monoamines i.e Norepineprine, serotonin, Dopamine, and 5-HT. But according to receptor sensitivity hypothesis, it is super sensitivity and upregulation of post synaptic recdeptors In our research asa part of searching a new potent antidepressant agent from the randomly selected drugs we have used various Insilico studies. And the methods used are Molecular docking, ADMET screening, MMGBSA calculations and simulation studies. All these studies helped us to find out best interaction of the potent ligand and target which is responsible for inhibition. Further more all these studies provide required key information to find out the potent antidepressant agent. 2. Methods The 3D structure of Serotonin tranporter (PDB ID: 1kuv, Resolution: 2.0 Å) and MAO-A(PDB ID : 2Z5Y) was collected from the protein data bank. The protein structure was prepared using protein preparation wizard module in the schrodinger software[ 8 ]. The protein structure was modified by removing similar binding sites, water molecules, by adding hydrogens, by defining bondlengths and similar chains are also removed. Then the particular protein was minimized using prime module[ 9 ]. Grid box was generated to identify the active site for binding. Finally all the randomly selected drugs were docked with the preferred protein of serotonin transporter and monoamino oxidase by using Glide mode of scrodinger[ 10 ]. The compounds with the best Glide score was selected for the further process. MMGBSA studies were performed using prime molecular mechanics of schrodinger VSGB2.0 solvent model[ 11 ] in order to obtain free energy binding of ligand receptor complex and energy minimization was also performed. Followed by simulation studies which are carried for the ligand and receptor complex with best Glide score and free energy using Desmond module of schrodinger to determine the binding stability of ligand and receptor. RMSD, RMSF, Interaction fraction of protein ligand complex during 100ns, Time line representation in 100ns, radius of gyration were also determined Table-1 Some of the randomly selected drugs S.NO DRUG THERAPEUTIC USE 1A7 Chloramphenicol Epilepsy 2A7 Sodium valproate Epilepsy 3A7 Atorvastatin HMG-CoA reductase inhibitors 4A7 Cinnamoyl chloride Precursor 5A7 Zolmitriptan migraine 6A7 Simvastatin HMG-CoA reductase inhibitors 7A7 Naproxen NSAIDS 8A7 Domperidone Dopamine antagonist 9A7 Tramadol Hcl Opoid analgesic 10A7 Enrofloxacin antibiotic 11A7 Rasagyline mesylate Parkinsons disease 12A7 Nimesulide NSAIDS 13A7 Alpha lipoic acid Antioxidant 14A7 Atropine sulphate Anticholinergic 15A7 Sulphamethaxazole Sulphonamide antibiotic 16A7 Isoniazid Antituberculosis 17A7 (STANDARD) Paroxetine Antidepressant 18A7 (STANDARD) Phenelzine Antidepressant Results and discussion The docking results(glidescore),MMGBSA,ADMET studies were summated in the tables 1-7 and compounds with best glide score,2D representation of simulation studies were given in figure 1-8. The results obtained helps us find the potent antidepressant agent from the randomly selected drugs. Docking studies The molecular docking studies were performed to obtain best binding affinities of the ligand and protein using glide module of schrodinger of molecular docking program. All the randomly selected drugs were docked with the preferred proteins SSRT (PDB id: 1KUV) and MAO-A (PDB id : 2Z5Y) to obtain best inhibitory activity of the ligand against the protein. The results are depicted in the table 1,2. It clearly demonstrated that some of the randomly selected drugs are significantly active against SSRT and MOA-A with significant glide score when compared to standard paroxetine(-4.7). Most of the selected drugs have good affinity with the receptor due to more liphophilicity and hydrogen bonding. Compound 1A7(-8.2) & 9A7 ( -8.1) has shown good affinity with SSRT , compound 1A7(-8.4) & 13A7(-7.2) has shown good affinity with MAO-A . Docking results of the selected drugs and protein are summated in table 2&3. The docked analogs with best glide score against SSRT & MAO-A are depicted in figure 2&3. The same binding pocket was used for all the selected drugs. Table : 2 Docking results of selected drugs with SSRT (PDB id: 1KUV) Compound G.score L. EvdW Ph En H B XP Elec Low MW R p XP Penalties 1A7 -8.2 -4.41 0 -0.996 −0.26 −0.5 0.52 0 2A7 -3.1 -4.42 0 -0.7 -0.24 -0.5 0.52 0 3A7 -5.17 -3.18 0 -0.7 −0.63 −0.5 0.76 0 4A7 -5.64 -3.77 0 0 −0.39 −0.36 0.84 0 5A7 -4.66 -3.82 0 -1.18357 −0.34 −0.5 0.45 0 6A7 -2.8 -3.42 0 -0.21419 −0.3 −0.5 0.54 0 7A7 -1.0 -3.28 0 0 −0.33 −0.5 1.64 0 8A7 -4.8 -3.11 0 -0.7 −0.37 −0.5 1.45 0 9A7 -8.1 -4.42 0 -1.3228 −0.31 −0.5 0.45 0 10A7 -5.8 -4.48 0 -1.66 −0.33 −0.5 0.54 0 11A7 -5.6 -4.56 0 -1.95375 −0.34 −0.5 1.64 0 12A7 -6.3 -3.78 0 0 −0.68 −0.5 1.45 0 13A7 -4.2 -3.89 0 -1.12311 −0.43 −0.5 1.52 0 14A7 -0.9 -3.42 0 -0.69132 −0.33 −0.5 1.59 0 15A7 -4.6 -3.00 0 -0.35 −0.38 −0.46 0.25 0 16A7 -5.3 -3.18 0 -1.85588 −0.34 −0.5 0.68 0 17A7 (STANDARD) -4.7 -3.00 0 0 −0.38 −0.46 1.14 0 Table :3 Docking results of selected drugs with MAO-A (PDB id: 2Z5Y ) : Compound G.score L. EvdW Ph En H B XP Elec Low MW R p XP Penalties 1A7 -8.4 -3.41 0 −0.55 −0.26 −0.5 0.62 0 2A7 -3.9 -3.32 0 -0.55 -0.54 -0.5 0.56 0 3A7 -5.8 -2.18 0 −2.31 −0.63 −0.5 0.56 0 4A7 -5.4 -2.77 0 −1.92 −0.39 −0.36 0.64 0 5A7 -6.2 -2.82 0 −1.07 −0.34 −0.5 0.55 0 6A7 -3.0 -2.42 0 −1.49 −0.3 −0.5 0.54 0 7A7 -6.5 -2.28 0 −1.92 −0.33 −0.5 1.64 0 8A7 -5.6 -2.11 0 −2 −0.37 −0.5 1.55 0 9A7 -3.4 -3.42 0 −0.43 −0.31 −0.5 0.65 0 10A7 -0.8 -3.48 0 −0.24 −0.33 −0.5 0.54 0 11A7 -0.6 -3.56 0 −1.82 −0.34 −0.5 1.64 0 12A7 -1.8 -2.78 0 −1.87 −0.68 −0.5 1.45 0 13A7 -7.2 -3.89 0 −1.59 −0.43 −0.5 1.52 0 14A7 -1.1 -3.42 0 −1.62 −0.33 −0.5 1.59 0 15A7 -4.8 -3.00 0 −1.92 −0.38 −0.46 0.25 0 16A7 -6.0 -2.18 0 −2.1 −0.34 −0.5 0.68 0 18A7 (STANDARD) -2.2 -3.00 0 −1.67 −0.38 −0.46 1.14 0 ADMET Properties The ADMET properties are determined for selected drug molecules(1A7-16A7) using QUIKPROP module of schrodinger. The properties determined using these studies are Molecular weight, number of hydrogen bond domars, hydrogen bond acceptors, Mlogp, whether the molecules obeys Lipinski rule of five or not and oral absorption. The atomic charges were determined using jaguar module of schrodinger.(Govindarajan et al.,)[1]. The molecular of most of the drugs is below 500 mol -1 except 2A7 & 13A7. Number of hydrogen bond donar are less than five, number of hydrogen acceptors are less than 10 except 13A7. Mlogp is below 5. All the compounds found to obey Lipinski rule of 5 except 13A7 as it has 2 violations. Metabolism rate is between 1-5 and the % of human oral availability is between 69 to 100%. Table-4 : Insilico ADMET screening for selected analogs S.no M.W di D.HB A.HB M plog o/w Lipinski rule of 5 metabolism % of oral absorption 1A 166.1 1.1 0 2 1.96 0 3 82% 2A 558.6 4.1 4 6 3.48 0 3 76% 3A 166.6 4.2 0 1 2.31 0 4 88% 4A 287.3 5.1 2 3 1.45 0 3 100% 5A 418.3 4.3 1 5 3.77 0 5 100% 6A 230.2 7.0 1 3 2.57 0 4 69% 7A 425.9 6.6 2 3 3.28 0 3 70% 8A 263.3 8.9 1 3 2.77 0 4 86% 9A 359.3 3.5 1 5 1.75 0 5 90% 10A 267.3 9.2 2 4 1.65 0 3 94% 11A 308.3 3.6 1 5 0.91 0 3 100% 12A 206.3 8.1 1 2 1.57 0 3 78% 13A 676.8 8.3 4 12 1.60 2 4 84% 14A 253.2 3.7 2 4 0.25 0 3 80% 15A 137.1 5.0 2 4 -0.47 0 1 86% 16A7 476.8 8.3 2 10 1.50 2 4 84% 17A7 (STANDARD) 329.3 2.1 1 5 3.10 0 3 88% 18A7 (STANDARD) 234.27 2.0 1 5 2.80 0 4 88% MMGBSA studies :- Binding free energy calculations are assessed by MMGBSA approach. To determine binding free energy of receptor and ligand complex additionally energy minimization was done by MMGBSA prime modular mechanicsof schrodinger. The energy of particular complex was calculated using OPLS3 force field. The ∆G bind = E rec -E lig -E com Results obtained from free energy calculations provide the information about bound and unbound states in ligand receptor complex. The results of MMGBSA reveal that the ∆G bind values were obtained in the range of -7 to -40(SSRT) & -17 to -36(1KUV) for the selected compounds and all other calculated properties are also contributing to the total free binding energy. Table 5 :- MM-GBSA studies results (1kuv) S.no MMGBSA-( Bind) MMGBSA-( Bind-coloumb) MMGBSA-(Bind-covalent) MMGBSA- (Bind H bond) MMGBSA-( Bind-Lipo) MMGBSA- (Bind-vdW) 1A7 -23.6 -3.8 -2.3 -0.3 -8.9 -32.3 2A7 -20.2 -10.7 -3.5 -1.3 -6.02 -20.2 3A7 -20.4 -30.8 2.01 -1.1 -13.4 -20.6 4A7 -32.4 -28.1 3.4 0.12 -4.2 -21.6 5A7 -35.4 -19.3 7.8 0.47 -10.9 -21.8 6A7 -33.2 -11.3 -4.4 -0.16 -9.06 -33.5 7A7 -35.4 -2.42 -8.2 -1.10 -11.7 -40.2 8A7 -42.2 23.6 5.3 0.13 -17.15 -28.2 9A7 -30.3 7.05 -9.8 0.16 -7.8 -31.0 10A7 -24.8 -6.72 1.9 -0.86 -11.2 -20.1 11A7 -19.11 -21.2 17.6 -1.19 -12.8 -36.4 12A7 -12.4 -3.60 -1.8 -1.24 -9.6 -7.00 13A7 -38.2 -1.12 -2.9 0.86 -8.4 -15.8 14A7 -11.4 -4.70 3.4 -0.42 -5.2 -28.01 15A7 -20.1 -3.92 -5.2 -0.4 -11.6 -22.6 16A7 -19.11 -21.2 17.6 -1.19 -12.8 -36.4 17A7 (STANDARD) -24.2 -3.68 -2.1 -0.2 -8.4 -32.6 Table 6 :- MM-GBSA studies results (2Z5Y) S.no MMGBSA-( Bind) MMGBSA-( Bind-coloumb) MMGBSA-(Bind-covalent) MMGBSA- (Bind H bond) MMGBSA-( Bind-Lipo) MMGBSA- (Bind-vdW) 1A7 -24.6 -18.8 -10.8 -0.6 -10.9 -28.3 2A7 -22.2 -16.7 -12.5 -11.3 -16.2 -22.2 3A7 -26.2 -33.8 2.01 -11.1 -18.4 -24.6 4A7 -22.6 -26.1 6.4 0.12 -14.2 -26.6 5A7 -36.4 -21.3 8.8 0.47 -12.9 -22.8 6A7 -32.2 -21.3 -8.4 -0.86 -19.6 -32.5 7A7 -33.4 -22.4 -8.2 -1.80 -21.7 -36.2 8A7 -28.2 23.8 5.3 0.43 -18.15 -26.2 9A7 -28.3 11.05 -8.8 1.16 -17.8 -33.0 10A7 -26.8 -16.72 10.9 -1.86 -14.2 -26.1 11A7 -31.11 -28.2 16.6 -11.19 -15.8 -33.4 12A7 -18.4 -6.60 -10.8 -12.24 -18.6 -17.00 13A7 -36.2 -3.12 -12.9 10.86 -18.4 -18.8 14A7 -19.4 -7.70 13.4 -0.42 -15.2 -26.01 15A7 -24.1 -6.92 -15.2 -2.40 -11.6 -20.6 16A7 -18.4 -6.60 -10.8 -12.24 -18.6 -17.00 17A7 (STANDARD) -28.2 -16.68 -12.1 -0.6 -10.4 -28.6 18A7 (STANDARD) -26.2 -15.68 -12.1 -0.56 -11.2 -26.6 Molecular dynamic simulation studies of best docked complex The Glide score of drug complex 1A7/1KUV was found to be highest among the selected drugs . the stsbility of the particular complex was determined using Desmond module of schrodinger software at 100ns MD (Guo et al.,)[2]. In the process the complex was solvated using TIP3P(Jogensen et al.,)[3] at 10A 0 buffer region followed by deletion of overlapping water molecule & neutralization was done, constant temperature of 300K & pressure 1bar was maintained.(martyna et al.,)[4][5]. And futher RMSD & RMSF is observed during 100 ns finally interaction fraction of ligand with protein is also depicted. The RMSF (figure 4) was observed in the range of 0.8-2.48 A 0 . The radius of gyration (figure 7) was in the range of 3.6-3.75 A 0 . Molecular surface area is 264- 273 A 0 , Solvent accessibility surface area is 0-15 A 0 . Polar surface of ligands is 204-222 A respectively. The 2-Dimensional interaction representation (figure 8) predicts the hydrogen bonding formed by ligand with MET 159 which is saved in molecular dynamic trajectory pose. The picture indicates that the OH group of 1A7 compound donate 90% of hydrogen bond to LEU 121, the NH 2 group of compound 1A7 donate 83% of hydrogen bond to HIS 122 and the carbonyl oxygen form 43% of hydrogen bond with MET 159 with water molecule in the complete simulation process. Pharmacological activity Antidepressant activity The randomly selected drugs were screened for antidepressant activity by force swim method [6][7] in mice (100mg/kg) by comparing with the standard drug paroxetine (20mg/kg). For the following study adult male mice (20±5g) were selected and provided with free acess for food and water. The mice were grouped , in each group 6 were used and housed. Acute oral toxicity & LD50 is determined according to OECD guidelines.selected drugs (100mg/kg & paroxetine(20mg/kg) was suspended in tween80 of 0.5% and injected in to the mice through I.P route. After 0.5 hr the mice is dropped in to the glass cylinder of diameter 12cm , height 30cm containing 25cm of water with the temperature 25±2 0 C approximately. The each mice was left for 6min and its immobility was observed when the mice leaves struggling & remains floating in the water with out any movement , & it is concluded as immobility. This immobility rate was determined for each mice. % DID (decrease in immobility duration) was calculated using the following formula for test & standard. %DID = [A-B/B]*100 A – duration of immobility in test group. B – duration of immobility in control group. Pharmacological screening The randomly selected drugs from (1A7-16A7) were screened for antidepressant activity using forced swim method in mice at a dose of 100 mg/kg by comparing with the standard drug Paroxetine and phenelzine (20 mg/kg). The mortality rate was not observed in the tested groups. There are no behavioural change observed in tested groups. The selected drugs were observed to be safe until 2000mg/kg of body weight. Firstly the dose dependent study was performed using various doses like 25mg/kg,50mg/kg,100mg/kg & 200mg/kg by intraperitonial route. From the results the maximum effective dose was determined. Antidepressant activity was depicted in the Table 7. The standard drug paroxetine decreased immobility to 67% at a dose level of 20 mg/kg. In our present research work all the selected drugs have been shown nearer immobility when compared with the standard drug of paroxetine(20mg/kg). Among all the selected drugs 1A7 and 9A7 were found potent, showing % reduction of immobility rate at 61.0% & 63.0% . At the same time, compounds 10A7 and 12A7 had moderate immobility reduction activity of 49.1% & 46.3% while compounds 6A7 and 7A7 had poor immobility reduction activity of 28.4% & 25.9%. Finally the drugs 1A7 and 9A7 have been produced potent antidepressant activity when compared with the standard drug paroxetine and phenelzine. The immobility time of compound 1A7 and 9A7 (20 mg/kg, i.p.) and Paroxetine (20 mg/kg, i.p.) using forced swim method. (Values mentioned as mean ± S.E.M. all the Values are significant *P < 0.001, when compared with the control group. Table :- 7 Effect of randomly selected drugs in forced swim method S.NO Selected drugs DOI (mean ±SEM) % DID 1 1A7 38.25 ± 5.2 61.0% 2 4A7 54.26 ± 4.8 44.7% 3 6A7 70.25 ± 5.5 28.4% 4 7A7 72.75 ± 6.4 25.9% 5 9A7 36.28 ± 4.2 63.0% 6 10A7 50.00 ± 4.6 49.1% 7 12A7 52.75 ± 4.7 46.3% 8 16A7 55.26 ± 5.5 43.7% 9 control 98.25 ± 3.6 0.0 STD Paroxetine 32.00 ± 1.7 67.0% STD Phenelzine 30.00 ± 1.7 66.0% The Data is analyzed using one-way ANOVA method using Dunnett’s test. n = 6; at the dose ( 100 mg/kg). All the values were mentioned using mean ± S.E.M. Conclusion In conclusion, from the selected drugs 1A7-16A7, most of the drugs have potent binding affinity with the selected protein 1KUV & 2Z5Y . Molecular docking studies and MMGBSA studies were performed to determine the potent ligand which has best binding affinity with preferred protein of 1KUV & 2Z5Y Protein and to finally conclude them as potent antidepressant agent. Molecular Dynamic simulation studies for the highest glide score drug of 1A7 which is complexed with protein 1KUV has been revealed that the stability of ligand was achieved by forming most stable hydrophobic interactions. The results were also depicted by the modifications in the pharmacophoe features which have helped in improving the inhibitory activity. The drug 1A7 has been showed good activity using Invivo Force swim method . All the insilico studies and invivo studies in the present investigation helped us to repurpose the efficient drug molecules from the randomly selected drugs as potent Antidepressant agents. There was good correlation observed between InSilico and Invivo studies. Declarations Acknowledgement The authors like to express the gratitude to the management of Sri padmavati Mahila Visvavidyalayam, Institute of pharmaceutical sciences, Tirupati, Andrapradesh-517502,India for providing the facilities required to complete the study project. Conflict of interest There is no any conflict of interest, according to authors. Authors contribution All the authors have been contributed to the preparation of manuscript, participated in reviewing, editing, and the approved of the final draft for publication. The research profile of the authors can be verified from the ORCID ids, given below: Palupanuri Naveena : https://orcid.org/0009-0007-2597-1822 Swathi Konda : https://orcid.org/0000-0002-3186-0543 References Govindarajan M, Periandy S, Carthigayen K. FT-IR and FT-Raman spectra, thermo dynamical behavior, HOMO and LUMO, UV, NLO properties, computed frequency estimation analysis and electronic structure calculations on α-bromotoluene. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy. 2012 Nov 1;97:411-22. Guo Z, Mohanty U, Noehre J, Sawyer TK, Sherman W, Krilov G. Probing the α‐helical structural stability of stapled p53 peptides: molecular dynamics simulations and analysis. Chemical biology & drug design. 2010 Apr;75(4):348-59. Jorgensen WL, Chandrasekhar J, Madura JD, Impey RW, Klein ML. Comparison of simple potential functions for simulating liquid water. The Journal of chemical physics. 1983 Jul 15;79(2):926-35. Martyna GJ, Klein ML, Tuckerman M. 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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-4686166","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":323410655,"identity":"745b4276-45f9-47e5-a9d4-f880ca6b373f","order_by":0,"name":"Palupanuri. Naveena","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA80lEQVRIiWNgGAWjYNCCAjjLBogZGw8Q1mIAZ6WBtDSQpOUwmMSrRT4iO3Uzj4FdHv+M5IOPC2rO261tPwy0pcYmGpcWwxu5227zGCQXS9xISzaecex28rYziUAtx9JyG3BpmQHWwpzYcOaMmTQP2+1kswNALYwNhwlpqU+cf+b89988/84lm51/iF+LvARYy+HEDcd72Jh52w7Ymd0gYIsBz9ttN+cYHE/ceLzNWJq3LznB7AbQlgQ8fpFvz912401FdeK8w8wPP/N8s7M3O5/+8MGHGhvcthxAE0gEq0zAoRxsC7pZ9ngUj4JRMApGwQgFAJLLZysbCgyGAAAAAElFTkSuQmCC","orcid":"","institution":"Sri Padmavati Mahila Visvavidyalayam","correspondingAuthor":true,"prefix":"","firstName":"Palupanuri.","middleName":"","lastName":"Naveena","suffix":""},{"id":323410656,"identity":"bcda27f2-4937-481c-9678-3389ca282ef6","order_by":1,"name":"Swathi konda","email":"","orcid":"","institution":"Sri Padmavati Mahila Visvavidyalayam","correspondingAuthor":false,"prefix":"","firstName":"Swathi","middleName":"","lastName":"konda","suffix":""}],"badges":[],"createdAt":"2024-07-04 11:16:02","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4686166/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4686166/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":61385795,"identity":"ea1a1981-fe33-4fd0-afbb-bcf139b6b389","added_by":"auto","created_at":"2024-07-30 07:05:57","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":3908863,"visible":true,"origin":"","legend":"\u003cp\u003eLigand interaction of coumpounds 1A7,2A7,4A7,8A7,9A7,10A7,11A7,12A7, 16A7 with SSRT\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4686166/v1/01ee3f1af582079f5ee2cbce.png"},{"id":61386508,"identity":"55bc52c2-3b92-4d65-86dd-1de87f42ceed","added_by":"auto","created_at":"2024-07-30 07:13:58","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":4602986,"visible":true,"origin":"","legend":"\u003cp\u003eLigand interaction of coumpounds 1A7,2A7,3A7,4A7,5A7,6A7,7A7,12A7,14A7, 15A7 with SSRT\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4686166/v1/76d6c23459fd1113dd559705.png"},{"id":61386507,"identity":"e742948b-8165-43c4-8751-8493406ed81f","added_by":"auto","created_at":"2024-07-30 07:13:57","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":108006,"visible":true,"origin":"","legend":"\u003cp\u003eRMSD (A\u003csup\u003e0\u003c/sup\u003e) of simulated protein pdb 1KUV \u0026nbsp;complexed with the drug 1A7 during 100 ns Molecular dynamic simulation.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4686166/v1/3aae5b638d25a898848104a6.png"},{"id":61387508,"identity":"74df90f3-8e34-4a44-bfd9-a68fe201edd0","added_by":"auto","created_at":"2024-07-30 07:21:58","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":47739,"visible":true,"origin":"","legend":"\u003cp\u003eRMSF of simulated protein pdb 1KUV \u0026nbsp;complexed with drug 1A7 during 100ns Molecular Dynamic Simulation\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4686166/v1/d76c3ae751159cf298e1df1f.png"},{"id":61385802,"identity":"265fb265-861b-441f-881a-b4e190290449","added_by":"auto","created_at":"2024-07-30 07:05:58","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":31963,"visible":true,"origin":"","legend":"\u003cp\u003eInteraction fraction of pdb 1KUV complexed with the drug 1A7 during 100ns Molecular Dynamic Simulation\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4686166/v1/334bb1b18cf13c871284c566.png"},{"id":61385792,"identity":"cc3211ff-85b0-4ac1-9504-71022331d5b7","added_by":"auto","created_at":"2024-07-30 07:05:57","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":98410,"visible":true,"origin":"","legend":"\u003cp\u003eTime line interaction \u0026nbsp;with different proteins formed by 1A7 with 1KUV .pdb during 100 ns Molecular Dynamic Simulation\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-4686166/v1/472ba825df529f4646f28896.png"},{"id":61385796,"identity":"0bd11172-d67e-447d-b7b3-3f62e8c14ee9","added_by":"auto","created_at":"2024-07-30 07:05:58","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":138688,"visible":true,"origin":"","legend":"\u003cp\u003eLigand properties of 1A7 \u0026nbsp;complexed with pdb 1KUV during 100 ns Molecular Dynamic Simulation.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-4686166/v1/d2870af1a9d34aec27d69112.png"},{"id":61385801,"identity":"86f12d85-1d03-4856-b063-e1652d66f31c","added_by":"auto","created_at":"2024-07-30 07:05:58","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":60203,"visible":true,"origin":"","legend":"\u003cp\u003e2 Dimensional interaction picture of drug 1A7 complexed \u0026nbsp;with pdb 1KUV during 100 ns Molecular Dynamic Simulation\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-4686166/v1/5d46b6c240b70f1369acdbb9.png"},{"id":61385800,"identity":"38faca15-2159-43a7-af7c-d496d058a105","added_by":"auto","created_at":"2024-07-30 07:05:58","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":462791,"visible":true,"origin":"","legend":"\u003cp\u003eUnnumbered image in the Method section.\u003c/p\u003e","description":"","filename":"unfig1.png","url":"https://assets-eu.researchsquare.com/files/rs-4686166/v1/8b58cafc7697108e63f5ac92.png"},{"id":61385799,"identity":"4045b617-c717-42ae-b298-2ca4b8a7e822","added_by":"auto","created_at":"2024-07-30 07:05:58","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":75274,"visible":true,"origin":"","legend":"\u003cp\u003eUnnumbered image in the Results and discussion section.\u003c/p\u003e","description":"","filename":"unfig2.png","url":"https://assets-eu.researchsquare.com/files/rs-4686166/v1/cffc00bc4f6802d690bf910c.png"},{"id":61388153,"identity":"074fb5da-327f-4dc6-86a6-50ef7f7d4c09","added_by":"auto","created_at":"2024-07-30 07:30:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":15146700,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4686166/v1/d6a43db0-692d-40d2-92e6-dfbc3f69dac0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Repositioning randomly selected Drugs as Antidepressants by computational and Invivo methods","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eDepression is an intense normal response but usually of relatively brief duration to loss and disappointment, it is a prominent feature of several mood disorders. Depression is characterized by feelings on intense sadness or worry, agitation, self deprecation, physical changes like insomnia,anorexia, loss of enthusiasm and mental slowing. Endogenous depression occurs due to the concentration of various biogenic amines and other modulators of nervous transmission at neuronal level. According to monoamine hypothesis, depression is due to decreased or functional deficiency of monoamines i.e Norepineprine, serotonin, Dopamine, and 5-HT. But according to receptor sensitivity hypothesis, it is super sensitivity and upregulation of post synaptic recdeptors\u003c/p\u003e \u003cp\u003eIn our research asa part of searching a new potent antidepressant agent from the randomly selected drugs we have used various Insilico studies. And the methods used are Molecular docking, ADMET screening, MMGBSA calculations and simulation studies. All these studies helped us to find out best interaction of the potent ligand and target which is responsible for inhibition. Further more all these studies provide required key information to find out the potent antidepressant agent.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003eThe 3D structure of Serotonin tranporter (PDB ID: 1kuv, Resolution: 2.0 \u0026Aring;) and MAO-A(PDB ID : 2Z5Y) was collected from the protein data bank. The protein structure was prepared using protein preparation wizard module in the schrodinger software[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The protein structure was modified by removing similar binding sites, water molecules, by adding hydrogens, by defining bondlengths and similar chains are also removed. Then the particular protein was minimized using prime module[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Grid box was generated to identify the active site for binding. Finally all the randomly selected drugs were docked with the preferred protein of serotonin transporter and monoamino oxidase by using Glide mode of scrodinger[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The compounds with the best Glide score was selected for the further process. MMGBSA studies were performed using prime molecular mechanics of schrodinger VSGB2.0 solvent model[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] in order to obtain free energy binding of ligand receptor complex and energy minimization was also performed. Followed by simulation studies which are carried for the ligand and receptor complex with best Glide score and free energy using Desmond module of schrodinger to determine the binding stability of ligand and receptor. RMSD, RMSF, Interaction fraction of protein ligand complex during 100ns, Time line representation in 100ns, radius of gyration were also determined\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eTable-1 Some of the randomly selected drugs\u003c/span\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS.NO\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDRUG\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTHERAPEUTIC USE\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1A7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChloramphenicol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEpilepsy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2A7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSodium valproate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEpilepsy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3A7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAtorvastatin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHMG-CoA reductase inhibitors\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4A7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCinnamoyl chloride\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePrecursor\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5A7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eZolmitriptan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emigraine\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6A7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSimvastatin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHMG-CoA reductase inhibitors\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7A7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNaproxen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNSAIDS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8A7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDomperidone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDopamine antagonist\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9A7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTramadol Hcl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOpoid analgesic\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10A7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEnrofloxacin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eantibiotic\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11A7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRasagyline mesylate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eParkinsons disease\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12A7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNimesulide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNSAIDS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13A7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAlpha lipoic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAntioxidant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14A7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAtropine sulphate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAnticholinergic\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15A7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSulphamethaxazole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSulphonamide antibiotic\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16A7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIsoniazid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAntituberculosis\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17A7\u003c/p\u003e \u003cp\u003e(STANDARD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParoxetine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAntidepressant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18A7\u003c/p\u003e \u003cp\u003e(STANDARD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhenelzine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAntidepressant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Results and discussion","content":"\u003cp\u003eThe docking results(glidescore),MMGBSA,ADMET studies were summated in the tables 1-7 and compounds with best glide score,2D representation of simulation studies were given in figure 1-8. The results obtained helps us find the potent antidepressant agent from the randomly selected drugs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eDocking studies \u0026nbsp;\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe molecular docking studies were performed to obtain best binding affinities of the ligand and protein using glide module of schrodinger of molecular docking program. All the randomly selected drugs were docked with the preferred proteins SSRT (PDB id: 1KUV) \u0026nbsp;and MAO-A (PDB id : 2Z5Y) to obtain best inhibitory activity of the ligand against the protein. The results are depicted in the table 1,2. It clearly demonstrated that some of the randomly selected drugs are significantly active against SSRT and MOA-A with significant glide score when compared to standard paroxetine(-4.7). Most of the selected drugs have good affinity with the receptor due to more liphophilicity and hydrogen bonding. Compound 1A7(-8.2) \u0026amp; 9A7 ( -8.1) \u0026nbsp; has shown good affinity with SSRT , compound 1A7(-8.4) \u0026amp; 13A7(-7.2) has shown good affinity with MAO-A .\u003c/p\u003e\n\u003cp\u003eDocking results of the selected drugs and protein are summated in table 2\u0026amp;3. The docked analogs with best glide score against SSRT \u0026amp; MAO-A are depicted in figure 2\u0026amp;3. The same binding pocket was used for all the selected drugs.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eTable : 2 \u0026nbsp;Docking results of selected drugs with SSRT (PDB id: 1KUV)\u003c/u\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"683\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.887262079062957%\" valign=\"top\"\u003e\n \u003cp\u003eCompound\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.66325036603221%\" valign=\"top\"\u003e\n \u003cp\u003eG.score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.469985358711567%\" valign=\"top\"\u003e\n \u003cp\u003eL. EvdW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003ePh En\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.420204978038067%\" valign=\"top\"\u003e\n \u003cp\u003eH B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.68814055636896%\" valign=\"top\"\u003e\n \u003cp\u003eXP Elec\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.809663250366032%\" valign=\"top\"\u003e\n \u003cp\u003eLow MW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003eR p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370424597364568%\" valign=\"top\"\u003e\n \u003cp\u003eXP Penalties\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.887262079062957%\" valign=\"top\"\u003e\n \u003cp\u003e1A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.66325036603221%\" valign=\"bottom\"\u003e\n \u003cp\u003e-8.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.469985358711567%\" valign=\"top\"\u003e\n \u003cp\u003e-4.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.420204978038067%\" valign=\"top\"\u003e\n \u003cp\u003e-0.996\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.68814055636896%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.809663250366032%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370424597364568%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.887262079062957%\" valign=\"top\"\u003e\n \u003cp\u003e2A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.66325036603221%\" valign=\"bottom\"\u003e\n \u003cp\u003e-3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.469985358711567%\" valign=\"top\"\u003e\n \u003cp\u003e-4.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.420204978038067%\" valign=\"top\"\u003e\n \u003cp\u003e-0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.68814055636896%\" valign=\"top\"\u003e\n \u003cp\u003e-0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.809663250366032%\" valign=\"top\"\u003e\n \u003cp\u003e-0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370424597364568%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.887262079062957%\" valign=\"top\"\u003e\n \u003cp\u003e3A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.66325036603221%\" valign=\"top\"\u003e\n \u003cp\u003e-5.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.469985358711567%\" valign=\"top\"\u003e\n \u003cp\u003e-3.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.420204978038067%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.68814055636896%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.809663250366032%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370424597364568%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.887262079062957%\" valign=\"top\"\u003e\n \u003cp\u003e4A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.66325036603221%\" valign=\"top\"\u003e\n \u003cp\u003e-5.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.469985358711567%\" valign=\"top\"\u003e\n \u003cp\u003e-3.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.420204978038067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.68814055636896%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.809663250366032%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370424597364568%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.887262079062957%\" valign=\"top\"\u003e\n \u003cp\u003e5A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.66325036603221%\" valign=\"top\"\u003e\n \u003cp\u003e-4.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.469985358711567%\" valign=\"top\"\u003e\n \u003cp\u003e-3.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.420204978038067%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.18357\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.68814055636896%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.809663250366032%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370424597364568%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.887262079062957%\" valign=\"top\"\u003e\n \u003cp\u003e6A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.66325036603221%\" valign=\"top\"\u003e\n \u003cp\u003e-2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.469985358711567%\" valign=\"top\"\u003e\n \u003cp\u003e-3.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.420204978038067%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.21419\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.68814055636896%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.809663250366032%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370424597364568%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.887262079062957%\" valign=\"top\"\u003e\n \u003cp\u003e7A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.66325036603221%\" valign=\"top\"\u003e\n \u003cp\u003e-1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.469985358711567%\" valign=\"top\"\u003e\n \u003cp\u003e-3.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.420204978038067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.68814055636896%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.809663250366032%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370424597364568%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.887262079062957%\" valign=\"top\"\u003e\n \u003cp\u003e8A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.66325036603221%\" valign=\"top\"\u003e\n \u003cp\u003e-4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.469985358711567%\" valign=\"top\"\u003e\n \u003cp\u003e-3.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.420204978038067%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.68814055636896%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.809663250366032%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370424597364568%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.887262079062957%\" valign=\"top\"\u003e\n \u003cp\u003e9A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.66325036603221%\" valign=\"top\"\u003e\n \u003cp\u003e-8.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.469985358711567%\" valign=\"top\"\u003e\n \u003cp\u003e-4.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.420204978038067%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.3228\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.68814055636896%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.809663250366032%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370424597364568%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.887262079062957%\" valign=\"top\"\u003e\n \u003cp\u003e10A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.66325036603221%\" valign=\"top\"\u003e\n \u003cp\u003e-5.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.469985358711567%\" valign=\"top\"\u003e\n \u003cp\u003e-4.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.420204978038067%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.68814055636896%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.809663250366032%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370424597364568%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.887262079062957%\" valign=\"top\"\u003e\n \u003cp\u003e11A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.66325036603221%\" valign=\"top\"\u003e\n \u003cp\u003e-5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.469985358711567%\" valign=\"top\"\u003e\n \u003cp\u003e-4.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.420204978038067%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.95375\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.68814055636896%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.809663250366032%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370424597364568%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.887262079062957%\" valign=\"top\"\u003e\n \u003cp\u003e12A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.66325036603221%\" valign=\"top\"\u003e\n \u003cp\u003e-6.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.469985358711567%\" valign=\"top\"\u003e\n \u003cp\u003e-3.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.420204978038067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.68814055636896%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.809663250366032%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370424597364568%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.887262079062957%\" valign=\"top\"\u003e\n \u003cp\u003e13A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.66325036603221%\" valign=\"top\"\u003e\n \u003cp\u003e-4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.469985358711567%\" valign=\"top\"\u003e\n \u003cp\u003e-3.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.420204978038067%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.12311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.68814055636896%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.809663250366032%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e1.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370424597364568%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.887262079062957%\" valign=\"top\"\u003e\n \u003cp\u003e14A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.66325036603221%\" valign=\"top\"\u003e\n \u003cp\u003e-0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.469985358711567%\" valign=\"top\"\u003e\n \u003cp\u003e-3.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.420204978038067%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.69132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.68814055636896%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.809663250366032%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e1.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370424597364568%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.887262079062957%\" valign=\"top\"\u003e\n \u003cp\u003e15A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.66325036603221%\" valign=\"top\"\u003e\n \u003cp\u003e-4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.469985358711567%\" valign=\"top\"\u003e\n \u003cp\u003e-3.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.420204978038067%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.68814055636896%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.809663250366032%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370424597364568%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.887262079062957%\" valign=\"top\"\u003e\n \u003cp\u003e16A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.66325036603221%\" valign=\"top\"\u003e\n \u003cp\u003e-5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.469985358711567%\" valign=\"top\"\u003e\n \u003cp\u003e-3.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.420204978038067%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.85588\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.68814055636896%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.809663250366032%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370424597364568%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.887262079062957%\" valign=\"top\"\u003e\n \u003cp\u003e17A7\u003c/p\u003e\n \u003cp\u003e(STANDARD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.66325036603221%\" valign=\"top\"\u003e\n \u003cp\u003e-4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.469985358711567%\" valign=\"top\"\u003e\n \u003cp\u003e-3.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.420204978038067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.68814055636896%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.809663250366032%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.345534407027818%\" valign=\"top\"\u003e\n \u003cp\u003e1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.370424597364568%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cu\u003eTable :3 Docking results of selected drugs with MAO-A \u0026nbsp;(PDB id: 2Z5Y ) :\u003c/u\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"697\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.454935622317596%\" valign=\"top\"\u003e\n \u003cp\u003eCompound\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003eG.score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.017167381974248%\" valign=\"top\"\u003e\n \u003cp\u003eL. EvdW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003ePh En\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003eH B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003eXP Elec\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.72818311874106%\" valign=\"top\"\u003e\n \u003cp\u003eLow MW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.297567954220314%\" valign=\"top\"\u003e\n \u003cp\u003eR p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.158798283261802%\" valign=\"top\"\u003e\n \u003cp\u003eXP Penalties\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.454935622317596%\" valign=\"top\"\u003e\n \u003cp\u003e1A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"bottom\"\u003e\n \u003cp\u003e-8.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.017167381974248%\" valign=\"top\"\u003e\n \u003cp\u003e-3.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.72818311874106%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.297567954220314%\" valign=\"top\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.158798283261802%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.454935622317596%\" valign=\"top\"\u003e\n \u003cp\u003e2A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"bottom\"\u003e\n \u003cp\u003e-3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.017167381974248%\" valign=\"top\"\u003e\n \u003cp\u003e-3.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e-0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e-0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.72818311874106%\" valign=\"top\"\u003e\n \u003cp\u003e-0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.297567954220314%\" valign=\"top\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.158798283261802%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.454935622317596%\" valign=\"top\"\u003e\n \u003cp\u003e3A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e-5.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.017167381974248%\" valign=\"top\"\u003e\n \u003cp\u003e-2.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;2.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.72818311874106%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.297567954220314%\" valign=\"top\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.158798283261802%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.454935622317596%\" valign=\"top\"\u003e\n \u003cp\u003e4A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e-5.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.017167381974248%\" valign=\"top\"\u003e\n \u003cp\u003e-2.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;1.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.72818311874106%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.297567954220314%\" valign=\"top\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.158798283261802%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.454935622317596%\" valign=\"top\"\u003e\n \u003cp\u003e5A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e-6.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.017167381974248%\" valign=\"top\"\u003e\n \u003cp\u003e-2.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.72818311874106%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.297567954220314%\" valign=\"top\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.158798283261802%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.454935622317596%\" valign=\"top\"\u003e\n \u003cp\u003e6A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e-3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.017167381974248%\" valign=\"top\"\u003e\n \u003cp\u003e-2.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.72818311874106%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.297567954220314%\" valign=\"top\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.158798283261802%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.454935622317596%\" valign=\"top\"\u003e\n \u003cp\u003e7A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e-6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.017167381974248%\" valign=\"top\"\u003e\n \u003cp\u003e-2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;1.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.72818311874106%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.297567954220314%\" valign=\"top\"\u003e\n \u003cp\u003e1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.158798283261802%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.454935622317596%\" valign=\"top\"\u003e\n \u003cp\u003e8A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e-5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.017167381974248%\" valign=\"top\"\u003e\n \u003cp\u003e-2.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.72818311874106%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.297567954220314%\" valign=\"top\"\u003e\n \u003cp\u003e1.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.158798283261802%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.454935622317596%\" valign=\"top\"\u003e\n \u003cp\u003e9A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e-3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.017167381974248%\" valign=\"top\"\u003e\n \u003cp\u003e-3.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.72818311874106%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.297567954220314%\" valign=\"top\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.158798283261802%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.454935622317596%\" valign=\"top\"\u003e\n \u003cp\u003e10A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e-0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.017167381974248%\" valign=\"top\"\u003e\n \u003cp\u003e-3.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.72818311874106%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.297567954220314%\" valign=\"top\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.158798283261802%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.454935622317596%\" valign=\"top\"\u003e\n \u003cp\u003e11A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e-0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.017167381974248%\" valign=\"top\"\u003e\n \u003cp\u003e-3.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.72818311874106%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.297567954220314%\" valign=\"top\"\u003e\n \u003cp\u003e1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.158798283261802%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.454935622317596%\" valign=\"top\"\u003e\n \u003cp\u003e12A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e-1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.017167381974248%\" valign=\"top\"\u003e\n \u003cp\u003e-2.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;1.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.72818311874106%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.297567954220314%\" valign=\"top\"\u003e\n \u003cp\u003e1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.158798283261802%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.454935622317596%\" valign=\"top\"\u003e\n \u003cp\u003e13A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e-7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.017167381974248%\" valign=\"top\"\u003e\n \u003cp\u003e-3.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;1.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.72818311874106%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.297567954220314%\" valign=\"top\"\u003e\n \u003cp\u003e1.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.158798283261802%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.454935622317596%\" valign=\"top\"\u003e\n \u003cp\u003e14A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e-1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.017167381974248%\" valign=\"top\"\u003e\n \u003cp\u003e-3.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;1.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.72818311874106%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.297567954220314%\" valign=\"top\"\u003e\n \u003cp\u003e1.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.158798283261802%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.454935622317596%\" valign=\"top\"\u003e\n \u003cp\u003e15A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e-4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.017167381974248%\" valign=\"top\"\u003e\n \u003cp\u003e-3.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;1.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.72818311874106%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.297567954220314%\" valign=\"top\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.158798283261802%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.454935622317596%\" valign=\"top\"\u003e\n \u003cp\u003e16A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e-6.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.017167381974248%\" valign=\"top\"\u003e\n \u003cp\u003e-2.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.72818311874106%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.297567954220314%\" valign=\"top\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.158798283261802%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.454935622317596%\" valign=\"top\"\u003e\n \u003cp\u003e18A7\u003c/p\u003e\n \u003cp\u003e(STANDARD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e-2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.017167381974248%\" valign=\"top\"\u003e\n \u003cp\u003e-3.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.586552217453505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.72818311874106%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026minus;0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.297567954220314%\" valign=\"top\"\u003e\n \u003cp\u003e1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.158798283261802%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eADMET Properties\u0026nbsp;\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe ADMET properties are determined for selected drug molecules(1A7-16A7) using QUIKPROP module of schrodinger. The properties determined using these studies are Molecular weight, number of hydrogen bond domars, hydrogen bond acceptors, Mlogp, whether the molecules obeys Lipinski rule of five or not and oral absorption. The atomic charges were determined using jaguar module of schrodinger.(Govindarajan et al.,)[1].\u003c/p\u003e\n\u003cp\u003eThe molecular of most of the drugs is below 500 mol\u003csup\u003e-1\u003c/sup\u003e except 2A7 \u0026amp; 13A7. \u0026nbsp;Number of hydrogen bond donar are less than five, number of hydrogen acceptors are less than 10 except 13A7. Mlogp is below 5. \u0026nbsp;All the compounds found to obey Lipinski rule of 5 except 13A7 as it has 2 violations. Metabolism rate is between 1-5 and the % of human oral availability is between 69 to 100%.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eTable-4 : \u003cem\u003eInsilico\u0026nbsp;\u003c/em\u003eADMET screening for selected analogs\u003c/u\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"655\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.229007633587786%\" valign=\"top\"\u003e\n \u003cp\u003eS.no\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003eM.W\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.076335877862595%\" valign=\"top\"\u003e\n \u003cp\u003edi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.992366412213741%\" valign=\"top\"\u003e\n \u003cp\u003eD.HB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.82442748091603%\" valign=\"top\"\u003e\n \u003cp\u003eA.HB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003eM plog o/w\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.244274809160306%\" valign=\"top\"\u003e\n \u003cp\u003eLipinski rule of 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003emetabolism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e% of oral absorption\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.229007633587786%\" valign=\"top\"\u003e\n \u003cp\u003e1A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e166.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.076335877862595%\" valign=\"top\"\u003e\n \u003cp\u003e1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.992366412213741%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.82442748091603%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e1.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.244274809160306%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e82%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.229007633587786%\" valign=\"top\"\u003e\n \u003cp\u003e2A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e558.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.076335877862595%\" valign=\"top\"\u003e\n \u003cp\u003e4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.992366412213741%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.82442748091603%\" valign=\"top\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e3.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.244274809160306%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e76%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.229007633587786%\" valign=\"top\"\u003e\n \u003cp\u003e3A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e166.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.076335877862595%\" valign=\"top\"\u003e\n \u003cp\u003e4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.992366412213741%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.82442748091603%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e2.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.244274809160306%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e88%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.229007633587786%\" valign=\"top\"\u003e\n \u003cp\u003e4A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e287.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.076335877862595%\" valign=\"top\"\u003e\n \u003cp\u003e5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.992366412213741%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.82442748091603%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.244274809160306%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e100%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.229007633587786%\" valign=\"top\"\u003e\n \u003cp\u003e5A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e418.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.076335877862595%\" valign=\"top\"\u003e\n \u003cp\u003e4.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.992366412213741%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.82442748091603%\" valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e3.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.244274809160306%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e100%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.229007633587786%\" valign=\"top\"\u003e\n \u003cp\u003e6A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e230.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.076335877862595%\" valign=\"top\"\u003e\n \u003cp\u003e7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.992366412213741%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.82442748091603%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e2.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.244274809160306%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e69%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.229007633587786%\" valign=\"top\"\u003e\n \u003cp\u003e7A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e425.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.076335877862595%\" valign=\"top\"\u003e\n \u003cp\u003e6.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.992366412213741%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.82442748091603%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e3.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.244274809160306%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e70%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.229007633587786%\" valign=\"top\"\u003e\n \u003cp\u003e8A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e263.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.076335877862595%\" valign=\"top\"\u003e\n \u003cp\u003e8.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.992366412213741%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.82442748091603%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e2.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.244274809160306%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e86%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.229007633587786%\" valign=\"top\"\u003e\n \u003cp\u003e9A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e359.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.076335877862595%\" valign=\"top\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.992366412213741%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.82442748091603%\" valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.244274809160306%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e90%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.229007633587786%\" valign=\"top\"\u003e\n \u003cp\u003e10A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e267.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.076335877862595%\" valign=\"top\"\u003e\n \u003cp\u003e9.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.992366412213741%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.82442748091603%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e1.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.244274809160306%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e94%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.229007633587786%\" valign=\"top\"\u003e\n \u003cp\u003e11A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e308.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.076335877862595%\" valign=\"top\"\u003e\n \u003cp\u003e3.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.992366412213741%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.82442748091603%\" valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.244274809160306%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e100%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.229007633587786%\" valign=\"top\"\u003e\n \u003cp\u003e12A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e206.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.076335877862595%\" valign=\"top\"\u003e\n \u003cp\u003e8.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.992366412213741%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.82442748091603%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e1.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.244274809160306%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e78%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.229007633587786%\" valign=\"top\"\u003e\n \u003cp\u003e13A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e676.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.076335877862595%\" valign=\"top\"\u003e\n \u003cp\u003e8.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.992366412213741%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.82442748091603%\" valign=\"top\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.244274809160306%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e84%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.229007633587786%\" valign=\"top\"\u003e\n \u003cp\u003e14A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e253.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.076335877862595%\" valign=\"top\"\u003e\n \u003cp\u003e3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.992366412213741%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.82442748091603%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.244274809160306%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e80%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.229007633587786%\" valign=\"top\"\u003e\n \u003cp\u003e15A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e137.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.076335877862595%\" valign=\"top\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.992366412213741%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.82442748091603%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e-0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.244274809160306%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e86%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.229007633587786%\" valign=\"top\"\u003e\n \u003cp\u003e16A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e476.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.076335877862595%\" valign=\"top\"\u003e\n \u003cp\u003e8.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.992366412213741%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.82442748091603%\" valign=\"top\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.244274809160306%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e84%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.229007633587786%\" valign=\"top\"\u003e\n \u003cp\u003e17A7\u003c/p\u003e\n \u003cp\u003e(STANDARD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e329.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.076335877862595%\" valign=\"top\"\u003e\n \u003cp\u003e2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.992366412213741%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.82442748091603%\" valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e3.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.244274809160306%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e88%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.229007633587786%\" valign=\"top\"\u003e\n \u003cp\u003e18A7\u003c/p\u003e\n \u003cp\u003e(STANDARD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e234.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.076335877862595%\" valign=\"top\"\u003e\n \u003cp\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.992366412213741%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.82442748091603%\" valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.16030534351145%\" valign=\"top\"\u003e\n \u003cp\u003e2.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.244274809160306%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.65648854961832%\" valign=\"top\"\u003e\n \u003cp\u003e88%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eMMGBSA studies :-\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBinding free energy calculations are assessed by MMGBSA approach. To determine binding free energy of receptor and ligand complex additionally energy minimization was done by MMGBSA prime modular mechanicsof schrodinger. The energy of particular complex was calculated using OPLS3 force field.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe ∆G bind = E\u003csub\u003erec\u003c/sub\u003e-E\u003csub\u003elig\u003c/sub\u003e-E\u003csub\u003ecom\u003c/sub\u003e\u003c/p\u003e\n\u003cp\u003eResults obtained from free energy calculations provide the information about bound and unbound states in ligand receptor complex.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The \u0026nbsp; results \u0026nbsp;of \u0026nbsp;MMGBSA \u0026nbsp; reveal that \u0026nbsp;the ∆G bind values were obtained in \u0026nbsp;the range of -7 to -40(SSRT) \u0026amp; -17 to -36(1KUV) for the selected \u0026nbsp;compounds and all other calculated properties are also contributing to the total free binding energy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eTable 5 :- MM-GBSA studies results (1kuv)\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"589\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.356536502546689%\" valign=\"top\"\u003e\n \u003cp\u003eS.no\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003eMMGBSA-( Bind)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003eMMGBSA-( Bind-coloumb)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003eMMGBSA-(Bind-covalent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.242784380305602%\" valign=\"top\"\u003e\n \u003cp\u003eMMGBSA- (Bind H bond)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.280135823429541%\" valign=\"top\"\u003e\n \u003cp\u003eMMGBSA-( Bind-Lipo)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003eMMGBSA- (Bind-vdW)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.356536502546689%\" valign=\"top\"\u003e\n \u003cp\u003e1A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-23.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e-3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e-2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.242784380305602%\" valign=\"top\"\u003e\n \u003cp\u003e-0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.280135823429541%\" valign=\"top\"\u003e\n \u003cp\u003e-8.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-32.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.356536502546689%\" valign=\"top\"\u003e\n \u003cp\u003e2A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-20.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e-10.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e-3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.242784380305602%\" valign=\"top\"\u003e\n \u003cp\u003e-1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.280135823429541%\" valign=\"top\"\u003e\n \u003cp\u003e-6.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-20.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.356536502546689%\" valign=\"top\"\u003e\n \u003cp\u003e3A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-20.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e-30.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.242784380305602%\" valign=\"top\"\u003e\n \u003cp\u003e-1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.280135823429541%\" valign=\"top\"\u003e\n \u003cp\u003e-13.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-20.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.356536502546689%\" valign=\"top\"\u003e\n \u003cp\u003e4A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-32.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e-28.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.242784380305602%\" valign=\"top\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.280135823429541%\" valign=\"top\"\u003e\n \u003cp\u003e-4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-21.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.356536502546689%\" valign=\"top\"\u003e\n \u003cp\u003e5A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-35.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e-19.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e7.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.242784380305602%\" valign=\"top\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.280135823429541%\" valign=\"top\"\u003e\n \u003cp\u003e-10.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-21.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.356536502546689%\" valign=\"top\"\u003e\n \u003cp\u003e6A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-33.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e-11.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e-4.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.242784380305602%\" valign=\"top\"\u003e\n \u003cp\u003e-0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.280135823429541%\" valign=\"top\"\u003e\n \u003cp\u003e-9.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-33.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.356536502546689%\" valign=\"top\"\u003e\n \u003cp\u003e7A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-35.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e-2.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e-8.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.242784380305602%\" valign=\"top\"\u003e\n \u003cp\u003e-1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.280135823429541%\" valign=\"top\"\u003e\n \u003cp\u003e-11.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-40.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.356536502546689%\" valign=\"top\"\u003e\n \u003cp\u003e8A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-42.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e23.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.242784380305602%\" valign=\"top\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.280135823429541%\" valign=\"top\"\u003e\n \u003cp\u003e-17.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-28.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.356536502546689%\" valign=\"top\"\u003e\n \u003cp\u003e9A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-30.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e7.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e-9.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.242784380305602%\" valign=\"top\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.280135823429541%\" valign=\"top\"\u003e\n \u003cp\u003e-7.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-31.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.356536502546689%\" valign=\"top\"\u003e\n \u003cp\u003e10A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-24.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e-6.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.242784380305602%\" valign=\"top\"\u003e\n \u003cp\u003e-0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.280135823429541%\" valign=\"top\"\u003e\n \u003cp\u003e-11.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-20.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.356536502546689%\" valign=\"top\"\u003e\n \u003cp\u003e11A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-19.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e-21.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e17.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.242784380305602%\" valign=\"top\"\u003e\n \u003cp\u003e-1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.280135823429541%\" valign=\"top\"\u003e\n \u003cp\u003e-12.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-36.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.356536502546689%\" valign=\"top\"\u003e\n \u003cp\u003e12A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-12.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e-3.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e-1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.242784380305602%\" valign=\"top\"\u003e\n \u003cp\u003e-1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.280135823429541%\" valign=\"top\"\u003e\n \u003cp\u003e-9.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-7.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.356536502546689%\" valign=\"top\"\u003e\n \u003cp\u003e13A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-38.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e-1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e-2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.242784380305602%\" valign=\"top\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.280135823429541%\" valign=\"top\"\u003e\n \u003cp\u003e-8.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-15.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.356536502546689%\" valign=\"top\"\u003e\n \u003cp\u003e14A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-11.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e-4.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.242784380305602%\" valign=\"top\"\u003e\n \u003cp\u003e-0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.280135823429541%\" valign=\"top\"\u003e\n \u003cp\u003e-5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-28.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.356536502546689%\" valign=\"top\"\u003e\n \u003cp\u003e15A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-20.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e-3.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e-5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.242784380305602%\" valign=\"top\"\u003e\n \u003cp\u003e-0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.280135823429541%\" valign=\"top\"\u003e\n \u003cp\u003e-11.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-22.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.356536502546689%\" valign=\"top\"\u003e\n \u003cp\u003e16A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-19.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e-21.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e17.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.242784380305602%\" valign=\"top\"\u003e\n \u003cp\u003e-1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.280135823429541%\" valign=\"top\"\u003e\n \u003cp\u003e-12.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-36.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.356536502546689%\" valign=\"top\"\u003e\n \u003cp\u003e17A7\u003c/p\u003e\n \u003cp\u003e(STANDARD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-24.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e-3.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.261460101867572%\" valign=\"top\"\u003e\n \u003cp\u003e-2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.242784380305602%\" valign=\"top\"\u003e\n \u003cp\u003e-0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.280135823429541%\" valign=\"top\"\u003e\n \u003cp\u003e-8.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.298811544991512%\" valign=\"top\"\u003e\n \u003cp\u003e-32.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eTable 6 :- MM-GBSA studies results (2Z5Y)\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"583\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.4631217838765%\" valign=\"top\"\u003e\n \u003cp\u003eS.no\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003eMMGBSA-( Bind)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003eMMGBSA-( Bind-coloumb)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003eMMGBSA-(Bind-covalent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.379073756432247%\" valign=\"top\"\u003e\n \u003cp\u003eMMGBSA- (Bind H bond)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003eMMGBSA-( Bind-Lipo)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003eMMGBSA- (Bind-vdW)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.4631217838765%\" valign=\"top\"\u003e\n \u003cp\u003e1A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-24.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-18.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-10.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.379073756432247%\" valign=\"top\"\u003e\n \u003cp\u003e-0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-10.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-28.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.4631217838765%\" valign=\"top\"\u003e\n \u003cp\u003e2A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-22.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-16.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-12.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.379073756432247%\" valign=\"top\"\u003e\n \u003cp\u003e-11.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-16.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-22.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.4631217838765%\" valign=\"top\"\u003e\n \u003cp\u003e3A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-26.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-33.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.379073756432247%\" valign=\"top\"\u003e\n \u003cp\u003e-11.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-18.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-24.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.4631217838765%\" valign=\"top\"\u003e\n \u003cp\u003e4A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-22.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-26.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e6.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.379073756432247%\" valign=\"top\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-14.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-26.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.4631217838765%\" valign=\"top\"\u003e\n \u003cp\u003e5A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-36.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-21.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e8.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.379073756432247%\" valign=\"top\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-12.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-22.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.4631217838765%\" valign=\"top\"\u003e\n \u003cp\u003e6A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-32.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-21.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-8.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.379073756432247%\" valign=\"top\"\u003e\n \u003cp\u003e-0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-19.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-32.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.4631217838765%\" valign=\"top\"\u003e\n \u003cp\u003e7A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-33.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-22.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-8.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.379073756432247%\" valign=\"top\"\u003e\n \u003cp\u003e-1.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-21.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-36.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.4631217838765%\" valign=\"top\"\u003e\n \u003cp\u003e8A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-28.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e23.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.379073756432247%\" valign=\"top\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-18.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-26.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.4631217838765%\" valign=\"top\"\u003e\n \u003cp\u003e9A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-28.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e11.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-8.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.379073756432247%\" valign=\"top\"\u003e\n \u003cp\u003e1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-17.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-33.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.4631217838765%\" valign=\"top\"\u003e\n \u003cp\u003e10A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-26.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-16.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e10.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.379073756432247%\" valign=\"top\"\u003e\n \u003cp\u003e-1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-14.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-26.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.4631217838765%\" valign=\"top\"\u003e\n \u003cp\u003e11A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-31.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-28.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e16.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.379073756432247%\" valign=\"top\"\u003e\n \u003cp\u003e-11.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-15.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-33.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.4631217838765%\" valign=\"top\"\u003e\n \u003cp\u003e12A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-18.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-6.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-10.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.379073756432247%\" valign=\"top\"\u003e\n \u003cp\u003e-12.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-18.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-17.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.4631217838765%\" valign=\"top\"\u003e\n \u003cp\u003e13A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-36.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-3.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-12.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.379073756432247%\" valign=\"top\"\u003e\n \u003cp\u003e10.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-18.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-18.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.4631217838765%\" valign=\"top\"\u003e\n \u003cp\u003e14A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-19.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-7.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e13.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.379073756432247%\" valign=\"top\"\u003e\n \u003cp\u003e-0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-15.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-26.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.4631217838765%\" valign=\"top\"\u003e\n \u003cp\u003e15A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-24.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-6.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-15.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.379073756432247%\" valign=\"top\"\u003e\n \u003cp\u003e-2.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-11.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-20.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.4631217838765%\" valign=\"top\"\u003e\n \u003cp\u003e16A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-18.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-6.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-10.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.379073756432247%\" valign=\"top\"\u003e\n \u003cp\u003e-12.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-18.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-17.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.4631217838765%\" valign=\"top\"\u003e\n \u003cp\u003e17A7\u003c/p\u003e\n \u003cp\u003e(STANDARD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-28.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-16.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-12.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.379073756432247%\" valign=\"top\"\u003e\n \u003cp\u003e-0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-10.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-28.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.4631217838765%\" valign=\"top\"\u003e\n \u003cp\u003e18A7\u003c/p\u003e\n \u003cp\u003e(STANDARD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-26.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-15.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-12.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.379073756432247%\" valign=\"top\"\u003e\n \u003cp\u003e-0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.408233276157805%\" valign=\"top\"\u003e\n \u003cp\u003e-11.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.46655231560892%\" valign=\"top\"\u003e\n \u003cp\u003e-26.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eMolecular dynamic simulation studies of best docked complex\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Glide score of drug complex 1A7/1KUV was \u0026nbsp;found to be highest among the selected drugs . the stsbility of the particular complex was determined using Desmond module of schrodinger software at 100ns MD (Guo et al.,)[2].\u003c/p\u003e\n\u003cp\u003eIn the process the complex was solvated using TIP3P(Jogensen et al.,)[3] at 10A\u003csup\u003e0\u003c/sup\u003e buffer region followed by deletion of overlapping water molecule \u0026amp; neutralization was done, constant temperature of 300K \u0026amp; pressure 1bar was maintained.(martyna et al.,)[4][5]. And futher RMSD \u0026amp; RMSF is observed during 100 ns finally interaction fraction of ligand with protein is also depicted.\u003c/p\u003e\n\u003cp\u003eThe RMSF (figure 4) was observed in the range of 0.8-2.48 A\u003csup\u003e0\u003c/sup\u003e . The radius of gyration (figure 7) was in the range of 3.6-3.75 A\u003csup\u003e0\u003c/sup\u003e. Molecular surface area is 264- 273 A\u003csup\u003e0\u003c/sup\u003e , Solvent accessibility surface area is 0-15 A\u003csup\u003e0\u003c/sup\u003e. Polar surface of ligands is 204-222 A\u003csup\u003e\u0026nbsp;\u003c/sup\u003erespectively.\u003c/p\u003e\n\u003cp\u003eThe 2-Dimensional interaction representation (figure 8) predicts the hydrogen bonding formed by ligand with MET 159 which is saved in molecular dynamic trajectory pose. The picture indicates that the OH group of 1A7 compound donate 90% of hydrogen bond to LEU 121, the NH\u003csub\u003e2\u003c/sub\u003e group of compound 1A7 donate 83% of hydrogen bond to HIS 122 and the carbonyl oxygen form 43% of hydrogen bond with MET 159 with water molecule in the complete simulation process.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003ePharmacological activity\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eAntidepressant activity\u0026nbsp;\u003c/u\u003e\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe randomly selected drugs were screened for antidepressant activity by force swim method [6][7] in mice (100mg/kg) by comparing with the standard drug paroxetine (20mg/kg). For the following study adult male mice (20\u0026plusmn;5g) were \u0026nbsp;selected and provided with free acess for food and water. The mice were grouped , in each group 6 were used and housed. Acute oral toxicity \u0026amp; LD50 is determined according to OECD guidelines.selected drugs (100mg/kg \u0026amp; paroxetine(20mg/kg) was suspended in tween80 of 0.5% and injected in to the mice through I.P route.\u003c/p\u003e\n\u003cp\u003eAfter 0.5 hr the mice is dropped in to the glass cylinder of diameter 12cm , height 30cm containing 25cm of water with the temperature 25\u0026plusmn;2\u003csup\u003e0\u003c/sup\u003eC approximately.\u003c/p\u003e\n\u003cp\u003eThe each mice was left for 6min and its immobility was observed when the mice leaves struggling \u0026amp; remains floating in the water with out any movement , \u0026amp; it is concluded as immobility. This immobility rate was determined for each mice.\u003c/p\u003e\n\u003cp\u003e% DID (decrease in immobility duration) was calculated using the following formula for test \u0026amp; standard.\u003c/p\u003e\n\u003cp\u003e%DID = [A-B/B]*100\u003c/p\u003e\n\u003cp\u003eA \u0026ndash; duration of immobility in test group.\u003c/p\u003e\n\u003cp\u003eB \u0026ndash; duration of immobility in control group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePharmacological screening\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe randomly selected drugs \u0026nbsp;from (1A7-16A7) were screened \u0026nbsp;for antidepressant activity using forced swim \u0026nbsp;method \u0026nbsp;in mice at a dose of 100 mg/kg by comparing with the standard drug Paroxetine and phenelzine (20 mg/kg). The mortality rate was not observed in the tested groups. There are no behavioural change observed in tested groups. The selected drugs were observed to be safe until 2000mg/kg of body weight. Firstly the dose dependent study was performed using various doses like 25mg/kg,50mg/kg,100mg/kg \u0026amp; 200mg/kg by intraperitonial route. From the results the maximum effective dose was determined. Antidepressant activity was \u0026nbsp;depicted \u0026nbsp;in the Table 7.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe standard drug \u0026nbsp;paroxetine decreased immobility to 67% at a dose level of 20 mg/kg. In our present research work \u0026nbsp;all the selected drugs have been shown nearer\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;immobility \u0026nbsp; when compared with the standard drug of paroxetine(20mg/kg). Among all the selected drugs 1A7 and 9A7 were found \u0026nbsp;potent, showing % reduction of \u0026nbsp;immobility rate at 61.0% \u0026nbsp;\u0026amp; 63.0% . At the same time, compounds 10A7 and 12A7 had moderate immobility reduction \u0026nbsp;activity of 49.1% \u0026amp; 46.3% \u0026nbsp;while compounds 6A7 and 7A7 had \u0026nbsp;poor immobility reduction activity of 28.4% \u0026amp; 25.9%.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFinally the drugs 1A7 and 9A7 \u0026nbsp;have been produced potent antidepressant activity \u0026nbsp;when compared with the standard drug paroxetine and phenelzine.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe immobility time of compound 1A7 and 9A7 (20 mg/kg, i.p.) and Paroxetine (20 mg/kg, i.p.) using forced swim method. (Values mentioned as mean \u0026plusmn; S.E.M. all the Values are significant \u0026nbsp;*P \u0026lt; 0.001, when compared with the control group.\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eTable :- 7 \u0026nbsp;Effect of randomly selected drugs in forced swim method\u0026nbsp;\u003c/u\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.77742946708464%\" valign=\"top\"\u003e\n \u003cp\u003eS.NO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.592476489028215%\" valign=\"top\"\u003e\n \u003cp\u003eSelected drugs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.79623824451411%\" valign=\"top\"\u003e\n \u003cp\u003eDOI\u003c/p\u003e\n \u003cp\u003e(mean \u0026plusmn;SEM)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.83385579937304%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;% DID\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.77742946708464%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.592476489028215%\" valign=\"top\"\u003e\n \u003cp\u003e1A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.79623824451411%\" valign=\"top\"\u003e\n \u003cp\u003e38.25 \u0026plusmn; 5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.83385579937304%\" valign=\"top\"\u003e\n \u003cp\u003e61.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.77742946708464%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.592476489028215%\" valign=\"top\"\u003e\n \u003cp\u003e4A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.79623824451411%\" valign=\"top\"\u003e\n \u003cp\u003e54.26 \u0026plusmn; 4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.83385579937304%\" valign=\"top\"\u003e\n \u003cp\u003e44.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.77742946708464%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.592476489028215%\" valign=\"top\"\u003e\n \u003cp\u003e6A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.79623824451411%\" valign=\"top\"\u003e\n \u003cp\u003e70.25 \u0026plusmn; 5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.83385579937304%\" valign=\"top\"\u003e\n \u003cp\u003e28.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.77742946708464%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.592476489028215%\" valign=\"top\"\u003e\n \u003cp\u003e7A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.79623824451411%\" valign=\"top\"\u003e\n \u003cp\u003e72.75 \u0026plusmn; 6.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.83385579937304%\" valign=\"top\"\u003e\n \u003cp\u003e25.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.77742946708464%\" valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.592476489028215%\" valign=\"top\"\u003e\n \u003cp\u003e9A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.79623824451411%\" valign=\"top\"\u003e\n \u003cp\u003e36.28 \u0026plusmn; 4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.83385579937304%\" valign=\"top\"\u003e\n \u003cp\u003e63.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.77742946708464%\" valign=\"top\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.592476489028215%\" valign=\"top\"\u003e\n \u003cp\u003e10A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.79623824451411%\" valign=\"top\"\u003e\n \u003cp\u003e50.00 \u0026plusmn; 4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.83385579937304%\" valign=\"top\"\u003e\n \u003cp\u003e49.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.77742946708464%\" valign=\"top\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.592476489028215%\" valign=\"top\"\u003e\n \u003cp\u003e12A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.79623824451411%\" valign=\"top\"\u003e\n \u003cp\u003e52.75 \u0026plusmn; 4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.83385579937304%\" valign=\"top\"\u003e\n \u003cp\u003e46.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.77742946708464%\" valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.592476489028215%\" valign=\"top\"\u003e\n \u003cp\u003e16A7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.79623824451411%\" valign=\"top\"\u003e\n \u003cp\u003e55.26 \u0026plusmn; 5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.83385579937304%\" valign=\"top\"\u003e\n \u003cp\u003e43.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.77742946708464%\" valign=\"top\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.592476489028215%\" valign=\"top\"\u003e\n \u003cp\u003econtrol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.79623824451411%\" valign=\"top\"\u003e\n \u003cp\u003e98.25 \u0026plusmn; 3.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.83385579937304%\" valign=\"top\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.77742946708464%\" valign=\"top\"\u003e\n \u003cp\u003eSTD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.592476489028215%\" valign=\"top\"\u003e\n \u003cp\u003eParoxetine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.79623824451411%\" valign=\"top\"\u003e\n \u003cp\u003e32.00 \u0026plusmn; 1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.83385579937304%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;67.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.77742946708464%\" valign=\"top\"\u003e\n \u003cp\u003eSTD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.592476489028215%\" valign=\"top\"\u003e\n \u003cp\u003ePhenelzine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.79623824451411%\" valign=\"top\"\u003e\n \u003cp\u003e30.00 \u0026plusmn; 1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.83385579937304%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;66.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe Data is analyzed using one-way ANOVA method using Dunnett\u0026rsquo;s test. \u003cem\u003en\u0026nbsp;\u003c/em\u003e= 6; at the dose ( 100 mg/kg). All the values were mentioned using mean \u0026plusmn; S.E.M.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, from the selected drugs 1A7-16A7, most of the drugs have potent binding affinity with the selected protein 1KUV \u0026amp; 2Z5Y . Molecular docking studies and MMGBSA studies were performed to determine the potent ligand which has best binding affinity with preferred protein of 1KUV \u0026amp; 2Z5Y Protein and to finally conclude them as potent \u0026nbsp;antidepressant agent. \u0026nbsp;Molecular Dynamic simulation studies \u0026nbsp;for the highest glide score drug of \u0026nbsp;1A7 which is \u0026nbsp;complexed \u0026nbsp;with protein 1KUV has been revealed \u0026nbsp;that the stability of ligand was achieved by forming \u0026nbsp; most stable hydrophobic interactions. The \u0026nbsp;results were also depicted by the modifications in the pharmacophoe features which have helped in improving the inhibitory activity. The drug 1A7 has been showed good activity using Invivo Force swim method .\u003c/p\u003e\n\u003cp\u003eAll the insilico \u0026nbsp;studies and invivo studies \u0026nbsp;in the present investigation helped us to repurpose the efficient drug molecules from the randomly selected drugs as potent Antidepressant agents. There was good correlation observed between InSilico and Invivo studies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cu\u003eAcknowledgement\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe authors like to express the gratitude to the management of Sri padmavati Mahila Visvavidyalayam, Institute of pharmaceutical sciences, Tirupati, Andrapradesh-517502,India\u0026nbsp;for providing the facilities required to complete the study project.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eConflict of interest\u0026nbsp;\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;There is no any conflict of interest, according to authors.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAuthors contribution\u0026nbsp;\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;All the authors have been contributed to the preparation of manuscript, participated in reviewing, editing, and the approved of the final draft for publication. The research profile of the authors can be verified from the ORCID ids, given below:\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Palupanuri \u0026nbsp;Naveena : https://orcid.org/0009-0007-2597-1822\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Swathi \u0026nbsp; Konda : https://orcid.org/0000-0002-3186-0543\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGovindarajan M, Periandy S, Carthigayen K. FT-IR and FT-Raman spectra, thermo dynamical behavior, HOMO and LUMO, UV, NLO properties, computed frequency estimation analysis and electronic structure calculations on \u0026alpha;-bromotoluene. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy. 2012 Nov 1;97:411-22.\u003c/li\u003e\n\u003cli\u003eGuo Z, Mohanty U, Noehre J, Sawyer TK, Sherman W, Krilov G. Probing the \u0026alpha;‐helical structural stability of stapled p53 peptides: molecular dynamics simulations and analysis. Chemical biology \u0026amp; drug design. 2010 Apr;75(4):348-59.\u003c/li\u003e\n\u003cli\u003eJorgensen WL, Chandrasekhar J, Madura JD, Impey RW, Klein ML. Comparison of simple potential functions for simulating liquid water. The Journal of chemical physics. 1983 Jul 15;79(2):926-35.\u003c/li\u003e\n\u003cli\u003eMartyna GJ, Klein ML, Tuckerman M. Nos\u0026eacute;\u0026ndash;Hoover chains: The canonical ensemble via continuous dynamics. The Journal of chemical physics. 1992 Aug 15;97(4):2635-43.\u003c/li\u003e\n\u003cli\u003eMartyna GJ, Tobias DJ, Klein ML. Constant pressure molecular dynamics algorithms. The Journal of chemical physics. 1994 Sep 1;101(5):4177-89.\u003c/li\u003e\n\u003cli\u003ePorsolt RD, Anton G, Blavet N, Jalfre M. Behavioural despair in rats: a new model sensitive to antidepressant treatments. European journal of pharmacology. 1978 Feb 15;47(4):379-91.\u003c/li\u003e\n\u003cli\u003eSchechter LE, Ring RH, Beyer CE, Hughes ZA, Khawaja X, Malberg JE, Rosenzweig-Lipson S. Innovative approaches for the development of antidepressant drugs: current and future strategies. NeuroRx. 2005 Oct 1;2(4):590-611.\u003c/li\u003e\n\u003cli\u003eMadhavi Sastry G, Adzhigirey M, Day T, Annabhimoju R, Sherman W. Protein and ligand preparation: parameters, protocols, and influence on virtual screening enrichments. Journal of computer-aided molecular design. 2013 Mar;27:221-34.\u003c/li\u003e\n\u003cli\u003eJacobson MP, Pincus DL, Rapp CS, Day TJ, Honig B, Shaw DE, Friesner RA. A hierarchical approach to all‐atom protein loop prediction. Proteins: Structure, Function, and Bioinformatics. 2004 May 1;55(2):351-67.\u003c/li\u003e\n\u003cli\u003eFriesner RA, Murphy RB, Repasky MP, Frye LL, Greenwood JR, Halgren TA, Sanschagrin PC, Mainz DT. Extra precision glide: Docking and scoring incorporating a model of hydrophobic enclosure for protein\u0026minus; ligand complexes. Journal of medicinal chemistry. 2006 Oct 19;49(21):6177-96.\u003c/li\u003e\n\u003cli\u003eLi J, Abel R, Zhu K, Cao Y, Zhao S, Friesner RA. The VSGB 2.0 model: a next generation energy model for high resolution protein structure modeling. Proteins: Structure, Function, and Bioinformatics. 2011 Oct;79(10):2794-812.\u003c/li\u003e\n\u003cli\u003eL, Zheng S, Chen B, Butte AJ, Swamidass SJ, Lu Z. A survey of current trends in computational drug repositioning. Briefings in bioinformatics. 2016 Jan 1;17(1):2-12.i J\u003c/li\u003e\n\u003cli\u003eMohammad Sadeghi H, Adeli I, Mousavi T, Daniali M, Nikfar S, Abdollahi M. Drug repurposing for the management of depression: where do we stand currently?. Life. 2021 Jul 30;11(8):774.\u003c/li\u003e\n\u003cli\u003eVatansever S, Schlessinger A, Wacker D, Kaniskan H\u0026Uuml;, Jin J, Zhou MM, Zhang B. Artificial intelligence and machine learning‐aided drug discovery in central nervous system diseases: State‐of‐the‐arts and future directions. Medicinal research reviews. 2021 May;41(3):1427-73.\u003c/li\u003e\n\u003cli\u003eMichał Antoszczak\u003csup\u003e1\u003c/sup\u003e, Anna Markowska\u003csup\u003e2\u003c/sup\u003e, Janina Markowska\u003csup\u003e3\u003c/sup\u003e and Adam Huczyński\u003csup\u003e1. \u003c/sup\u003eAntidepressants and Antipsychotic Agents as Repurposable Oncological Drug Candidates\u003cstrong\u003e. \u003c/strong\u003eCurrent medicinal chemistry,2020,27,1-38.\u003c/li\u003e\n\u003cli\u003eMohammad Elsaed Ebada . Drug repurposing may generate novel approaches to treating depression.journal of pharmacy and pharmacology,69(2017),pp 1428-1436\u003c/li\u003e\n\u003cli\u003eSo HC, Chau CK, Chiu WT, Ho KS, Lo CP, Yim SH, Sham PC. When GWAS meets the Connectivity Map: drug repositioning for seven psychiatric disorders. bioRxiv. 2016 Dec 23:096503.\u003c/li\u003e\n\u003cli\u003eManepalli S, Surratt CK, Madura JD, Nolan TL. Monoamine transporter structure, function, dynamics, and drug discovery: a computational perspective. The AAPS journal. 2012 Dec;14:820-31.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-computer-aided-molecular-design","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jcam","sideBox":"Learn more about [Journal of Computer-Aided Molecular Design](http://link.springer.com/journal/10822)","snPcode":"10822","submissionUrl":"https://submission.nature.com/new-submission/10822/3","title":"Journal of Computer-Aided Molecular Design","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Antidepressant, Insilico studies, Docking, ADMET, MMGBSA, Simulation studies, Invivo studies.","lastPublishedDoi":"10.21203/rs.3.rs-4686166/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4686166/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDrug repositioning is also known as drug repurposing, drug refilling. Drug repositioning is one of the most preferred field in current research. The drugs with different adverse effect and the drugs which are shelved can be used for the treatment of other diseases. Thus it helps in finding new therapeutic index for already existing drugs. The main advantage of this drug reposioning is it decreases the investment in drug discovery and optimization, and all the pharmacokinetics studies will be readily available as their profiles are already established. In recent times one of the most useful strategies for repositioning the drug of the therapeutic activity towards other new target is done by computational screening.\u003c/p\u003e \u003cp\u003eThe deeper knowledge about pathogenesis of depression helps us to develop or discover the new drug moieties through drug repositioning to treat the disease condition of depression. In this study we have selected randomly some available drugs and repurposed them as potent anti depressant agents using Insilico and Invivo studies.\u003c/p\u003e","manuscriptTitle":"Repositioning randomly selected Drugs as Antidepressants by computational and Invivo methods","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-30 07:05:52","doi":"10.21203/rs.3.rs-4686166/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorAssigned","content":"","date":"2024-07-06T07:28:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-05T14:09:59+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Computer-Aided Molecular Design","date":"2024-07-04T11:14:36+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-computer-aided-molecular-design","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jcam","sideBox":"Learn more about [Journal of Computer-Aided Molecular Design](http://link.springer.com/journal/10822)","snPcode":"10822","submissionUrl":"https://submission.nature.com/new-submission/10822/3","title":"Journal of Computer-Aided Molecular Design","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"6c36c4b8-4285-4ae1-ace8-b323d2212810","owner":[],"postedDate":"July 30th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-07-30T07:05:53+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-30 07:05:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4686166","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4686166","identity":"rs-4686166","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}