Computer-aided analysis for identification of novel analogues of ketoprofen based on molecular docking, ADMET, drug-likeness and DFT studies for the treatment of inflammation

References

• Anjum, K., Abbas, S. Q., Shah, S. A. A., Akhter, N., Batool, S., & Hassan, S. S. U. (2016). Marine sponges as a drug treasure. Biomolecules & Therapeutics, 24(4), 347–362. https://doi.org/10.4062/biomolther.2016.067
   PubMed Web of Science ®Google Scholar
• Artis, D., & Spits, H. (2015). The biology of innate lymphoid cells. Nature, 517(7534), 293–301. https://doi.org/10.1038/nature14189
   PubMed Web of Science ®Google Scholar
• Becke, A. D. (1993). Density-functional thermochemistry. III. The role of exact exchange. The Journal of Chemical Physics, 98(7), 5648–5652. https://doi.org/10.1063/1.464913
   Web of Science ®Google Scholar
• Birmingham, B., & Buvanendran, A. (2013). Nonsteroidal anti-inflammatory drugs, cetaminophen, and COX-2 inhibitors. In Practical management of pain: Fifth edition (5th ed.). Elsevier Inc. https://doi.org/10.1016/B978-0-323-08340-9.00040-2
   Google Scholar
• Braun, R. K., Ferrick, C., Neubauer, P., Sjoding, M., Sterner-Kock, A., Kock, M., Putney, L., Ferrick, D. A., Hyde, D. M., & Love, R. B. (2008). IL-17 producing γδ T cells are required for a controlled inflammatory response after bleomycin-induced lung injury. Inflammation, 31(3), 167–179. https://doi.org/10.1007/s10753-008-9062-6
   PubMed Web of Science ®Google Scholar
• Carbon-Mangels, M., & Hutter, M. C. (2011). Selecting relevant descriptors for classification by Bayesian estimates: A comparison with decision trees and support vector machines approaches for disparate data sets. Molecular Informatics, 30(10), 885–895. https://doi.org/10.1002/minf.201100069
   PubMed Web of Science ®Google Scholar
• Cingolani, G., Panella, A., Perrone, M. G., Vitale, P., Di Mauro, G., Fortuna, C. G., Armen, R. S., Ferorelli, S., Smith, W. L., & Scilimati, A. (2017). Structural basis for selective inhibition of Cyclooxygenase-1 (COX-1) by diarylisoxazoles mofezolac and 3-(5-chlorofuran-2-yl)-5-methyl-4-phenylisoxazole (P6). European Journal of Medicinal Chemistry, 138, 661–668. https://doi.org/10.1016/j.ejmech.2017.06.045
   PubMed Web of Science ®Google Scholar
• Dennington, R., Keith, T. A., & Millam, J. M. (2016). GaussView, Version 6. Semichem Inc., Shawnee Mission, KS.
   Google Scholar
• Desaphy, J.(2013). L'analyse structurale de complexes protéine/ligand et ses applications en chémogénomique. Sciences agricoles. Université de Strasbourg. Français. ⟨NNT : 2013STRAF029⟩.
   Google Scholar
• Di, L., & Kerns, E. H. (2016). Drug-like properties: Concepts, structure design and methods from ADME to toxicity optimization. Academic Press. https://doi.org/10.1016/C2013-0-18378-X
   Google Scholar
• Domingo, L. R., Pérez, P., & Sáez, J. A. (2013). Understanding the local reactivity in polar organic reactions through electrophilic and nucleophilic Parr functions. RSC Advances, 3(5), 1486–1494. https://doi.org/10.1039/C2RA22886F
   Web of Science ®Google Scholar
• Dong, J., Wang, N. N., Yao, Z. J., Zhang, L., Cheng, Y., Ouyang, D., Lu, A. P., & Cao, D. S. (2018). Admetlab: A platform for systematic ADMET evaluation based on a comprehensively collected ADMET database. Journal of Cheminformatics, 10(1), 1–11. https://doi.org/10.1186/s13321-018-0283-x
   PubMedGoogle Scholar
• El Ayouchia, H., Ben Anane, H., El Idrissi Moubtassim, M. L., Domingo, L. R., Julve, M., & Stiriba, S. E. (2016). A theoretical study of the relationship between the electrophilicity ω index and hammett constant σp in [3 + 2] cycloaddition reactions of aryl azide/alkyne derivatives. Molecules, 21(11), 1434–1439. https://doi.org/10.3390/molecules21111434
   PubMed Web of Science ®Google Scholar
• Foster, R. T., Jamali, F., & Russell, A. S. (1989). Ketoprofen enantiomers in synovial fluid. Journal of Pharmaceutical Sciences, 78(10), 881–882. https://doi.org/10.1002/jps.2600781021
   PubMed Web of Science ®Google Scholar
• Frisch, M. J., Trucks, G. W., Schlegel, H. B., Scuseria, G. E., Robb, M. A., Cheeseman, J. R., Scalmani, G., Barone, V., Mennucci, B., Petersson, G. A., Nakatsuji, H., Caricato, M., Li, X., Hratchian, H. P., Izmaylov, A. F., Bloino, J., Zheng, G., Sonnenberg, J. L., Hada, M., … Fox, D. J. (2009). Gaussian 09. Gaussian, Inc.
   Google Scholar
• Geerlings, P., De Proft, F., & Langenaeker, W. (2003). Conceptual density functional theory. Chemical Reviews, 103(5), 1793–1873. https://doi.org/10.1021/cr990029p
   PubMed Web of Science ®Google Scholar
• Ghose, A. K., Viswanadhan, V. N., & Wendoloski, J. J. (1999). A knowledge-based approach in designing combinatorial or medicinal chemistry libraries for drug discovery. 1. A qualitative and quantitative characterization of known drug databases. Journal of Combinatorial Chemistry, 1(1), 55–68. https://doi.org/10.1021/cc9800071
   PubMedGoogle Scholar
• Giessen, J. (2000). Pharmacological basis for the therapy of pain and inflammation with nonsteroidal anti-inflammatory drugs Jürgen Steinmeyer. Arthritis Research, 2(5), 379–385. https://doi.org/10.1186/ar116
   Google Scholar
• Hassan, S. S., Shah, S. A. A., Pan, C., Fu, L., Cao, X., Shi, Y., Wu, X., Wang, K., & Wu, B. (2017). Production of an antibiotic enterocin from a marine actinobacteria strain H1003 by metal-stress technique with enhanced enrichment using response surface methodology. Pakistan Journal of Pharmaceutical Sciences, 30(1 Suppl), 313–324.
   PubMed Web of Science ®Google Scholar
• Hassan, S. S. U., & Shaikh, A. L. (2017). Marine actinobacteria as a drug treasure house. Biomedicine & Pharmacotherapy = Biomedecine & Pharmacotherapie, 87, 46–57. https://doi.org/10.1016/j.biopha.2016.12.086
   PubMed Web of Science ®Google Scholar
• Howard, A., McIver, J., & Collins, J. (1994). Hyperchem computational chemistry. Hypercube Inc. Waterloo.
   Google Scholar
• Jamali, F., & Brocks, D. R. (1990). Clinical pharmacokinetics of ketoprofen and its enantiomers. Clinical Pharmacokinetics, 19(3), 197–217. https://doi.org/10.2165/00003088-199019030-00004
   PubMed Web of Science ®Google Scholar
• Jamali, F., Lovlin, R., & Aberg, G. (1997). Bi-directional chiral inversion of ketoprofen in CD-1 mice. Chirality, 9(1), 29–31. https://doi.org/10.1002/(SICI)1520-636X(1997)9:1<29::AID-CHIR6>3.0.CO;2-B
   PubMed Web of Science ®Google Scholar
• Jamali, F., Russell, A. S., Foster, R. T., & Lemko, C. (1990). Ketoprofen pharmacokinetics in humans: Evidence of enantiomeric inversion and lack of interaction. Journal of Pharmaceutical Sciences, 79(5), 460–461. https://doi.org/10.1002/jps.2600790522
   PubMed Web of Science ®Google Scholar
• Jonkers, J., & Berns, A. (1996). Retroviral insertional mutagenesis as a strategy to identify cancer genes. Biochimica Et Biophysica Acta (BBA) - Reviews on Cancer, 1287(1), 29–57. https://doi.org/10.1016/0304-419X(95)00020-G
   PubMed Web of Science ®Google Scholar
• Juillerat-Jeanneret, L., & Schmitt, F. (2007). Chemical modification of therapeutic drugs or drug vector systems to achieve targeted therapy: Looking for the grail. Medicinal Research Reviews, 27(4), 574–590. https://doi.org/10.1002/med.20086
   PubMed Web of Science ®Google Scholar
• Julou, B. Y. L., Guyonnet, J. C., Ducrot, R., & Pasquet, J. (1949). Section I : Pharmacology, toxicology and pharmacokinetics of ketoprofen some pharmacological and toxicological studies on ketoprofen. https://academic.oup.com/rheumatology/article-abstract/15/5/5/1780675?redirectedFrom=PDF
   Google Scholar
• Khan, I., Abbas, T., Anjum, K., Abbas, S. Q., Shagufta, B. I., Shah, S. A. A., Akhter, N., & Hassan, S. S. u (2019). Antimicrobial potential of aqueous extract of Camellia sinensis against representative microbes. Pakistan Journal of Pharmaceutical Sciences, 32(2), 631–636.
   PubMed Web of Science ®Google Scholar
• Khan, Y. S., Gutiérrez-De-Terán, H., & Åqvist, J. (2018). Molecular mechanisms in the selectivity of nonsteroidal anti-inflammatory drugs. Biochemistry, 57(7), 1236–1248. https://doi.org/10.1021/acs.biochem.7b01019
   PubMed Web of Science ®Google Scholar
• Khan, S. A., Imam, S. M., Ahmad, A., Basha, S. H., & Husain, A. (2018). Synthesis, molecular docking with COX 1& II enzyme, ADMET screening and in vivo anti-inflammatory activity of oxadiazole, thiadiazole and triazole analogs of felbinac. Journal of Saudi Chemical Society, 22(4), 469–484. https://doi.org/10.1016/j.jscs.2017.05.006
   Web of Science ®Google Scholar
• Kuczyńska, J., & Nieradko-Iwanicka, B. (2021). Future prospects of ketoprofen in improving the safety of the gastric mucosa. Biomedicine & Pharmacotherapy, 139, 111608. https://doi.org/10.1016/j.biopha.2021.111608
   PubMed Web of Science ®Google Scholar
• Kumar, N., Goel, N., Chand Yadav, T., & Pruthi, V. (2017). Quantum chemical, ADMET and molecular docking studies of ferulic acid amide derivatives with a novel anticancer drug target. Medicinal Chemistry Research, 26(8), 1822–1834. https://doi.org/10.1007/s00044-017-1893-y
   Web of Science ®Google Scholar
• Kumar, N., Gupta, S., Chand Yadav, T., Pruthi, V., Kumar Varadwaj, P., & Goel, N. (2019). Extrapolation of phenolic compounds as multi-target agents against cancer and inflammation. Journal of Biomolecular Structure & Dynamics, 37(9), 2355–2369. https://doi.org/10.1080/07391102.2018.1481457
   PubMed Web of Science ®Google Scholar
• Kurumbail, R. G., Stevens, A. M., Gierse, J. K., McDonald, J. J., Stegeman, R. A., Pak, J. Y., Gildehaus, D., Miyashiro, J. M., Penning, T. D., Seibert, K., Isakson, P. C., & Stallings, W. C. (1996). Structural basis for selective inhibition of cyciooxygenase-2 by anti-inflammatory agents. Nature, 384(6610), 644–648. https://doi.org/10.1038/384644a0
   PubMed Web of Science ®Google Scholar
• Lanas, A., Bresalier, R., Sandler, R., Bolognese, J., Quan, H., Oxenius, B., Horgan, K., Riddell, R., Morton, D., & Baron, J. (2005). Upper gastrointestinal events associated with rofecoxib in a colorectal adenoma chemoprevention trial. Gastroenterology, 129(1), 371. https://doi.org/10.1053/j.gastro.2005.05.061
   Google Scholar
• Lei, T., Li, Y., Song, Y., Li, D., Sun, H., & Hou, T. (2016). ADMET evaluation in drug discovery: 15. Accurate prediction of rat oral acute toxicity using relevance vector machine and consensus modeling. Journal of Cheminformatics, 8(1), 6–19. https://doi.org/10.1186/s13321-016-0117-7
   PubMedGoogle Scholar
• Li, X. Q., Andersson, T. B., Ahlström, M., & Weidolf, L. (2004). Comparison of inhibitory effects of the proton pump-inhibiting drugs omeprazole, esomeprazole, lansoprazole, pantoprazole, and rabeprazole on human cytochrome P450 activities. Drug Metabolism and Disposition: The Biological Fate of Chemicals, 32(8), 821–827. https://doi.org/10.1124/dmd.32.8.821
   PubMed Web of Science ®Google Scholar
• Lipinski, C. A., Lombardo, F., Dominy, B. W., & Feeney, P. J. (2012). Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Advanced Drug Delivery Reviews, 64(SUPPL), 4–17. https://doi.org/10.1016/j.addr.2012.09.019
   Google Scholar
• Lu, G., Tsai, A. L., Van Wart, H. E., & Kulmacz, R. J. (1999). Comparison of the peroxidase reaction kinetics of prostaglandin H synthase-1 and -2. The Journal of Biological Chemistry, 274(23), 16162–16167. https://doi.org/10.1074/jbc.274.23.16162
   PubMed Web of Science ®Google Scholar
• Lucas, S. M., Rothwell, N. J., & Gibson, R. M. (2006). The role of inflammation in CNS injury and disease. British Journal of Pharmacology, 147(S1), S232–S240. https://doi.org/10.1038/sj.bjp.0706400
   PubMedGoogle Scholar
• Lucido, M. J., Orlando, B. J., Vecchio, A. J., & Malkowski, M. G. (2016). Crystal structure of aspirin-acetylated human cyclooxygenase-2: Insight into the formation of products with reversed stereochemistry. Biochemistry, 55(8), 1226–1238. https://doi.org/10.1021/acs.biochem.5b01378
   PubMed Web of Science ®Google Scholar
• Masferrer, J. L., Zweifel, B. S., Manning, P. T., Hauser, S. D., Leahy, K. M., Smith, W. G., Isakson, P. C., & Seibert, K. (1994). Selective inhibition of inducible cyclooxygenase 2 in vivo is antiinflammatory and nonulcerogenic. Proceedings of the National Academy of Sciences of the United States of America, 91(8), 3228–3232. https://doi.org/10.1073/pnas.91.8.3228
   PubMed Web of Science ®Google Scholar
• Mazumder, K., Hossain Md, E., Aktar, A., Mohiuddin, M., Sarkar, K. K., Biswas, B., Aziz Md, A., Abid Md, A., & Fukase, K. (2021). In silico analysis and experimental evaluation of ester prodrugs of ketoprofen for oral delivery: With a view to reduce toxicity. Processes, 9(12), 2221. https://doi.org/10.3390/pr9122221
   Web of Science ®Google Scholar
• Scott, D., Solomon, M. D., John, J.V., McMurray, M.D., Marc A. Pfeffer, M. D., Janet Wittes, Robert Fowler, Peter Finn, William F. Anderson, Ann Zauber, Ernest Hawk, & Monica Bertagnolli, (2005). Cardiovascular risk associated with celecoxib in a clinical trial for colorectal adenoma prevention. New England Journal of Medicine, 352(11), 1071-1080. https://doi.org/10.1056/nejmoa050405
   Google Scholar
• Miciaccia, M., Belviso, B. D., Iaselli, M., Cingolani, G., Ferorelli, S., Cappellari, M., Loguercio Polosa, P., Perrone, M. G., Caliandro, R., & Scilimati, A. (2021). Three-dimensional structure of human cyclooxygenase (hCOX)-1. Scientific Reports, 11(1), 1–18. https://doi.org/10.1038/s41598-021-83438-z
   PubMed Web of Science ®Google Scholar
• Muller, N., Payan, E., Lapicque, F., Bannwarth, B., & Netter, P. (1990). Pharmacological aspects of chiral nonsteroidal anti‐inflammatory drugs. Fundamental & Clinical Pharmacology, 4(6), 617–634. https://doi.org/10.1111/j.1472-8206.1990.tb00042.x
   PubMed Web of Science ®Google Scholar
• Nussmeier, N. A., Whelton, A. A., Brown, M. T., Langford, R. M., Hoeft, A., Parlow, J. L., Boyce, S. W., & Verburg, K. M. (2005). Complications of the COX-2 inhibitors parecoxib and valdecoxib after cardiac surgery. The New England Journal of Medicine, 352(11), 1081–1091. https://doi.org/10.1056/nejmoa050330
   PubMed Web of Science ®Google Scholar
• Oprea, T. I. (2000). Property distribution of drug-related chemical databases. Journal of Computer-Aided Molecular Design, 14(3), 251–264. https://doi.org/10.1023/A:1008130001697
   PubMed Web of Science ®Google Scholar
• Palareti, G., Legnani, C., Cosmi, B., Antonucci, E., Erba, N., Poli, D., Testa, S., & Tosetto, A., DULCIS (D-dimer-ULtrasonography in Combination Italian Study) Investigators. (2016). Comparison between different D-Dimer cutoff values to assess the individual risk of recurrent venous thromboembolism: Analysis of results obtained in the DULCIS study. International Journal of Laboratory Hematology, 38(1), 42–49. (https://doi.org/10.1111/ijlh.12426
   PubMed Web of Science ®Google Scholar
• Pan, C., Shi, Y., Auckloo, B. N., Hassan, S. S., Ul Akhter, N., Wang, K., Ye, Y., Arthur Chen, C. T., Tao, X., & Wu, B. (2017). Isolation and antibiotic screening of fungi from a hydrothermal vent site and characterization of secondary metabolites from a penicillium isolate. Marine Biotechnology (New York, NY), 19(5), 469–479. https://doi.org/10.1007/s10126-017-9765-5
   PubMed Web of Science ®Google Scholar
• Pardridge, W. M. (1998). CNS drug design based on principles of blood-brain barrier transport. Journal of Neurochemistry, 70(5), 1781–1792. https://doi.org/10.1046/j.1471-4159.1998.70051781.x
   PubMed Web of Science ®Google Scholar
• Pawlędzio, S., Makal, A., Trzybiński, D., & Woźniak, K. (2018). Crystal structure, interaction energies and experimental electron density of the popular drug ketoprophen. IUCrJ, 5(Pt 6), 841–853. https://doi.org/10.1107/S2052252518013222
   PubMedGoogle Scholar
• Pettersen, E. F., Goddard, T. D., Huang, C. C., Couch, G. S., Greenblatt, D. M., Meng, E. C., & Ferrin, T. E. (2004). UCSF Chimera—a visualization system for exploratory research and analysis. Journal of Computational Chemistry, 25(13), 1605–1612. https://doi.org/10.1002/jcc.20084
   PubMed Web of Science ®Google Scholar
• Rahman, A., Hoque, M. M., Khan, M. A. K., Sarwar, M. G., & Halim, M. A. (2016). Non-covalent interactions involving halogenated derivatives of capecitabine and thymidylate synthase: a computational approach. SpringerPlus, 5(1), 1–18. https://doi.org/10.1186/s40064-016-1844-y
   PubMedGoogle Scholar
• Rausch, M. P., & Hastings, K. T. (2019). Innate and adaptive immune responses to cancer. Fundamentals of Cancer Prevention: Fourth Edition, 243, 111–159. https://doi.org/10.1007/978-3-030-15935-1_5
   Google Scholar
• Rençber, S., Karavana, S. Y., & Özyazici, M. (2009). Bioavailability file: Ketoprofen. Fabad Journal of Pharmaceutical Sciences, 34(4), 203–216.
   Google Scholar
• Rossi, P., Paoli, P., Ienco, A., Biagi, D., Valleri, M., & Conti, L. (2019). A new crystal form of the NSAID dexketoprofen. Acta Crystallographica. Section C, Structural Chemistry, 75(Pt 6), 783–792. https://doi.org/10.1107/S2053229619006533
   PubMedGoogle Scholar
• Rostkowski, M., Spjuth, O., & Rydberg, P. (2013). WhichCyp: Prediction of cytochromes P450 inhibition. Bioinformatics (Oxford, England), 29(16), 2051–2052. https://doi.org/10.1093/bioinformatics/btt325
   PubMed Web of Science ®Google Scholar
• Rudy, A. C., Liu, Y., Brater, D. C., & Hall, S. D. (1998). Stereoselective pharmacokinetics and inversion of (R)- ketoprofen in healthy volunteers. Journal of Clinical Pharmacology, 38(2 SUPPL), 3–10. https://doi.org/10.1002/j.1552-4604.1998.tb04411.x
   PubMed Web of Science ®Google Scholar
• BIOVIA, Dassault Systemes. BIOVIA discovery studio. Dassault Systèmes, 2020.
   Google Scholar
• Sanguinetti, M. C., & Mitcheson, J. S. (2005). Predicting drug-hERG channel interactions that cause acquired long QT syndrome. Trends in Pharmacological Sciences, 26(3), 119–124. https://doi.org/10.1016/j.tips.2005.01.003
   PubMed Web of Science ®Google Scholar
• Schneider, V., Lévesque, L. E., Zhang, B., Hutchinson, T., & Brophy, J. M. (2006). Association of selective and conventional nonsteroidal antiinflammatory drugs with acute renal failure: A population-based, nested case-control analysis. American Journal of Epidemiology, 164(9), 881–889. https://doi.org/10.1093/aje/kwj331
   PubMed Web of Science ®Google Scholar
• Seibert, K., Zhang, Y., Leahy, K., Hauser, S., Masferrer, J., Perkins, W., Lee, L., & Isakson, P. (1994). Pharmacological and biochemical demonstration of the role of cyclooxygenase 2 in inflammation and pain. Proceedings of the National Academy of Sciences of the United States of America, 91(25), 12013–12017. https://doi.org/10.1073/pnas.91.25.12013
   PubMed Web of Science ®Google Scholar
• Tajani, A., Jangi, E., Davodi, M., Golmakaniyoon, S., Ghodsi, R., Soheili, V., & Bazzaz, B. S. F. (2021). Anti‑quorum sensing potential of ketoprofen and its derivatives against Pseudomonas aeruginosa: insights to in silico and in vitro studies. Archives of Microbiology, 203(8), 5123–5132. https://doi.org/10.1007/s00203-021-02499-w
   PubMed Web of Science ®Google Scholar
• Tian, S., Li, Y., Wang, J., Zhang, J., & Hou, T. (2011). ADME evaluation in drug discovery. 9. Prediction of oral bioavailability in humans based on molecular properties and structural fingerprints. Molecular Pharmaceutics, 8(3), 841–851. https://doi.org/10.1021/mp100444g
   PubMed Web of Science ®Google Scholar
• Trott, O., & Olson, A. J. (2010). AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. Journal of Computational Chemistry, 31(2), 455–461. https://doi.org/10.1002/jcc.21334
   PubMed Web of Science ®Google Scholar
• Tziona, P., Theodosis-Nobelos, P., Papagiouvannis, G., Petrou, A., Drouza, C. A., & Rekka, E. (2022). Enhancement of the anti-inflammatory activity of NSAIDs by their conjugation with 3,4,5-trimethoxybenzyl alcohol. Molecules, 27(7), 2104. https://doi.org/10.3390/molecules27072104
   PubMed Web of Science ®Google Scholar
• Uzzaman, M., & Uddin, M. N. (2019). Optimization of structures, biochemical properties of ketorolac and its degradation products based on computational studies. Daru: Journal of Faculty of Pharmacy, Tehran University of Medical Sciences, 27(1), 71–82. https://doi.org/10.1007/s40199-019-00243-w
   PubMed Web of Science ®Google Scholar
• Varma, M. V. S., Obach, R. S., Rotter, C., Miller, H. R., Chang, G., Steyn, S. J., El-Kattan, A., & Troutman, M. D. (2010). Physicochemical space for optimum oral bioavailability: Contribution of human intestinal absorption and first-pass elimination. Journal of Medicinal Chemistry, 53(3), 1098–1108. https://doi.org/10.1021/jm901371v
   PubMed Web of Science ®Google Scholar
• Veber, D. F., Johnson, S. R., Cheng, H. Y., Smith, B. R., Ward, K. W., & Kopple, K. D. (2002). Molecular properties that influence the oral bioavailability of drug candidates. Journal of Medicinal Chemistry, 45(12), 2615–2623. https://doi.org/10.1021/jm020017n
   PubMed Web of Science ®Google Scholar
• Veith, H., Southall, N., Huang, R., James, T., Fayne, D., Artemenko, N., Shen, M., Inglese, J., Austin, C. P., Lloyd, D. G., & Auld, D. S. (2009). Comprehensive characterization of cytochrome P450 isozyme selectivity across chemical libraries. Nature Biotechnology, 27(11), 1050–1055. https://doi.org/10.1038/nbt.1581
   PubMed Web of Science ®Google Scholar
• Waisman, A., Liblau, R. S., & Becher, B. (2015). Innate and adaptive immune responses in the CNS. The Lancet. Neurology, 14(9), 945–955. https://doi.org/10.1016/S1474-4422(15)00141-6
   PubMed Web of Science ®Google Scholar
• Wang, N. N., Dong, J., Deng, Y. H., Zhu, M. F., Wen, M., Yao, Z. J., Lu, A. P., Wang, J. B., & Cao, D. S. (2016). ADME properties evaluation in drug discovery: Prediction of Caco-2 cell permeability using a combination of NSGA-II and boosting. Journal of Chemical Information and Modeling, 56(4), 763–773. https://doi.org/10.1021/acs.jcim.5b00642
   PubMed Web of Science ®Google Scholar
• Wang, N. N., Huang, C., Dong, J., Yao, Z. J., Zhu, M. F., Deng, Z. K., Lv, B., Lu, A. P., Chen, A. F., & Cao, D. S. (2017). Predicting human intestinal absorption with modified random forest approach: A comprehensive evaluation of molecular representation, unbalanced data, and applicability domain issues. RSC Advances, 7(31), 19007–19018. https://doi.org/10.1039/C6RA28442F
   Web of Science ®Google Scholar
• Wang, S., Sun, H., Liu, H., Li, D., Li, Y., & Hou, T. (2016). ADMET evaluation in drug discovery. 16. Predicting hERG blockers by combining multiple pharmacophores and machine learning approaches. Molecular Pharmaceutics, 13(8), 2855–2866. https://doi.org/10.1021/acs.molpharmaceut.6b00471
   PubMed Web of Science ®Google Scholar
• Winkelmayer, W. C., Waikar, S. S., Mogun, H., & Solomon, D. H. (2008). Nonselective and cyclooxygenase-2-selective NSAIDs and acute kidney injury. The American Journal of Medicine, 121(12), 1092–1098. https://doi.org/10.1016/j.amjmed.2008.06.035
   PubMed Web of Science ®Google Scholar
• Xu, C., Cheng, F., Chen, L., Du, Z., Li, W., Liu, G., Lee, P. W., & Tang, Y. (2012). In silico prediction of chemical ames mutagenicity. Journal of Chemical Information and Modeling, 52(11), 2840–2847. https://doi.org/10.1021/ci300400a
   PubMed Web of Science ®Google Scholar
• Zaretzki, J., Matlock, M., & Swamidass, S. J. (2013). XenoSite: Accurately predicting cyp-mediated sites of metabolism with neural networks. Journal of Chemical Information and Modeling, 53(12), 3373–3383. https://doi.org/10.1021/ci400518g
   PubMed Web of Science ®Google Scholar
• Zhu, H., Martin, T. M., Ye, L., Sedykh, A., Young, D. M., & Tropsha, A. (2009). Quantitative structure-activity relationship modeling of rat acute toxicity by oral exposure. Chemical Research in Toxicology, 22(12), 1913–1921. https://doi.org/10.1021/tx900189p
   PubMed Web of Science ®Google Scholar