Identification of novel inhibitors from Urtica spp against MDAMB-231 targeting JAK 2 receptor for breast cancer therapy

Identification of novel inhibitors from Urtica spp against MDAMB-231 targeting JAK 2 receptor for breast cancer therapy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Identification of novel inhibitors from Urtica spp against MDAMB-231 targeting JAK 2 receptor for breast cancer therapy Shobha Upreti, Kartik Muduli, Jagannath Pradhan, Selvakumar Elangovan, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3000935/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 08 Oct, 2023 Read the published version in Medical Oncology → Version 1 posted 4 You are reading this latest preprint version Abstract Breast cancer is the most prevalent form of cancer in women globally, and MDA-MB-231 or TNBC (Triple-negative breast cancer) is its aggressive type since it lacks the usual targets. JAK2/STAT3 pathway can be an important lead in anticancer drug discovery, as restraining the downstream signalling of this pathway results in the induction of cell apoptosis. Moreover, various limitations associated with chemotherapy are the reason to find an alternative herbal-based therapy. For this study, we collected Urtica dioica , and U. parviflora from different regions of Uttarakhand, followed by preparation of their leaf and stem extracts in different solvents. The GC-MS analysis of these extracts revealed a total of 173 compounds to be present in them. Further, by molecular docking approach, we studied the interaction between these compounds and JAK2, and 12 major compounds with better binding energy than the control Paclitaxel were identified. In addition, the selected hits were also reported to display better pharmacokinetic properties. The anticancer potential of these extracts was also evaluated by in vitro approach in the MDA-MB-231 cell line, and both extracts displayed significant anticancer activity. Hence, the findings in our study can be crucial in the area of herbal-based target-specific drug development against breast cancer. Triple-negative breast cancer Molecular docking Pharmacokinetic studies IC50 Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Cancer is undoubtedly one of the major causes of mortality all around the globe, the growing burden of cancer is a matter of concern for the international health community to search for novel alternative treatments [ 1 ]. Recently, WHO estimated around 10 million deaths in the year 2020, and breast cancer is a leading cause of death accounting for around 2.26 million cases [ 2 ]. Even in the countries like the US where health facility is quite advanced the annual mortality cases from this particular cancer is high. Women are more likely than men to get breast cancer, among them triple-negative breast cancer (TNBC) accounts for 15–20% of all the cases. Since these cells lack the major receptors (oestrogen, progesterone, HER2) that are targeted in chemotherapy, optimizing therapeutic management in them is challenging [ 3 ]. Moreover, a Poor prognosis of TNBC lowers the overall survival rates of the patients [ 4 ]. Patients with TNBC are often treated with conventional adjuvant chemotherapy, which does not have sufficient curative effects, since it lacks specificity, thus there is a setback in proper treatment for these patients [ 3 ]. Hence, the discovery of target-specific therapeutic agents is necessary. JAK2/STAT3 pathway can be an important target in the development of treatment against TNBC [ 5 ]. The downstream signalling of this pathway is responsible for the transcription of their target genes, leading to cell survival, proliferation, differentiation and angiogenesis [ 6 , 7 ]. JAK2/STAT3 signalling is constitutively expressed in the breast cancer cell line [ 8 ]. Hence, restraining the downstream signalling of this pathway in breast cancer has been reported to lower cell viability, invasion, and migration while also causing cell death [ 9 , 10 ]. Moreover, the increasing rates of drug resistance and extreme side effects associated with synthetic drugs are the reasons to find an alternative treatment [ 11 ]. Herbal-based compounds, due to the least side effects [ 12 , 13 ]can be employed in the treatment of TNBC via targeting the JAK2 receptor. Urtica , a plant of the Uttarakhand Himalayan with potential anticancer and antiviral properties [ 14 – 17 ], can be exploited to develop treatment regimens for TNBC. Hence, moving in this direction, we collected two species of Urtica ( U. dioica , and U. parviflora ) from different regions of Uttarakhand, followed by preparation of its leaf and stem extracts in polar (ethanol), mid-polar (chloroform), and non-polar (hexane) solvents utilizing the Soxhlet extraction technique. The extracts were DLEE (Dioica leaf ethanol extract), DSEE (Dioica stem ethanol extract), DLCE (Dioica leaf chloroform extract), DSCE (Dioica stem chloroform extract), DLHE (Dioica leaf hexane extract), DSHE (Dioica stem hexane extract), PLEE (Parviflora leaf ethanol extract), PSEE (Parviflora stem ethanol extract), PLCE (Parviflora leaf chloroform extract), PSCE (Parviflora stem chloroform extract), PLHE (Parviflora leaf hexane extract), and PSHE (Parviflora stem hexane extract). The GC-MS analysis of these extracts revealed a total of 173 compounds to be present in them. Further, by the molecular docking approach, the compounds were studied for their interaction with JAK2, and around 12 compounds were reported to display better binding energy than the control Paclitaxel. The selected hits were then subjected to the ADMET and drug-likeness studies. It was observed that the selected hits demonstrated substantial pharmacokinetic properties. The prepared extracts were also evaluated by invitro studies against the MDA-MB-231 cell line, and interestingly it was observed that PLCE, PLHE, DSEE, PSHE, DLHE, PSCE, DLEE, DSHE, PSEE, DLCE, DSCE, PLEE displayed significant anticancer activity. Therefore, the strategy involved in our study will be helpful to understand the action mechanism of these herbal compounds, targeting JAK2 in TNBC. Moreover, the findings from this study could help to improve the future drug discovery process to treat breast cancer. 2. Materials and Methods 2.1. Plant collection We collected the stem and leaf of U. dioica and U. parviflora from two different altitudes of Uttarakhand i.e. Almora Khatyari (Latitude = 29.5945° N, and Longitude = 79.6474° E ), and Almora, Jageshwar (latitude- 29.6384° N, longitude- 79.8528° E) respectively. A voucher [Accession numbers − 22903(RKT), and 25808 (RKT) were obtained for U. dioica , and U. parviflora , respectively] has been deposited at the Herbarium of Regional Ayurveda Research Institute, Ranikhet, Almora, Uttarakhand, India. 2.2 Drying and extraction Healthy plants of U . dioica and U. parviflora were selected for collection and extraction purposes. 2.2.1 Initial preparation Collected plants were washed thoroughly with water, and then with distilled water to remove dust and other contaminants from the leaves and stem. Later these leaves and stems were sliced into small pieces and kept in the shade for drying until the moisture was eliminated, followed by grinding of this material into homogenous powder. 2.2.2 Soxhlet extraction The Soxhlet extraction technique constitutes a thimble that was filled with the powder, followed by its insertion into the Soxhlet apparatus (Borosil). The extraction was carried out by using polar (ethanol), mid-polar (chloroform), and non-polar (hexane) solvents. Each extraction was carried out for 9–10 hours at a temperature of 60–65°C. A rotary evaporator operating at 40°C was then used to remove the excess solvent. Further, the percent yield value was calculated for all the prepared extracts. The dried extracts were then utilized for phytochemical screening and were also evaluated for their anticancer potential. 2.3. Chemical profiling The phytochemicals present in the respective solvents were then identified by utilizing the GC-MS technique. The analysis was done at the AIRF (Advanced instrumental research facility), JNU (Jawahar Lal Nehru University), New Delhi. 2.4. Target protein selection and preparation The crystal structure of the human JAK-2 was retrieved from the RCSB (Research Collaboratory for Structural Bioinformatics) in PDB format. The protein had a resolution of 1.80 Å. Using Pymol [ 18 ] the ligand was isolated from the respective PDB structure, followed by the removal of water molecules [ 18 ]. This receptor structure was then uploaded into PyRx, where it was subjected to energy minimization and was further converted to PDBQT format for analysis. 2.5. Ligands preparation All the phytochemicals or ligands were obtained from the PubChem database in sdf format (URL: https://pubchem.ncbi.nlm.nih.gov ). Further by utilizing Open Babel 3.1.1 software, these ligands were converted from their SDF format to the PDB format for further virtual screening. Before testing the potentiality of the Urtica dioca and Urtica parviflora compounds against JAK 2(PDB ID: 3krr) a broad-spectrum anti-cancerous drug i.e., Paclitaxel with PubChem CID- 36314 was also used as a control. 2.6. Molecular docking Molecular docking was performed by utilizing the PyRx virtual screening tool, which uses the auto dock wizard for docking [ 19 ]. All the docking calculations utilized LGA (Lamarckian genetic algorithm) technique, and the exhaustiveness score for these calculations was set to 8. Moreover, a grid box large enough to cover the active site with the following dimensions: centre (X, Y, Z): (15.4960, 12.6684, 1.4063) Å and size: (X, Y, Z): (25.6943, 22.8757, 21.2828). The binding affinity and the RMSD (root mean square deviation) value were utilized to find the favourable binding. Lastly, the top 12 hit compounds were selected based on their higher binding affinity. The compounds displaying an RMSD value less than 1.0 Å were employed for observing the favourable binding. The ligand molecules were docked automatically to the active site of the receptor protein, and the conformers with the highest binding affinity were selected for the post-docking analysis. The selected hits were finally visualized utilizing the Discovery Studio visualizer 3.0. 2.7. Drug-likeness and in silico ADMET prediction ADMET analysis is crucial at an early phase of drug development. The pharmacokinetic profile viz., absorption, distribution, metabolism, and excretion. Lipinski’s rule of five is crucial for determining the drug-likeness of the identified compounds. According to the rule of five, there should be only 5 hydrogen bond donors, and 10 hydrogen bond acceptors, a partition coefficient of no more than 5, a polar surface area (PSA) of no more than 140 Å 2 and a molecular weight of no more than 500 Da [ 20 ]. To make our study time and cost-effective Lipinski’s rule of five was applied to analyze the pharmacokinetics of the twelve identified hits. The candidate hits from the virtual screening were further employed for ADMET analysis. These candidate hits, along with the control, Paclitaxel was evaluated for different parameters viz., drug-likeness, physiochemical properties, pharmacokinetics, and toxicity. SwissADME was employed for ADME analysis [ 21 ], Protox II, for toxicity and median lethal dose (LD50) prediction [ 22 ], and pkCSM, for ADMET parameters of compounds [ 23 ]. 2.8. Cell culture and cell viability assay MDA-MB-231 breast cancer cell lines were purchased from the National Centre for Cell Science (NCCS), Pune, India. MDA-MB-231 cells were grown in L15 media with 10% FBS (fetal bovine serum), 100 IU/ml penicillin, 100 g/ml streptomycin, and 0.25 µg/ml amphotericin B at 37°C in a humid incubator with 5% CO 2 . Cell viability assay was performed, and 1x10 4 MDA-MB-231 cells were seeded per well in 96-well plates. After 24 hours of incubation in a 5% CO 2 incubator at 37°C, the cells were treated with different concentrations (10µg/ml, 50 µg/ml, 100 µg/ml and 200 µg/ml) of the prepared extracts. MTT assay was performed as described earlier [ 24 ], in brief after 48 hours of incubation, 20 µL of the MTT (MP Biomedicals, USA) stock solution (5mg/ml) was added to each well, followed by additional 4 hours of incubation. After which, 100µl of the solubilizing buffer was added to each well to dissolve the formazan crystals. The absorbance was taken at 570 nm wavelength using an Elisa reader (Epoch, Biotek, USA). Further, the percentage inhibition was calculated by comparing the percentage of viability with the untreated control. The experiment was performed in triplicates to verify the results. Paclitaxel was taken as a positive control. 2.9. Statistical Analysis. The experiments were performed in triplicates, and compiled as mean ± SD. Further analysis of the results was done by one-way ANOVA, and Dunnett’s post-test was applied. GraphPad Prism (version 9) software, was utilized for all the analysis. 3. Result 3.1. Yield leaves and stem extract yield were calculated in three different solvents i.e., hexane, chloroform and ethanol. The percent yield is presented in Table 1 . Table 1 percentage yield of different extracts from Urtica spp. Plants Solvent Sample Weight (g) Yield (g) % Yield Urtica dioica Ethanol Leave 81 13.19 16.19 Stem 81 13.19 16.19 Chloroform Leave 81 13.35 16.4 Stem 81 5.60 6.88 Hexane Leave 81 8.57 10.52 Stem 81 5.93 7.29 Urtica parviflora Ethanol Leave 81 7.91 9.72 Stem 81 9.39 11.54 Chloroform Leave 81 8.40 10.32 Stem 81 4.78 5.87 Hexane Leave 81 7.91 9.72 Stem 81 4.78 5.87 3.2. Chemical profiling The phytoconstituent were evaluated and identified by comparing their mass spectra. NIST-MS and WILEY library were utilized to compare molecular weight, peak retention time, and molecular formula of the identified compounds to that of the already known compounds. The gas chromatogram of each sample is presented in Supplementary Fig. 1. The major phytoconstituents obtained from the GCMS analysis are presented in Supplementary Table 1. 3.3. Molecular docking In the current study, we have employed the molecular docking approach to calculate the binding energy of the docked structure. Th e c ompounds, 14-Methylcholesta-2,8-dien-6-yl acetate (-8.6 Kcal/mol), Stigmasta-4,7,22-trien-3. alpha.-ol (-8.6 Kcal/mol), 2-(p-Chlorobenzyl)-1-(2-diethylaminoethyl)-5-nitrobenzimidazole (-8.4 Kcal/mol), Stigmasta-5,22-dien-3. beta. -ol, acetate (-8.3 Kcal/mol), Stigmasta-3,5-diene (-8.0 Kcal/mol), etc., had better binding energy than the control Paclitaxel (-7.1 Kcal/mol), the chemical structure of the top 12 hit compounds have been depicted in Fig. 1 . Molecular docking interaction analysis revealed that all the top 12 hits showed binding interaction patterns with various catalytic site residues like LEU983, LEU855, VAL863, ARG980, VAL863, ALA880, LEU855, LEU932, in the binding pocket of JAK 2 (Table 2 ) . Moreover, the selected hits showed H-bond with amino acids GLY 856, ARG980, ASN981, and ASP994 of JAK2. The protein-ligand interactions, with control and the hits, have been displayed in Fig. 2 , and Fig. 3 , respectively. Overall, in comparison to the control, the selected hits had favourable interactions that proves them to be potent modulators of JAK2. Table 2 Binding interaction of top twelve selected hits with active site amino acid residues of JAK2 S.No. Compound Name Binding Energy Kcal/mol rmsd/ub rmsd/lb Interactive residues Hydrogen Bonds 1 14-Methylcholesta-2,8-dien-6-yl acetate -8.6 0 0 LEU983, LEU855, VAL863, ARG980 GLY 856 2 Stigmasta-4,7,22-trien-3. alpha.-ol -8.6 0 0 LEU855, LEU983, VAL863, ARG980 -- 3 2-(p-Chlorobenzyl)-1-(2-diethylaminoethyl)-5-nitrobenzimidazole -8.4 0 0 VAL863, ALA880, LEU855, LEU932, LEU983 ARG980, ASN981, ASP994 4 Stigmasta-5,22-dien-3. beta. -ol, acetate -8.3 0 0 VAL1110, PTR1007, LYS1030 - 5 Stigmasta-3,5-diene -8 0 0 LYS1030, VAL1110, ALA1034, VAL1033 - 6 Oxalic acid, 3,5-difluorophenyl undecyl ester -7.7 0 0 ARG1117 ALA1034, VAL1033, SER1032, GLU1006 7 ERGOST-5-EN-3-OL -7.6 0 0 ALA880, LEU855, VAL863, LEU983 ASP994 8 XANTHOSINE -7.6 0 0 - THR875, ARG867 9 alpha-Tocospiro-B -7.4 0 0 PHE1019, PRO1058, PRO1017 ARG980, SER936 10 Vitamin E -7.2 0 0 ALA880, LEU855, VAL863, LEU983 GLY856 11 Diazoprogesterone -7.1 0 0 PRO1058 ASN 981, ASP976 12 . BETA. -SITOSTEROL -7.1 0 0 LEU1026 SER1029 PRO1013 VAL1075 PHE1076 ILE1079 Control Paclitaxel -7.1 0 0 VAL 1033 SER1115 ARG971 3.4. Prediction of ADMET properties The development of an effective drug depends on pharmacokinetic factors such as absorption, distribution, metabolism, and excretion. ADME prediction is an important component of pre-clinical drug research since it lowers the likelihood that the compounds with a better pharmacokinetic profile would fall through the clinical trials. Selected 12 hits were examined for their pharmacological, pharmacokinetic, drug-like, and toxicological characteristics. The anticipated pharmacological parameters for a subset of 12 hits as well as the control are described in Table 3 (A, B, and C) . The data makes it evident that the hits that were chosen displayed pharmacological characteristics that were in a favourable range, thus these compounds can act as a potential drug candidate against TNBC. All the 12 hits fulfilled Lipinski's five-hit guideline. The consensus Log Po/w ranges from 3.34 to 8.27, which represents the good lipophilicity behaviour that all of the hits exhibited. These hits demonstrated synthetic accessibility in the range of 3.09 to 6.88. All the compounds except 2-(p-Chlorobenzyl)-1-(2-diethylaminoethyl)-5-nitrobenzimidazole exhibited high intestinal absorption and bioavailability. Moreover, the capacity of each hit to interact with the different isomers of cytochrome P450 varied. The cytochrome P450 isoenzymes interacted somewhat with the top hits, thus demonstrating their better effectiveness in biotransformation with less toxicity. Almost all of the hits had Caco-2 (colon cancer cell line) permeability values greater than 0.90. The overall clearance rate of the chosen hits was between 0.307 to 1.589. The toxicity study of the hits indicates little to no harmful effects. A range of low to high maximum tolerated dosages are shown by each hit. Overall, the ADMET study indicates that the compounds employed in our study could be helpful in the development of safer anticancer drugs. Table 3: Pharmacological parameters for a subset of 12 hits as well as the control Table 3 A: Physiochemical, Drug likeness, and Medicinal chemistry prediction of control and selected hits using SwissADME Molecule Formula MW (g/mol) Rotatable bonds H-bond acceptors H-bond donors TPSA (Å 2 ) Consensus Log P ESOL Log S ESOL Class (Water solubility) Drug likeness (Lipinski violations) Medicinal Chemistry (Synthetic Accessibility) 1. C30H48O2 440.7 7 2 0 26.3 7.26 -7.7 Poorly soluble 1 6.1 2. C29H46O 410.67 5 1 1 20.23 6.71 -6.95 Poorly soluble 1 6.19 3. C20H23ClN4O2 386.88 8 4 0 66.88 3.56 -4.99 Moderately soluble 0 3.09 4. C31H50O2 454.73 7 2 0 26.3 7.38 -7.95 Poorly soluble 1 6.25 5. C29H48 396.69 6 0 0 0 7.95 -8.56 Poorly soluble 1 6.61 6. C19H26F2O4 356.4 14 6 0 52.6 5.62 -5.84 Moderately soluble 1 3.12 7. C28H48O 400.68 5 1 1 20.23 6.9 -7.54 Poorly soluble 1 6.17 8. C10H12N4O6 284.23 2 7 5 153.46 -1.92 -0.32 Very soluble 0 3.84 9. C29H50O4 462.7 13 4 1 63.6 6.37 -6.53 Poorly soluble 0 6.88 10. C29H50O2 430.71 12 2 1 29.46 8.27 -8.6 Poorly soluble 1 5.17 11. C21H28N2O2 340.46 2 4 0 71.53 3.34 -4.28 Moderately soluble 0 5.06 12. C29H50O 414.71 6 1 1 20.23 7.19 -7.9 Poorly soluble 1 6.3 Paclitaxel C47H51NO14 853.91 15 14 4 221.29 3.58 -6.66 Poorly soluble 2 8.34 MW: Molecular weight; HBA.: Hydrogen Bond Acceptor; HBD: Hydrogen Bond Donor; TPSA: Topological polar surface area. Table 3 B: ADMET prediction of control and selected hits using pkCSM. S.No. Caco2 permeability (log Papp in 10–6 cm/s) Intestinal absorption (human) (% Absorbed) P-glycoprotein substrate VDss (human) (log L/ kg) Fraction unbound (human) CYP2D6 substrate CYP3A4 substrate CYP1A2 inhibitor CYP2C19 inhibitor CYP2C9 inhibitor CYP2D6 inhibitor CYP3A4 inhibitor Total Clearance (log ml/min/ kg) Renal OCT2 substrate 1. 1.205 95.458 No 0.502 0 No Yes No No No No No 0.48 No 2. 1.219 95.604 No 0.181 0 No Yes No No No No No 0.622 No 3. 0.339 84.421 Yes 1.371 0.049 No Yes Yes Yes Yes Yes Yes 0.757 Yes 4. 1.203 97.083 No 0.051 0 No Yes No No No No No 0.539 No 5. 1.227 96.148 No 0.391 0 No Yes No No No No No 0.63 No 6. 1.29 91.491 No -0.103 0 No Yes No No No No No 1.589 No 7. 1.223 94.543 No 0.427 0 No Yes No No No No No 0.572 No 8. 0.192 44.839 No -0.02 0.914 No No No No No No No 0.594 No 9. 0.613 92.612 No -0.013 0 No Yes No No No No No 0.936 Yes 10. 1.345 89.782 No 0.709 0 No Yes No Yes No No No 0.794 No 11. 0.662 97.088 No -0.034 0.177 No Yes No No No No No 0.307 No 12. 1.201 94.464 No 0.193 0 No Yes No No No No No 0.628 No Paclitaxel 0.623 100 Yes 1.458 0 No Yes No No No No Yes -0.36 No Table 3 B: ADMET prediction of control and selected hits using pkCSM. S.No. Caco2 permeability (log Papp in 10–6 cm/s) Intestinal absorption (human) (% Absorbed) P-glycoprotein substrate VDss (human) (log L/ kg) Fraction unbound (human) CYP2D6 substrate CYP3A4 substrate CYP1A2 inhibitor CYP2C19 inhibitor CYP2C9 inhibitor CYP2D6 inhibitor CYP3A4 inhibitor Total Clearance (log ml/min/ kg) Renal OCT2 substrate 13. 1.205 95.458 No 0.502 0 No Yes No No No No No 0.48 No 14. 1.219 95.604 No 0.181 0 No Yes No No No No No 0.622 No 15. 0.339 84.421 Yes 1.371 0.049 No Yes Yes Yes Yes Yes Yes 0.757 Yes 16. 1.203 97.083 No 0.051 0 No Yes No No No No No 0.539 No 17. 1.227 96.148 No 0.391 0 No Yes No No No No No 0.63 No 18. 1.29 91.491 No -0.103 0 No Yes No No No No No 1.589 No 19. 1.223 94.543 No 0.427 0 No Yes No No No No No 0.572 No 20. 0.192 44.839 No -0.02 0.914 No No No No No No No 0.594 No 21. 0.613 92.612 No -0.013 0 No Yes No No No No No 0.936 Yes 22. 1.345 89.782 No 0.709 0 No Yes No Yes No No No 0.794 No 23. 0.662 97.088 No -0.034 0.177 No Yes No No No No No 0.307 No 24. 1.201 94.464 No 0.193 0 No Yes No No No No No 0.628 No Paclitaxel 0.623 100 Yes 1.458 0 No Yes No No No No Yes -0.36 No 3.5. Invitro anticancer activity The prepared extracts were also evaluated for their effect on MDA-MB-231 cells. The anticancer activity of different extracts was represented by the IC 50 values, viz., DLEE (118.07 ± 12.21 µg/ml), DSEE (99.13 ± 3.04 µg/ml), DLCE (168.89 ± 12.20 µg/ml), DSCE (172.16 ± 2.25 µg/ml), DLHE (105.62 ± 9.16 µg/ml), DSHE (125.55 ± 13.14 µg/ml), PLEE (170.84 ± 26.67 µg/ml), PSEE (129.56 ± 14.33 µg/ml), PLCE (90.09 ± 2.37 µg/ml), PSCE (113.47 ± 2.98 µg/ml), PLHE (99.14 ± 2.56 µg/ml), PSHE (105.63 ± 6.77 µg/ml), and was significantly higher (P < 0.05) in comparison to the untreated cells. IC 50 ± SD values of U. dioica, and U. parviflora extracts have been depicted in Fig. 4 and Fig. 5 , respectively. 4. Discussion TNBC is the most fatal form of breast cancer in women worldwide, since the three major targets of chemotherapy viz., Estrogen, Progesterone, and HER-2 receptors are not present in these cancer cells [ 25 ]. The increasing rates of drug resistance and extreme side effects associated with synthetic drugs are the main reasons to discontinue chemotherapy [ 11 ]. Thus, finding an alternative form of treatment is of utmost importance. Uttarakhand Himalaya has been known to be affluent in traditional plants that have been reported to be effective against a range of human diseases [ 14 – 17 ]. Herbs like Urtica or Stinging nettle are among the most common, multi-purpose plants that have not been exploited to their full potential yet. However, these plants of Uttarakhand Himalaya are still underestimated and unexplored plants, particularly in herbal medicine. JAK2/STAT3 pathway can be an important lead in the development of anticancer therapy in triple-negative breast cancer [ 5 ]. The binding of the cytokines (IL-6 family, leptin, and erythropoietin), hormones like prolactin, and growth factors like epidermal growth factor (EGF), to the extracellular domain of the tyrosine kinase associated receptor, causes dimerization of the JAK2 associated subunits, thus bringing these subunits together [ 26 ]. This induces cross-phosphorylation by JAK2 on the tyrosine residue, a process known as autophosphorylation, thus activating their kinase domain. It has been reported that tyrosine 221 and 570, which are conserved in Humans and these JAK2's equivalent tyrosines are not present in JAK1, JAK3, or TYK2, therefore phosphorylation of these tyrosines may start JAK2-specific processes [ 27 ]. The activated kinase subsequently phosphorylates the tyrosine residues on the intracellular domains of the receptor. This enables cytoplasmic STAT3 proteins to connect to the receptor's phosphorylated tyrosine residues utilising their SH2 domains. This is followed by JAKs phosphorylating STAT3 at Tyr705. This results in the separation of the STATs from the receptor, and their dimerization. Further, these dimerized STATs translocates to the nucleus where they induce the transcription of their target genes [ 6 , 7 ]. Moreover, the JAK2/STAT3 signalling can also work in conjunction with other signalling pathways, viz., MAPK/ERK and PI3K/AKT/mTOR, for particular cellular functions [ 28 ]. JAK2/STAT3 signalling is constitutively expressed in the breast cancer cell line [ 8 ]. The process depicting the role of JAK2/STAT3 pathway in cancer, and the role of the possible treatment targeting this pathway have been depicted in Fig. 6 . In our study we have hypothesized that during cancer, the binding of various factors in more than the usual amount to the JAK associated receptor, results in dimerization of the receptor, and increased activation of the JAK2 kinase domain. This could lead to increased phosphorylation STATs, resulting in the dimerization and translocation of STATs in more than usual amounts into the nucleus, and amplification of the target gene expression, leading to a cancerous condition. However, the herbal-based compounds might target the JAK 2 associated receptor, JAK2, and STAT3, thus modulating the upregulated activity of JAK 2, resulting in normal phosphorylation, and dimerization of STAT 3. These dimers are then translocated into the nucleus in normal amounts, resulting in the modulated expression of STAT 3 target genes, leading to normal cell survival. In the present study, we collected 2 species of Urtica ( U. dioica , and U. parviflora ) from different regions of Uttarakhand, and prepared their leaf and stem extracts separately in different solvents utilizing the Soxhlet extraction technique. The extracts were then analysed via the GC-MS technique, and a total of 173 compounds were identified from these extracts. These compounds were then evaluated for their anticancer potential by employing the molecular docking approach targeting JAK2, and out of these 173 compounds, 12 compounds were observed to have better binding energy (Table 2 ) than the control Paclitaxel. The selected hits were then subjected to the ADMET analysis. It was observed that the selected hits had better pharmacokinetic properties (Table 3 A, 3 B, and 3 C). In addition, the prepared extracts were also evaluated for their effect on MDA-MB-231 (TNBC cell line) cells. The anticancer activity of different extracts was significantly higher (P < 0.05) in comparison to the untreated cells. The IC 50 values of different extracts, and the % occurrence of the top 12 hits in these extracts, have been depicted in Table 4 . Thus, the presence of these hits in different extracts indicates that our study could provide lead compounds that will be crucial for target-specific drug discovery processes against TNBC. Table 4 Top 12 selected hits identified via GC/MS with percent of occurrence and IC 50 values S.No. Extracts Compounds % of occurence IC 50 (µg/ml) 1 PLCE ERGOST-5-EN-3-OL 0.79 90.09 ± 2.37 Vitamin E 0.63 2 PLHE ERGOST-5-EN-3-OL 2.4 99.14 ± 2.56 Vitamin E 2.4 3 DSEE alpha-Tocospiro-B 0.58 99.13 ± 3.04 14-Methylcholesta-2,8-dien-6-yl acetate 0.32 Stigmasta-4,7,22-trien-3.alpha.-ol 0.19 Stigmasta-5,22-dien-3-ol, acetate, (3.beta.)- 1.98 Ergost-5-en-3-ol, (3.beta.)- 1.58 4 PSHE 14-Methylcholesta-2,8-dien-6-yl acetate 0.99 105.63 ± 6.77 Stigmasta-4,7,22-trien-3.alpha.-ol 0.78 Stigmasta-5,22-dien-3-ol, acetate, (3.beta.)- 1.28 ERGOST-5-EN-3-OL 4.12 5 DLHE ERGOST-5-EN-3-OL 1.56 105.62 ± 9.16 Vitamin E 1.84 6 PSCE Stigmasta-4,7,22-trien-3.alpha.-ol 0.61 113.47 ± 2.98 Stigmasta-5,22-dien-3-ol, acetate, (3.beta.)- 0.85 ERGOST-5-EN-3-OL 1.48 7 DLEE ERGOST-5-EN-3-OL 1.33 118.07 ± 12.21 alpha-Tocospiro-B 0.65 8 DSHE ERGOST-5-EN-3-OL 1.46 125.55 ± 13.14 9 PSEE 14-Methylcholesta-2,8-dien-6-yl acetate 1.65 129.56 ± 14.33 Stigmasta-4,7,22-trien-3.alpha.-ol 1.6 Stigmasta-5,22-dien-3-ol, acetate, (3.beta.)- 2.43 Oxalic acid, 3,5-difluorophenyl undecyl ester 0.18 ERGOST-5-EN-3-OL 4.84 STIGMAST-5-EN-3-OL, (3.BETA.)- 0.2 10 DLCE ERGOST-5-EN-3-OL 0.55 168.89 ± 12.20 Vitamin E 0.57 11 DSCE ERGOST-5-EN-3-OL 1.7 172.16 ± 2.25 12 PLEE Diazoprogesterone 0.55 170.84 ± 26.67 2-(p-Chlorobenzyl)-1-(2-diethylaminoethyl)-5-nitrobenzimidazole 2.38 Stigmasta-3,5-diene 0.52 ERGOST-5-EN-3-OL 1.97 XANTHOSINE 4.88 13 Control Paclitaxel - 45 ± 3.25 5. Conclusion To the best of our knowledge, this is the first account of the anticancer activity displayed by Urtica spp. in Uttarakhand Himalaya. Thus, the present study will aid in the development of target-specific inhibitors for the development of novel anti-cancerous drugs. The ligands identified from the in-silico study were reported to display better binding energy. The in vitro studies, further confirmed that the Urtica extracts displayed significant anticancer potential. Hence, the compounds derived from both U. dioica and U. parviflora may represent good JAK2 modulators with the least toxic properties that could be employed as the platform for further in vivo studies and may enhance the pace of herbal drug development, which may be a better option for alternate chemotherapy against TNBC. Declarations Acknowledgements The authors are thankful to the Department of Zoology, SSJ University, Almora (Uttarakhand), India, and School of Biotechnology, Kalinga Institute of Industrial Technology (KIIT) Deemed to be University, Patia, India for providing the facility for this work. This work is supported by the DST-FIST grant SR/FST/LS- I/2018/131 to the Department of Zoology. Conflict of Interest The authors have declared no conflict of interest. References Rajabi S, Maresca M, Yumashev AV, Choopani R, Hajimehdipoor H. The Most Competent Plant-Derived Natural Products for Targeting Apoptosis in Cancer Therapy. Biomolecules. 2021;11. https://doi.org/10.3390/BIOM11040534 . Cancer. (n.d.). https://www.who.int/news-room/fact-sheets/detail/cancer (accessed April 3, 2023). Sun S, Zhao Y, Xu K. Post-adjuvant chemotherapy for triple-negative breast cancer. Med Hypotheses. 2016;90:74–5. https://doi.org/10.1016/J.MEHY.2016.03.009 . Foulkes WD, Smith IE, Reis-Filho JS. 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Identification of trans-2-cis-8-Matricaria-ester from the Essential Oil of Erigeron multiradiatus and Evaluation of Its Antileishmanial Potential by in Vitro and in Silico Approaches. ACS Omega. 2019;4:14640–9. https://doi.org/10.1021/ACSOMEGA.9B02130/SUPPL_FILE/AO9B02130_SI_001.PDF . Hu K, Law JH, Fotovati A, Dunn SE. Small interfering RNA library screen identified polo-like kinase-1 (PLK1) as a potential therapeutic target for breast cancer that uniquely eliminates tumor-initiating cells. Breast Cancer Res. 2012;14:R22. https://doi.org/10.1186/BCR3107 . Ayele TM, Muche ZT, Teklemariam AB, Kassie AB, Abebe EC. Role of JAK2/STAT3 Signaling Pathway in the Tumorigenesis, Chemotherapy Resistance, and Treatment of Solid Tumors: A Systemic Review. J Inflamm Res. 2022;15:1349. https://doi.org/10.2147/JIR.S353489 . Argetsinger LS, Kouadio J-LK, Steen H, Stensballe A, Jensen ON, Carter-Su C. Autophosphorylation of JAK2 on tyrosines 221 and 570 regulates its activity. Mol Cell Biol. 2004;24:4955–67. https://doi.org/10.1128/MCB.24.11.4955-4967.2004 . Murray PJ. The JAK-STAT signaling pathway: input and output integration. J Immunol. 2007;178:2623–9. https://doi.org/10.4049/JIMMUNOL.178.5.2623 . Supplementary Files supp1.tif Supplementary Fig. 1: Gas chromatogram of each sample Supp.table1.docx Cite Share Download PDF Status: Published Journal Publication published 08 Oct, 2023 Read the published version in Medical Oncology → Version 1 posted Reviewers agreed at journal 22 Aug, 2023 Reviewers invited by journal 11 Jun, 2023 Editor assigned by journal 31 May, 2023 First submitted to journal 30 May, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies 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-3000935","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":208810312,"identity":"eb603d21-bc72-4dc8-8d02-7ddd27f6c7e4","order_by":0,"name":"Shobha Upreti","email":"","orcid":"","institution":"Kumaun University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shobha","middleName":"","lastName":"Upreti","suffix":""},{"id":208810313,"identity":"61982977-8c76-4dd9-ae39-dbf8c119ecc5","order_by":1,"name":"Kartik Muduli","email":"","orcid":"","institution":"Kalinga Institute of Industrial Technology: Kalinga Institute of Industrial Technology Deemed to be University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Kartik","middleName":"","lastName":"Muduli","suffix":""},{"id":208810314,"identity":"36dc6513-aedf-41c8-8333-2cbd2152ca22","order_by":2,"name":"Jagannath Pradhan","email":"","orcid":"","institution":"Kalinga Institute of Industrial Technology: Kalinga Institute of Industrial Technology Deemed to be University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jagannath","middleName":"","lastName":"Pradhan","suffix":""},{"id":208810315,"identity":"086852e6-f9f8-4ddd-8fe2-df88e4dbe710","order_by":3,"name":"Selvakumar Elangovan","email":"","orcid":"","institution":"Kalinga Institute of Industrial Technology: Kalinga Institute of Industrial Technology Deemed to be University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Selvakumar","middleName":"","lastName":"Elangovan","suffix":""},{"id":208810316,"identity":"da0a2a1d-c342-4efc-97ff-42daf328cbea","order_by":4,"name":"Mukesh Samant","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6ElEQVRIiWNgGAWjYFACNgYGxgYo+wOIz06CFsbGGSA+MylamnlAFCEtujPSEh/+3FEnr9t+9vhjm1/b5PmYGRg/fMzBrcXsRtphY94zhw23nclLbM7tu23YxszALDlzGz4t6W3SjG0HGLcdyDFszu25zQjUwsbMi19L+8+fbXX2286/MWy27LltT4SWtGMMvG3MidtuAG1h+HE7kbCWM8+SpXnbDidvu/HGcGZvw+3kNmbGZvx+OZ5m+BHoMNtt53MMPvz4c9t2fnvzwQ8f8WhBBYxtYLKBWPUg8IcUxaNgFIyCUTBSAAAWs1ezXrgYnQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-0154-2421","institution":"Soban Singh Jeena University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Mukesh","middleName":"","lastName":"Samant","suffix":""}],"badges":[],"createdAt":"2023-05-30 15:11:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3000935/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3000935/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s12032-023-02193-5","type":"published","date":"2023-10-08T15:01:10+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":38538515,"identity":"4bdc36c1-6316-46ae-8a1c-068db0a0f015","added_by":"auto","created_at":"2023-06-14 14:11:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":222672,"visible":true,"origin":"","legend":"\u003cp\u003eChemical structure of top 12 selected hits\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-3000935/v1/3a75f02d5c7ae59d0167613c.png"},{"id":38538516,"identity":"42e34a85-6077-471e-be3c-873a074a3d5f","added_by":"auto","created_at":"2023-06-14 14:11:08","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":195733,"visible":true,"origin":"","legend":"\u003cp\u003eInteraction of the control Paclitaxel with the amino acid residues\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-3000935/v1/9751648ba5aebe71043b84c0.png"},{"id":38540211,"identity":"e9969a23-0892-497f-955a-062ed5c8e5c2","added_by":"auto","created_at":"2023-06-14 14:19:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":4841313,"visible":true,"origin":"","legend":"\u003cp\u003eInteraction displayed of Top 12 selected hits.\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-3000935/v1/9db4f2d36a84ae57d90f7eae.png"},{"id":38541407,"identity":"1888bef2-8038-4024-ba8e-798b6f2b5358","added_by":"auto","created_at":"2023-06-14 14:27:08","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2466305,"visible":true,"origin":"","legend":"\u003cp\u003eAnticancer activity of leaf and stem extracts from \u003cem\u003eUrtica dioica.\u003c/em\u003e There were three replicates in each experiment, and the results are expressed in mean IC50 ± SD at each time point. Significance values indicate the difference between the untreated cells and treated cells with various concentrations of different extracts (**, p\u0026lt;0.001)\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-3000935/v1/f56e798c07c21a265af35d3d.png"},{"id":38538514,"identity":"4f6117de-af5c-4084-bb4b-ce751ef0e1eb","added_by":"auto","created_at":"2023-06-14 14:11:08","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2537753,"visible":true,"origin":"","legend":"\u003cp\u003eAnticancer activity of leaf and stem extracts from \u003cem\u003eUrtica parviflora.\u003c/em\u003e There were three replicates in each experiment, and the results are expressed in mean IC50 ± SD at each time point. Significance values indicate the difference between the untreated cells and treated cells with various concentrations of different extracts (*, p\u0026lt;0.05; **, p\u0026lt;0.001)\u003c/p\u003e","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-3000935/v1/642d818c4b6e3f6bb9eb887b.png"},{"id":38541408,"identity":"8daca4c9-fc6b-44cb-a899-a2657bfd0a58","added_by":"auto","created_at":"2023-06-14 14:27:08","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":3639098,"visible":true,"origin":"","legend":"\u003cp\u003eA- During cancer: Up-regulated JAK2/STAT3 pathway\u003cstrong\u003e-\u003c/strong\u003e \u003cstrong\u003e(1)\u003c/strong\u003e Binding of various factors in more than the usual amount to the JAK2 associated receptor, \u003cstrong\u003e(2)\u003c/strong\u003e results in their dimerization, (\u003cstrong\u003e3\u003c/strong\u003e) followed by the autophosphorylation of JAK2, consequently enhancing the activation of JAK2 kinase domain. \u003cstrong\u003e(4,5,6)\u003c/strong\u003e Phosphorylated JAK2 then acts as the docking site for STAT3, leading to the increased number of phosphorylated STATs at the Tyr 705 residues, moreover, STAT 3 can be phosphorylated by the other pathways as well \u003cstrong\u003e(7,8,9).\u003c/strong\u003e The phosphorylated, STAT then separates from the receptor, and form dimers, which are then translocated inside the nucleus, in more than the usual amount. \u003cstrong\u003e(10, 11)\u003c/strong\u003e This whole process amplifies the target gene expression, leading to a cancerous condition. B- Possible treatment: Modulation of the JAK2/STAT3 pathway- \u003cstrong\u003e(12,13,14)\u003c/strong\u003e The herbal-based compounds viz., the Polar compounds, are thought to act by targeting the JAK 2 associated receptor, besides non-polar, and mid polar compounds are thought to target JAK2, and STAT3, \u003cstrong\u003e(15)\u003c/strong\u003e thus modulating the upregulated activity of JAK 2. \u003cstrong\u003e(16, 17, 18)\u003c/strong\u003e This results in the normal phosphorylation, and dimerization of STAT 3. \u003cstrong\u003e(19)\u003c/strong\u003e These dimers are then translocated into the nucleus in normal amount, \u003cstrong\u003e(20)\u003c/strong\u003e resulting in the modulated expression of STAT 3 target genes, leading to normal cell survival.\u003c/p\u003e","description":"","filename":"Fig6.png","url":"https://assets-eu.researchsquare.com/files/rs-3000935/v1/88b6d1d6da278242fe8521e7.png"},{"id":44794175,"identity":"26c4d962-6809-40ff-987f-9107476781fe","added_by":"auto","created_at":"2023-10-17 15:10:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1890041,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3000935/v1/f6e790eb-16c8-420d-b6b4-0a2f22fe8d21.pdf"},{"id":38538519,"identity":"6440bbeb-3532-4f4a-8e3a-b7d2d42f3877","added_by":"auto","created_at":"2023-06-14 14:11:08","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":576236,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Fig. 1: \u003c/strong\u003eGas chromatogram of each sample\u003c/p\u003e","description":"","filename":"supp1.tif","url":"https://assets-eu.researchsquare.com/files/rs-3000935/v1/99a205507018e80e32b9295e.tif"},{"id":38540210,"identity":"9d31d49b-4006-4dee-a6f8-fa75d1dd98fc","added_by":"auto","created_at":"2023-06-14 14:19:08","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":22156,"visible":true,"origin":"","legend":"","description":"","filename":"Supp.table1.docx","url":"https://assets-eu.researchsquare.com/files/rs-3000935/v1/2f620bad607959b10eff2f56.docx"}],"financialInterests":"","formattedTitle":"\u003cp\u003e\u003cstrong\u003eIdentification of novel inhibitors from \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eUrtica \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003espp against MDAMB-231 targeting JAK 2 receptor for breast cancer therapy\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eCancer is undoubtedly one of the major causes of mortality all around the globe, the growing burden of cancer is a matter of concern for the international health community to search for novel alternative treatments [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Recently, WHO estimated around 10\u0026nbsp;million deaths in the year 2020, and breast cancer is a leading cause of death accounting for around 2.26\u0026nbsp;million cases [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Even in the countries like the US where health facility is quite advanced the annual mortality cases from this particular cancer is high. Women are more likely than men to get breast cancer, among them triple-negative breast cancer (TNBC) accounts for 15\u0026ndash;20% of all the cases. Since these cells lack the major receptors (oestrogen, progesterone, HER2) that are targeted in chemotherapy, optimizing therapeutic management in them is challenging [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Moreover, a Poor prognosis of TNBC lowers the overall survival rates of the patients [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Patients with TNBC are often treated with conventional adjuvant chemotherapy, which does not have sufficient curative effects, since it lacks specificity, thus there is a setback in proper treatment for these patients [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Hence, the discovery of target-specific therapeutic agents is necessary.\u003c/p\u003e \u003cp\u003eJAK2/STAT3 pathway can be an important target in the development of treatment against TNBC [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The downstream signalling of this pathway is responsible for the transcription of their target genes, leading to cell survival, proliferation, differentiation and angiogenesis [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. JAK2/STAT3 signalling is constitutively expressed in the breast cancer cell line [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Hence, restraining the downstream signalling of this pathway in breast cancer has been reported to lower cell viability, invasion, and migration while also causing cell death [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Moreover, the increasing rates of drug resistance and extreme side effects associated with synthetic drugs are the reasons to find an alternative treatment [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Herbal-based compounds, due to the least side effects [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]can be employed in the treatment of TNBC via targeting the JAK2 receptor. \u003cem\u003eUrtica\u003c/em\u003e, a plant of the Uttarakhand Himalayan with potential anticancer and antiviral properties [\u003cspan additionalcitationids=\"CR15 CR16\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], can be exploited to develop treatment regimens for TNBC. Hence, moving in this direction, we collected two species of \u003cem\u003eUrtica\u003c/em\u003e (\u003cem\u003eU. dioica\u003c/em\u003e, and \u003cem\u003eU. parviflora\u003c/em\u003e) from different regions of Uttarakhand, followed by preparation of its leaf and stem extracts in polar (ethanol), mid-polar (chloroform), and non-polar (hexane) solvents utilizing the Soxhlet extraction technique. The extracts were DLEE (Dioica leaf ethanol extract), DSEE (Dioica stem ethanol extract), DLCE (Dioica leaf chloroform extract), DSCE (Dioica stem chloroform extract), DLHE (Dioica leaf hexane extract), DSHE (Dioica stem hexane extract),\u003c/p\u003e \u003cp\u003ePLEE (Parviflora leaf ethanol extract), PSEE (Parviflora stem ethanol extract), PLCE (Parviflora leaf chloroform extract), PSCE (Parviflora stem chloroform extract), PLHE (Parviflora leaf hexane extract), and PSHE (Parviflora stem hexane extract). The GC-MS analysis of these extracts revealed a total of 173 compounds to be present in them. Further, by the molecular docking approach, the compounds were studied for their interaction with JAK2, and around 12 compounds were reported to display better binding energy than the control Paclitaxel. The selected hits were then subjected to the ADMET and drug-likeness studies. It was observed that the selected hits demonstrated substantial pharmacokinetic properties. The prepared extracts were also evaluated by invitro studies against the MDA-MB-231 cell line, and interestingly it was observed that PLCE, PLHE, DSEE, PSHE, DLHE, PSCE, DLEE, DSHE, PSEE, DLCE, DSCE, PLEE displayed significant anticancer activity. Therefore, the strategy involved in our study will be helpful to understand the action mechanism of these herbal compounds, targeting JAK2 in TNBC. Moreover, the findings from this study could help to improve the future drug discovery process to treat breast cancer.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Plant collection\u003c/h2\u003e \u003cp\u003eWe collected the stem and leaf of \u003cem\u003eU. dioica\u003c/em\u003e and \u003cem\u003eU. parviflora\u003c/em\u003e from two different altitudes of Uttarakhand i.e. Almora Khatyari (Latitude\u0026thinsp;=\u0026thinsp;29.5945\u0026deg; N, and Longitude\u0026thinsp;=\u0026thinsp;79.6474\u0026deg; E ), and Almora, Jageshwar (latitude- 29.6384\u0026deg; N, longitude- 79.8528\u0026deg; E) respectively. A voucher [Accession numbers \u0026minus;\u0026thinsp;22903(RKT), and 25808 (RKT) were obtained for \u003cem\u003eU. dioica\u003c/em\u003e, and \u003cem\u003eU. parviflora\u003c/em\u003e, respectively] has been deposited at the Herbarium of Regional Ayurveda Research Institute, Ranikhet, Almora, Uttarakhand, India.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Drying and extraction\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eHealthy plants of \u003cem\u003eU\u003c/em\u003e. \u003cem\u003edioica\u003c/em\u003e and \u003cem\u003eU. parviflora\u003c/em\u003e were selected for collection and extraction purposes.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1 \u003cem\u003eInitial preparation\u003c/em\u003e\u003c/h2\u003e \u003cp\u003eCollected plants were washed thoroughly with water, and then with distilled water to remove dust and other contaminants from the leaves and stem. Later these leaves and stems were sliced into small pieces and kept in the shade for drying until the moisture was eliminated, followed by grinding of this material into homogenous powder.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e\u003cem\u003e2.2.2 Soxhlet extraction\u003c/em\u003e\u003c/h2\u003e \u003cp\u003eThe Soxhlet extraction technique constitutes a thimble that was filled with the powder, followed by its insertion into the Soxhlet apparatus (Borosil). The extraction was carried out by using polar (ethanol), mid-polar (chloroform), and non-polar (hexane) solvents. Each extraction was carried out for 9\u0026ndash;10 hours at a temperature of 60\u0026ndash;65\u0026deg;C. A rotary evaporator operating at 40\u0026deg;C was then used to remove the excess solvent. Further, the percent yield value was calculated for all the prepared extracts. The dried extracts were then utilized for phytochemical screening and were also evaluated for their anticancer potential.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Chemical profiling\u003c/h2\u003e \u003cp\u003eThe phytochemicals present in the respective solvents were then identified by utilizing the GC-MS technique. The analysis was done at the AIRF (Advanced instrumental research facility), JNU (Jawahar Lal Nehru University), New Delhi.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Target protein selection and preparation\u003c/h2\u003e \u003cp\u003eThe crystal structure of the human JAK-2 was retrieved from the RCSB (Research Collaboratory for Structural\u003c/p\u003e \u003cp\u003eBioinformatics) in PDB format. The protein had a resolution of 1.80 \u0026Aring;. Using Pymol [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] the ligand was isolated from the respective PDB structure, followed by the removal of water molecules [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. This receptor structure was then uploaded into PyRx, where it was subjected to energy minimization and was further converted to PDBQT format for analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Ligands preparation\u003c/h2\u003e \u003cp\u003eAll the phytochemicals or ligands were obtained from the PubChem database in sdf format (URL: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubchem.ncbi.nlm.nih.gov\u003c/span\u003e\u003cspan address=\"https://pubchem.ncbi.nlm.nih.gov\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Further by utilizing Open Babel 3.1.1 software, these ligands were converted from their SDF format to the PDB format for further virtual screening. Before testing the potentiality of the \u003cem\u003eUrtica dioca and Urtica parviflora\u003c/em\u003e compounds against JAK 2(PDB ID: 3krr) a broad-spectrum anti-cancerous drug i.e., Paclitaxel with PubChem CID- 36314 was also used as a control.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Molecular docking\u003c/h2\u003e \u003cp\u003eMolecular docking was performed by utilizing the PyRx virtual screening tool, which uses the auto dock wizard for docking [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. All the docking calculations utilized LGA (Lamarckian genetic algorithm) technique, and the exhaustiveness score for these calculations was set to 8. Moreover, a grid box large enough to cover the active site with the following dimensions: centre (X, Y, Z): (15.4960, 12.6684, 1.4063) \u0026Aring; and size: (X, Y, Z): (25.6943, 22.8757, 21.2828). The binding affinity and the RMSD (root mean square deviation) value were utilized to find the favourable binding. Lastly, the top 12 hit compounds were selected based on their higher binding affinity. The compounds displaying an RMSD value less than 1.0 \u0026Aring; were employed for observing the favourable binding. The ligand molecules were docked automatically to the active site of the receptor protein, and the conformers with the highest binding affinity were selected for the post-docking analysis. The selected hits were finally visualized utilizing the Discovery Studio visualizer 3.0.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.7. Drug-likeness and in silico ADMET prediction\u003c/h2\u003e \u003cp\u003eADMET analysis is crucial at an early phase of drug development. The pharmacokinetic profile viz., absorption, distribution, metabolism, and excretion. Lipinski\u0026rsquo;s rule of five is crucial for determining the drug-likeness of the identified compounds. According to the rule of five, there should be only 5 hydrogen bond donors, and 10 hydrogen bond acceptors, a partition coefficient of no more than 5, a polar surface area (PSA) of no more than 140 \u0026Aring;\u003csup\u003e2\u003c/sup\u003e and a molecular weight of no more than 500 Da [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. To make our study time and cost-effective Lipinski\u0026rsquo;s rule of five was applied to analyze the pharmacokinetics of the twelve identified hits. The candidate hits from the virtual screening were further employed for ADMET analysis. These candidate hits, along with the control, Paclitaxel was evaluated for different parameters viz., drug-likeness, physiochemical properties, pharmacokinetics, and toxicity. SwissADME was employed for ADME analysis [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], Protox II, for toxicity and median lethal dose (LD50) prediction [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], and pkCSM, for ADMET parameters of compounds [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.8. Cell culture and cell viability assay\u003c/h2\u003e \u003cp\u003eMDA-MB-231 breast cancer cell lines were purchased from the National Centre for Cell Science (NCCS), Pune, India. MDA-MB-231 cells were grown in L15 media with 10% FBS (fetal bovine serum), 100 IU/ml penicillin, 100 g/ml streptomycin, and 0.25 \u0026micro;g/ml amphotericin B at 37\u0026deg;C in a humid incubator with 5% CO\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e \u003cp\u003eCell viability assay was performed, and 1x10\u003csup\u003e4\u003c/sup\u003e MDA-MB-231 cells were seeded per well in 96-well plates. After 24 hours of incubation in a 5% CO\u003csub\u003e2\u003c/sub\u003e incubator at 37\u0026deg;C, the cells were treated with different concentrations (10\u0026micro;g/ml, 50 \u0026micro;g/ml, 100 \u0026micro;g/ml and 200 \u0026micro;g/ml) of the prepared extracts. MTT assay was performed as described earlier [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], in brief after 48 hours of incubation, 20 \u0026micro;L of the MTT (MP Biomedicals, USA) stock solution (5mg/ml) was added to each well, followed by additional 4 hours of incubation. After which, 100\u0026micro;l of the solubilizing buffer was added to each well to dissolve the formazan crystals. The absorbance was taken at 570 nm wavelength using an Elisa reader (Epoch, Biotek, USA). Further, the percentage inhibition was calculated by comparing the percentage of viability with the untreated control. The experiment was performed in triplicates to verify the results. Paclitaxel was taken as a positive control.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e2.9. Statistical Analysis.\u003c/h2\u003e \u003cp\u003eThe experiments were performed in triplicates, and compiled as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. Further analysis of the results was done by one-way ANOVA, and Dunnett\u0026rsquo;s post-test was applied. GraphPad Prism (version 9) software, was utilized for all the analysis.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Result","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Yield\u003c/h2\u003e \u003cp\u003eleaves and stem extract yield were calculated in three different solvents i.e., hexane, chloroform and ethanol. The percent yield is presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003epercentage yield of different extracts from \u003cem\u003eUrtica\u003c/em\u003e spp.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlants\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSolvent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWeight (g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYield (g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e% Yield\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cem\u003eUrtica dioica\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEthanol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLeave\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eChloroform\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLeave\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHexane\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLeave\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cem\u003eUrtica parviflora\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEthanol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLeave\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eChloroform\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLeave\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHexane\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLeave\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Chemical profiling\u003c/h2\u003e \u003cp\u003eThe phytoconstituent were evaluated and identified by comparing their mass spectra. NIST-MS and WILEY library were utilized to compare molecular weight, peak retention time, and molecular formula of the identified compounds to that of the already known compounds. The gas chromatogram of each sample is presented in \u003cb\u003eSupplementary Fig.\u0026nbsp;1.\u003c/b\u003e The major phytoconstituents obtained from the GCMS analysis are presented in \u003cb\u003eSupplementary Table\u0026nbsp;1.\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Molecular docking\u003c/h2\u003e \u003cp\u003eIn the current study, we have employed the molecular docking approach to calculate the binding energy of the docked structure. Th\u003cb\u003ee c\u003c/b\u003eompounds, 14-Methylcholesta-2,8-dien-6-yl acetate (-8.6 Kcal/mol), Stigmasta-4,7,22-trien-3. alpha.-ol (-8.6 Kcal/mol), 2-(p-Chlorobenzyl)-1-(2-diethylaminoethyl)-5-nitrobenzimidazole (-8.4 Kcal/mol), Stigmasta-5,22-dien-3. beta. -ol, acetate (-8.3 Kcal/mol), Stigmasta-3,5-diene (-8.0 Kcal/mol), etc., had better binding energy than the control Paclitaxel (-7.1 Kcal/mol), the chemical structure of the top 12 hit compounds have been depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Molecular docking interaction analysis revealed that all the top 12 hits showed binding interaction patterns with various catalytic site residues like LEU983, LEU855, VAL863, ARG980, VAL863, ALA880, LEU855, LEU932, in the binding pocket of JAK 2 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Moreover, the selected hits showed H-bond with amino acids GLY 856, ARG980, ASN981, and ASP994 of JAK2. The protein-ligand interactions, with control and the hits, have been displayed in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cb\u003eand\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, respectively. Overall, in comparison to the control, the selected hits had favourable interactions that proves them to be potent modulators of JAK2.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBinding interaction of top twelve selected hits with active site amino acid residues of JAK2\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\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\u003eCompound Name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBinding Energy Kcal/mol\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ermsd/ub\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ermsd/lb\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eInteractive residues\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHydrogen Bonds\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14-Methylcholesta-2,8-dien-6-yl acetate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLEU983, LEU855, VAL863, ARG980\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGLY 856\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStigmasta-4,7,22-trien-3. alpha.-ol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLEU855, LEU983, VAL863, ARG980\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2-(p-Chlorobenzyl)-1-(2-diethylaminoethyl)-5-nitrobenzimidazole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVAL863,\u003c/p\u003e \u003cp\u003eALA880, LEU855,\u003c/p\u003e \u003cp\u003eLEU932,\u003c/p\u003e \u003cp\u003eLEU983\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eARG980,\u003c/p\u003e \u003cp\u003eASN981, ASP994\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStigmasta-5,22-dien-3. beta. -ol, acetate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVAL1110,\u003c/p\u003e \u003cp\u003ePTR1007,\u003c/p\u003e \u003cp\u003eLYS1030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStigmasta-3,5-diene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLYS1030,\u003c/p\u003e \u003cp\u003eVAL1110,\u003c/p\u003e \u003cp\u003eALA1034,\u003c/p\u003e \u003cp\u003eVAL1033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOxalic acid, 3,5-difluorophenyl undecyl ester\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eARG1117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eALA1034, VAL1033, SER1032, GLU1006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eERGOST-5-EN-3-OL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eALA880, LEU855,\u003c/p\u003e \u003cp\u003eVAL863,\u003c/p\u003e \u003cp\u003eLEU983\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eASP994\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eXANTHOSINE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTHR875, ARG867\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ealpha-Tocospiro-B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePHE1019, PRO1058, PRO1017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eARG980, SER936\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVitamin E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eALA880,\u003c/p\u003e \u003cp\u003eLEU855,\u003c/p\u003e \u003cp\u003eVAL863,\u003c/p\u003e \u003cp\u003eLEU983\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGLY856\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiazoprogesterone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePRO1058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eASN 981, ASP976\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e. BETA. -SITOSTEROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLEU1026\u003c/p\u003e \u003cp\u003eSER1029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePRO1013\u003c/p\u003e \u003cp\u003eVAL1075\u003c/p\u003e \u003cp\u003ePHE1076\u003c/p\u003e \u003cp\u003eILE1079\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePaclitaxel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVAL 1033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSER1115\u003c/p\u003e \u003cp\u003eARG971\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 \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Prediction of ADMET properties\u003c/h2\u003e \u003cp\u003eThe development of an effective drug depends on pharmacokinetic factors such as absorption, distribution, metabolism, and excretion. ADME prediction is an important component of pre-clinical drug research since it lowers the likelihood that the compounds with a better pharmacokinetic profile would fall through the clinical trials. Selected 12 hits were examined for their pharmacological, pharmacokinetic, drug-like, and toxicological characteristics. The anticipated pharmacological parameters for a subset of 12 hits as well as the control are described in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cb\u003e(A, B, and C)\u003c/b\u003e. The data makes it evident that the hits that were chosen displayed pharmacological characteristics that were in a favourable range, thus these compounds can act as a potential drug candidate against TNBC. All the 12 hits fulfilled Lipinski's five-hit guideline. The consensus Log Po/w ranges from 3.34 to 8.27, which represents the good lipophilicity behaviour that all of the hits exhibited. These hits demonstrated synthetic accessibility in the range of 3.09 to 6.88. All the compounds except 2-(p-Chlorobenzyl)-1-(2-diethylaminoethyl)-5-nitrobenzimidazole exhibited high intestinal absorption and bioavailability. Moreover, the capacity of each hit to interact with the different isomers of cytochrome P450 varied. The cytochrome P450 isoenzymes interacted somewhat with the top hits, thus demonstrating their better effectiveness in biotransformation with less toxicity. Almost all of the hits had Caco-2 (colon cancer cell line) permeability values greater than 0.90. The overall clearance rate of the chosen hits was between 0.307 to 1.589. The toxicity study of the hits indicates little to no harmful effects. A range of low to high maximum tolerated dosages are shown by each hit. Overall, the ADMET study indicates that the compounds employed in our study could be helpful in the development of safer anticancer drugs.\u003c/p\u003e \u003cp\u003e\u003cstrong\u003eTable 3: Pharmacological parameters for a subset of 12 hits as well as the control\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eA: Physiochemical, Drug likeness, and Medicinal chemistry prediction of control and selected hits using SwissADME\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMolecule\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFormula\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMW (g/mol)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRotatable bonds\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eH-bond acceptors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eH-bond donors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTPSA\u003c/p\u003e \u003cp\u003e(\u0026Aring;\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eConsensus Log P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eESOL Log S\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eESOL Class (Water solubility)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eDrug likeness (Lipinski violations)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eMedicinal Chemistry (Synthetic Accessibility)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC30H48O2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e440.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e26.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e7.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePoorly soluble\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC29H46O\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e410.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e6.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-6.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePoorly soluble\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e6.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC20H23ClN4O2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e386.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e66.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-4.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eModerately soluble\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC31H50O2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e454.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e26.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e7.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-7.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePoorly soluble\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e6.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC29H48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e396.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e7.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-8.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePoorly soluble\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e6.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC19H26F2O4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e356.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e52.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-5.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eModerately soluble\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC28H48O\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e400.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-7.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePoorly soluble\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e6.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC10H12N4O6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e284.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e153.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-1.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eVery soluble\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC29H50O4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e462.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e63.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e6.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-6.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePoorly soluble\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e6.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC29H50O2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e430.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e29.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e8.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePoorly soluble\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e5.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC21H28N2O2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e340.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e71.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-4.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eModerately soluble\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e5.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC29H50O\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e414.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e7.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePoorly soluble\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePaclitaxel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC47H51NO14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e853.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e221.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-6.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePoorly soluble\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e8.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003eMW: Molecular weight; HBA.: Hydrogen Bond Acceptor; HBD: Hydrogen Bond Donor; TPSA: Topological polar surface area.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eB: ADMET prediction of control and selected hits using pkCSM.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"15\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\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\u003eCaco2 permeability\u003c/p\u003e \u003cp\u003e(log Papp in 10\u0026ndash;6 cm/s)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntestinal absorption (human)\u003c/p\u003e \u003cp\u003e(% Absorbed)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-glycoprotein substrate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVDss (human)\u003c/p\u003e \u003cp\u003e(log L/ kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFraction unbound (human)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCYP2D6 substrate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCYP3A4 substrate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eCYP1A2 inhibitor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCYP2C19 inhibitor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eCYP2C9 inhibitor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eCYP2D6 inhibitor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eCYP3A4 inhibitor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eTotal Clearance\u003c/p\u003e \u003cp\u003e(log ml/min/ kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003eRenal OCT2 substrate\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95.458\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.502\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95.604\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.622\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84.421\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.371\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.757\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.539\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96.148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91.491\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e1.589\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94.543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.427\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.839\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.594\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.613\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.612\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.936\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.345\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89.782\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.709\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.794\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.662\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97.088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94.464\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.628\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePaclitaxel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.623\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.458\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e-0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eNo\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 \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eB: ADMET prediction of control and selected hits using pkCSM.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"15\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\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\u003eCaco2 permeability\u003c/p\u003e \u003cp\u003e(log Papp in 10\u0026ndash;6 cm/s)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntestinal absorption (human)\u003c/p\u003e \u003cp\u003e(% Absorbed)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-glycoprotein substrate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVDss (human)\u003c/p\u003e \u003cp\u003e(log L/ kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFraction unbound (human)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCYP2D6 substrate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCYP3A4 substrate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eCYP1A2 inhibitor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCYP2C19 inhibitor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eCYP2C9 inhibitor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eCYP2D6 inhibitor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eCYP3A4 inhibitor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eTotal Clearance\u003c/p\u003e \u003cp\u003e(log ml/min/ kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003eRenal OCT2 substrate\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95.458\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.502\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95.604\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.622\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84.421\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.371\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.757\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.539\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96.148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91.491\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e1.589\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94.543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.427\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.839\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.594\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.613\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.612\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.936\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.345\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89.782\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.709\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.794\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.662\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97.088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94.464\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.628\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePaclitaxel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.623\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.458\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e-0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Invitro anticancer activity\u003c/h2\u003e \u003cp\u003eThe prepared extracts were also evaluated for their effect on MDA-MB-231 cells. The anticancer activity of different extracts was represented by the IC\u003csub\u003e50\u003c/sub\u003e values, viz., DLEE (118.07\u0026thinsp;\u0026plusmn;\u0026thinsp;12.21 \u0026micro;g/ml), DSEE (99.13\u0026thinsp;\u0026plusmn;\u0026thinsp;3.04 \u0026micro;g/ml), DLCE (168.89\u0026thinsp;\u0026plusmn;\u0026thinsp;12.20 \u0026micro;g/ml), DSCE (172.16\u0026thinsp;\u0026plusmn;\u0026thinsp;2.25 \u0026micro;g/ml), DLHE (105.62\u0026thinsp;\u0026plusmn;\u0026thinsp;9.16 \u0026micro;g/ml), DSHE (125.55\u0026thinsp;\u0026plusmn;\u0026thinsp;13.14 \u0026micro;g/ml), PLEE (170.84\u0026thinsp;\u0026plusmn;\u0026thinsp;26.67 \u0026micro;g/ml), PSEE (129.56\u0026thinsp;\u0026plusmn;\u0026thinsp;14.33 \u0026micro;g/ml), PLCE (90.09\u0026thinsp;\u0026plusmn;\u0026thinsp;2.37 \u0026micro;g/ml), PSCE (113.47\u0026thinsp;\u0026plusmn;\u0026thinsp;2.98 \u0026micro;g/ml), PLHE (99.14\u0026thinsp;\u0026plusmn;\u0026thinsp;2.56 \u0026micro;g/ml), PSHE (105.63\u0026thinsp;\u0026plusmn;\u0026thinsp;6.77 \u0026micro;g/ml), and was significantly higher (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in comparison to the untreated cells. IC\u003csub\u003e50\u003c/sub\u003e\u0026thinsp;\u003cem\u003e\u0026plusmn;\u003c/em\u003e\u0026thinsp;SD values of \u003cem\u003eU. dioica, and U. parviflora\u003c/em\u003e extracts have been depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e \u003cb\u003eand\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eTNBC is the most fatal form of breast cancer in women worldwide, since the three major targets of chemotherapy viz., Estrogen, Progesterone, and HER-2 receptors are not present in these cancer cells [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The increasing rates of drug resistance and extreme side effects associated with synthetic drugs are the main reasons to discontinue chemotherapy [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Thus, finding an alternative form of treatment is of utmost importance. Uttarakhand Himalaya has been known to be affluent in traditional plants that have been reported to be effective against a range of human diseases [\u003cspan additionalcitationids=\"CR15 CR16\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Herbs like \u003cem\u003eUrtica\u003c/em\u003e or Stinging nettle are among the most common, multi-purpose plants that have not been exploited to their full potential yet. However, these plants of Uttarakhand Himalaya are still underestimated and unexplored plants, particularly in herbal medicine.\u003c/p\u003e \u003cp\u003eJAK2/STAT3 pathway can be an important lead in the development of anticancer therapy in triple-negative breast cancer [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The binding of the cytokines (IL-6 family, leptin, and erythropoietin), hormones like prolactin, and growth factors like epidermal growth factor (EGF), to the extracellular domain of the tyrosine kinase associated receptor, causes dimerization of the JAK2 associated subunits, thus bringing these subunits together [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. This induces cross-phosphorylation by JAK2 on the tyrosine residue, a process known as autophosphorylation, thus activating their kinase domain. It has been reported that tyrosine 221 and 570, which are conserved in Humans and these JAK2's equivalent tyrosines are not present in JAK1, JAK3, or TYK2, therefore phosphorylation of these tyrosines may start JAK2-specific processes [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The activated kinase subsequently phosphorylates the tyrosine residues on the intracellular domains of the receptor. This enables cytoplasmic STAT3 proteins to connect to the receptor's phosphorylated tyrosine residues utilising their SH2 domains. This is followed by JAKs phosphorylating STAT3 at Tyr705. This results in the separation of the STATs from the receptor, and their dimerization. Further, these dimerized STATs translocates to the nucleus where they induce the transcription of their target genes [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Moreover, the JAK2/STAT3 signalling can also work in conjunction with other signalling pathways, viz., MAPK/ERK and PI3K/AKT/mTOR, for particular cellular functions [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. JAK2/STAT3 signalling is constitutively expressed in the breast cancer cell line [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The process depicting the role of JAK2/STAT3 pathway in cancer, and the role of the possible treatment targeting this pathway have been depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. In our study we have hypothesized that during cancer, the binding of various factors in more than the usual amount to the JAK associated receptor, results in dimerization of the receptor, and increased activation of the JAK2 kinase domain. This could lead to increased phosphorylation STATs, resulting in the dimerization and translocation of STATs in more than usual amounts into the nucleus, and amplification of the target gene expression, leading to a cancerous condition. However, the herbal-based compounds might target the JAK 2 associated receptor, JAK2, and STAT3, thus modulating the upregulated activity of JAK 2, resulting in normal phosphorylation, and dimerization of STAT 3. These dimers are then translocated into the nucleus in normal amounts, resulting in the modulated expression of STAT 3 target genes, leading to normal cell survival.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn the present study, we collected 2 species of \u003cem\u003eUrtica\u003c/em\u003e (\u003cem\u003eU. dioica\u003c/em\u003e, and \u003cem\u003eU. parviflora\u003c/em\u003e) from different regions of Uttarakhand, and prepared their leaf and stem extracts separately in different solvents utilizing the Soxhlet extraction technique. The extracts were then analysed via the GC-MS technique, and a total of 173 compounds were identified from these extracts. These compounds were then evaluated for their anticancer potential by employing the molecular docking approach targeting JAK2, and out of these 173 compounds, 12 compounds were observed to have better binding energy (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) than the control Paclitaxel. The selected hits were then subjected to the ADMET analysis. It was observed that the selected hits had better pharmacokinetic properties (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, and \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). In addition, the prepared extracts were also evaluated for their effect on MDA-MB-231 (TNBC cell line) cells. The anticancer activity of different extracts was significantly higher (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in comparison to the untreated cells. The IC\u003csub\u003e50\u003c/sub\u003e values of different extracts, and the % occurrence of the top 12 hits in these extracts, have been depicted in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Thus, the presence of these hits in different extracts indicates that our study could provide lead compounds that will be crucial for target-specific drug discovery processes against TNBC.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop 12 selected hits identified via GC/MS with percent of occurrence and IC\u003csub\u003e50\u003c/sub\u003e values\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\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\u003eExtracts\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCompounds\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e% of occurence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIC\u003csub\u003e50\u003c/sub\u003e (\u0026micro;g/ml)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePLCE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERGOST-5-EN-3-OL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e90.09\u0026thinsp;\u0026plusmn;\u0026thinsp;2.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVitamin E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePLHE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERGOST-5-EN-3-OL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e99.14\u0026thinsp;\u0026plusmn;\u0026thinsp;2.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVitamin E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eDSEE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ealpha-Tocospiro-B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e99.13\u0026thinsp;\u0026plusmn;\u0026thinsp;3.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14-Methylcholesta-2,8-dien-6-yl acetate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStigmasta-4,7,22-trien-3.alpha.-ol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStigmasta-5,22-dien-3-ol, acetate, (3.beta.)-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eErgost-5-en-3-ol, (3.beta.)-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003ePSHE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14-Methylcholesta-2,8-dien-6-yl acetate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e105.63\u0026thinsp;\u0026plusmn;\u0026thinsp;6.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStigmasta-4,7,22-trien-3.alpha.-ol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStigmasta-5,22-dien-3-ol, acetate, (3.beta.)-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERGOST-5-EN-3-OL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDLHE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERGOST-5-EN-3-OL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e105.62\u0026thinsp;\u0026plusmn;\u0026thinsp;9.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVitamin E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePSCE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStigmasta-4,7,22-trien-3.alpha.-ol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e113.47\u0026thinsp;\u0026plusmn;\u0026thinsp;2.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStigmasta-5,22-dien-3-ol, acetate, (3.beta.)-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERGOST-5-EN-3-OL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDLEE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERGOST-5-EN-3-OL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e118.07\u0026thinsp;\u0026plusmn;\u0026thinsp;12.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ealpha-Tocospiro-B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDSHE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERGOST-5-EN-3-OL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e125.55\u0026thinsp;\u0026plusmn;\u0026thinsp;13.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003ePSEE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14-Methylcholesta-2,8-dien-6-yl acetate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e129.56\u0026thinsp;\u0026plusmn;\u0026thinsp;14.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStigmasta-4,7,22-trien-3.alpha.-ol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStigmasta-5,22-dien-3-ol, acetate, (3.beta.)-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOxalic acid, 3,5-difluorophenyl undecyl ester\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERGOST-5-EN-3-OL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSTIGMAST-5-EN-3-OL, (3.BETA.)-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDLCE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERGOST-5-EN-3-OL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e168.89\u0026thinsp;\u0026plusmn;\u0026thinsp;12.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVitamin E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDSCE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERGOST-5-EN-3-OL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e172.16\u0026thinsp;\u0026plusmn;\u0026thinsp;2.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ePLEE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDiazoprogesterone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e170.84\u0026thinsp;\u0026plusmn;\u0026thinsp;26.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2-(p-Chlorobenzyl)-1-(2-diethylaminoethyl)-5-nitrobenzimidazole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStigmasta-3,5-diene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERGOST-5-EN-3-OL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eXANTHOSINE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePaclitaxel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e45\u0026thinsp;\u0026plusmn;\u0026thinsp;3.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eTo the best of our knowledge, this is the first account of the anticancer activity displayed by \u003cem\u003eUrtica\u003c/em\u003e spp. in Uttarakhand Himalaya. Thus, the present study will aid in the development of target-specific inhibitors for the development of novel anti-cancerous drugs. The ligands identified from the in-silico study were reported to display better binding energy. The in vitro studies, further confirmed that the \u003cem\u003eUrtica\u003c/em\u003e extracts displayed significant anticancer potential. Hence, the compounds derived from both \u003cem\u003eU. dioica\u003c/em\u003e and \u003cem\u003eU. parviflora\u003c/em\u003e may represent good JAK2 modulators with the least toxic properties that could be employed as the platform for further in vivo studies and may enhance the pace of herbal drug development, which may be a better option for alternate chemotherapy against TNBC.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are thankful to the Department of Zoology, SSJ University, Almora (Uttarakhand), India, and School of Biotechnology, Kalinga Institute of Industrial Technology (KIIT) Deemed to be University, Patia, India for providing the facility for this work.\u0026nbsp;This work is supported by the DST-FIST grant SR/FST/LS- I/2018/131 to the Department of Zoology.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have declared no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRajabi S, Maresca M, Yumashev AV, Choopani R, Hajimehdipoor H. 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J Immunol. 2007;178:2623\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4049/JIMMUNOL.178.5.2623\u003c/span\u003e\u003cspan address=\"10.4049/JIMMUNOL.178.5.2623\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"medical-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"medo","sideBox":"Learn more about [Medical Oncology](https://www.springer.com/journal/12032)","snPcode":"12032","submissionUrl":"https://submission.nature.com/new-submission/12032/3","title":"Medical Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Triple-negative breast cancer, Molecular docking, Pharmacokinetic studies, IC50","lastPublishedDoi":"10.21203/rs.3.rs-3000935/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3000935/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBreast cancer is the most prevalent form of cancer in women globally, and MDA-MB-231 or TNBC (Triple-negative breast cancer) is its aggressive type since it lacks the usual targets. JAK2/STAT3 pathway can be an important lead in anticancer drug discovery, as\u003cstrong\u003e \u003c/strong\u003erestraining the downstream signalling of this pathway results in the induction of cell apoptosis. Moreover, various limitations associated with chemotherapy are the reason to find an alternative herbal-based therapy. For this study, we collected \u003cem\u003eUrtica dioica\u003c/em\u003e, and \u003cem\u003eU. parviflora\u003c/em\u003e from different regions of Uttarakhand, followed by preparation of their leaf and stem extracts in different solvents. The GC-MS analysis of these extracts revealed a total of 173 compounds to be present in them. Further, by molecular docking approach, we studied the interaction between these compounds and JAK2, and 12 major compounds with better binding energy than the control Paclitaxel were identified. In addition, the selected hits were also reported to display better pharmacokinetic properties. The anticancer potential of these extracts was also evaluated by in vitro approach in the MDA-MB-231 cell line, and both extracts displayed significant anticancer activity. Hence, the findings in our study can be crucial in the area of herbal-based target-specific drug development against breast cancer.\u003c/p\u003e","manuscriptTitle":"Identification of novel inhibitors from Urtica spp against MDAMB-231 targeting JAK 2 receptor for breast cancer therapy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-06-14 14:11:03","doi":"10.21203/rs.3.rs-3000935/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2023-08-22T20:02:44+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-06-11T16:56:31+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-05-31T07:25:12+00:00","index":"","fulltext":""},{"type":"submitted","content":"Medical Oncology","date":"2023-05-30T11:11:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"medical-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"medo","sideBox":"Learn more about [Medical Oncology](https://www.springer.com/journal/12032)","snPcode":"12032","submissionUrl":"https://submission.nature.com/new-submission/12032/3","title":"Medical Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"45b988f8-a307-4784-8f90-b1b3b2c0238d","owner":[],"postedDate":"June 14th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-10-17T15:10:06+00:00","versionOfRecord":{"articleIdentity":"rs-3000935","link":"https://doi.org/10.1007/s12032-023-02193-5","journal":{"identity":"medical-oncology","isVorOnly":false,"title":"Medical Oncology"},"publishedOn":"2023-10-08 15:01:10","publishedOnDateReadable":"October 8th, 2023"},"versionCreatedAt":"2023-06-14 14:11:03","video":"","vorDoi":"10.1007/s12032-023-02193-5","vorDoiUrl":"https://doi.org/10.1007/s12032-023-02193-5","workflowStages":[]},"version":"v1","identity":"rs-3000935","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3000935","identity":"rs-3000935","version":["v1"]},"buildId":"GqpaHPwrfC8PjnIFayRh5","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}