Alexander Tropsha - Publications

Affiliations: 
Biomedical Engineering (Joint) University of North Carolina, Chapel Hill, Chapel Hill, NC 
Area:
Biomedical Engineering, Bioinformatics Biology, Pharmacy

201 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2018 Low Y, Alves VM, Fourches D, Sedykh A, Andrade CH, Muratov EN, Rusyn I, Tropsha A. Chemistry-Wide Association Studies (CWAS): A Novel Framework for Identifying and Interpreting Structure-Activity Relationships. Journal of Chemical Information and Modeling. PMID 30376324 DOI: 10.1021/acs.jcim.8b00450  0.4
2018 La MK, Sedykh A, Fourches D, Muratov E, Tropsha A. Predicting Adverse Drug Effects from Literature- and Database-Mined Assertions. Drug Safety. PMID 29876834 DOI: 10.1007/s40264-018-0688-5  0.4
2018 Wignall JA, Muratov E, Sedykh A, Guyton KZ, Tropsha A, Rusyn I, Chiu WA. Conditional Toxicity Value (CTV) Predictor: An Approach for Generating Quantitative Risk Estimates for Chemicals. Environmental Health Perspectives. 126: 057008. PMID 29847084 DOI: 10.1289/EHP2998  0.4
2018 Alves VM, Golbraikh A, Capuzzi SJ, Liu K, Lam WI, Korn D, Pozefsky D, Andrade CH, Muratov EN, Tropsha A. Multi-Descriptor Read Across (MuDRA): a simple and transparent approach for developing accurate QSAR models. Journal of Chemical Information and Modeling. PMID 29809005 DOI: 10.1021/acs.jcim.8b00124  0.64
2018 Capuzzi SJ, Sun W, Muratov EN, Martinez-Romero C, He S, Zhu W, Li H, Tawa GJ, Fisher EG, Xu M, Shinn P, Qiu X, García-Sastre A, Zheng W, Tropsha A. Computer-Aided Discovery and Characterization of Novel Ebola Virus Inhibitors. Journal of Medicinal Chemistry. PMID 29624387 DOI: 10.1021/acs.jmedchem.8b00035  0.4
2018 Capuzzi SJ, Thornton T, Liu K, Baker N, Lam WI, O'Banion C, Muratov EN, Pozefsky D, Tropsha A. Chemotext: A Publicly-Available Web Server for Mining Drug-Target-Disease Relationships in PubMed. Journal of Chemical Information and Modeling. PMID 29300482 DOI: 10.1021/acs.jcim.7b00589  0.4
2017 Capuzzi SJ, Kim IS, Lam WI, Thornton TE, Muratov EN, Pozefsky D, Tropsha A. Chembench: A Publicly-Accessible, Integrated Cheminformatics Portal. Journal of Chemical Information and Modeling. PMID 28045544 DOI: 10.1021/acs.jcim.6b00462  0.4
2016 Alves V, Muratov E, Capuzzi S, Politi R, Low Y, Braga R, Zakharov AV, Sedykh A, Mokshyna E, Farag S, Andrade C, Kuz'min V, Fourches D, Tropsha A. Alarms about structural alerts. Green Chemistry : An International Journal and Green Chemistry Resource : Gc. 18: 4348-4360. PMID 28503093 DOI: 10.1039/C6GC01492E  0.4
2016 Luo M, Wang XS, Tropsha A. Comparative Analysis of QSAR-based vs. Chemical Similarity Based Predictors of GPCRs Binding Affinity. Molecular Informatics. 35: 36-41. PMID 27491652 DOI: 10.1002/minf.201500038  1
2016 Politi R, Convertino M, Popov K, Dokholyan NV, Tropsha A. Docking and Scoring With Target-Specific Pose Classifier Succeeds in Native-Like Pose Identification But Not Binding Affinity Prediction In The CSAR 2014 Benchmark Exercise. Journal of Chemical Information and Modeling. PMID 27050767 DOI: 10.1021/acs.jcim.5b00751  0.4
2016 Mansouri K, Abdelaziz A, Rybacka A, Roncaglioni A, Tropsha A, Varnek A, Zakharov A, Worth A, Richard AM, Grulke CM, Trisciuzzi D, Fourches D, Horvath D, Benfenati E, Muratov E, et al. CERAPP: Collaborative Estrogen Receptor Activity Prediction Project. Environmental Health Perspectives. PMID 26908244 DOI: 10.1289/ehp.1510267  0.92
2016 Tropsha A, Bajorath J. Computational Methods for Drug Discovery and Design. Journal of Medicinal Chemistry. 59: 1. PMID 26716466 DOI: 10.1021/acs.jmedchem.5b01945  0.92
2016 Zakharov AV, Varlamova EV, Lagunin AA, Dmitriev AV, Muratov EN, Fourches D, Kuz'min VE, Poroikov VV, Tropsha A, Nicklaus MC. QSAR Modeling and Prediction of Drug-Drug Interactions. Molecular Pharmaceutics. PMID 26669717 DOI: 10.1021/acs.molpharmaceut.5b00762  0.92
2016 Luo M, Wang XS, Tropsha A. Comparative Analysis of QSAR-based vs. Chemical Similarity Based Predictors of GPCRs Binding Affinity Molecular Informatics. 35: 36-41. DOI: 10.1002/minf.201500038  1
2016 Borysov P, Hannig J, Marron JS, Muratov E, Fourches D, Tropsha A. Activity prediction and identification of mis-annotated chemical compounds using extreme descriptors Journal of Chemometrics. 30: 99-108. DOI: 10.1002/cem.2776  0.92
2015 Fourches D, Pu D, Li L, Zhou H, Mu Q, Su G, Yan B, Tropsha A. Computer-aided design of carbon nanotubes with the desired bioactivity and safety profiles. Nanotoxicology. 1-10. PMID 26525350 DOI: 10.3109/17435390.2015.1073397  0.92
2015 Elkins JM, Fedele V, Szklarz M, Abdul Azeez KR, Salah E, Mikolajczyk J, Romanov S, Sepetov N, Huang XP, Roth BL, Al Haj Zen A, Fourches D, Muratov E, Tropsha A, Morris J, et al. Comprehensive characterization of the Published Kinase Inhibitor Set. Nature Biotechnology. PMID 26501955 DOI: 10.1038/nbt.3374  0.92
2015 Fourches D, Muratov E, Tropsha A. Curation of chemogenomics data. Nature Chemical Biology. 11: 535. PMID 26196763 DOI: 10.1038/nchembio.1881  0.92
2015 Alexander DL, Tropsha A, Winkler DA. Beware of R(2): Simple, Unambiguous Assessment of the Prediction Accuracy of QSAR and QSPR Models. Journal of Chemical Information and Modeling. 55: 1316-22. PMID 26099013 DOI: 10.1021/acs.jcim.5b00206  0.92
2015 Wambaugh JF, Wetmore BA, Pearce R, Strope C, Goldsmith R, Sluka JP, Sedykh A, Tropsha A, Bosgra S, Shah I, Judson R, Thomas RS, Setzer RW. Toxicokinetic Triage for Environmental Chemicals. Toxicological Sciences : An Official Journal of the Society of Toxicology. PMID 26085347 DOI: 10.1093/toxsci/kfv118  0.92
2015 Merz KM, Rarey M, Tropsha A, Wahab HA. Letter from the editors. Journal of Chemical Information and Modeling. 55: 719-20. PMID 25912660 DOI: 10.1021/acs.jcim.5b00180  0.92
2015 Alves VM, Muratov E, Fourches D, Strickland J, Kleinstreuer N, Andrade CH, Tropsha A. Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds. Toxicology and Applied Pharmacology. 284: 262-72. PMID 25560674 DOI: 10.1016/j.taap.2014.12.014  0.92
2015 Alves VM, Muratov E, Fourches D, Strickland J, Kleinstreuer N, Andrade CH, Tropsha A. Predicting chemically-induced skin reactions. Part II: QSAR models of skin permeability and the relationships between skin permeability and skin sensitization. Toxicology and Applied Pharmacology. 284: 273-80. PMID 25560673 DOI: 10.1016/j.taap.2014.12.013  0.92
2015 Fourches D, Politi R, Tropsha A. Target-specific native/decoy pose classifier improves the accuracy of ligand ranking in the CSAR 2013 benchmark. Journal of Chemical Information and Modeling. 55: 63-71. PMID 25521713 DOI: 10.1021/ci500519w  0.92
2015 Isayev O, Fourches D, Muratov EN, Oses C, Rasch K, Tropsha A, Curtarolo S. Materials cartography: Representing and mining materials space using structural and electronic fingerprints Chemistry of Materials. 27: 735-743. DOI: 10.1021/cm503507h  0.92
2015 Braga RC, Alves VM, Silva MFB, Muratov E, Fourches D, Lião LM, Tropsha A, Andrade CH. Pred-hERG: A Novel web-Accessible Computational Tool for Predicting Cardiac Toxicity Molecular Informatics. 34: 698-701. DOI: 10.1002/minf.201500040  0.92
2015 Baker NC, Fourches D, Tropsha A. Drug Side Effect Profiles as Molecular Descriptors for Predictive Modeling of Target Bioactivity Molecular Informatics. DOI: 10.1002/minf.201400134  0.92
2014 Khashan R, Zheng W, Tropsha A. The Development of Novel Chemical Fragment-Based Descriptors Using Frequent Common Subgraph Mining Approach and Their Application in QSAR Modeling. Molecular Informatics. 33: 201-15. PMID 27485689 DOI: 10.1002/minf.201300165  0.4
2014 Goldstein JI, Jarskog LF, Hilliard C, Alfirevic A, Duncan L, Fourches D, Huang H, Lek M, Neale BM, Ripke S, Shianna K, Szatkiewicz JP, Tropsha A, van den Oord EJ, Cascorbi I, et al. Clozapine-induced agranulocytosis is associated with rare HLA-DQB1 and HLA-B alleles. Nature Communications. 5: 4757. PMID 25187353 DOI: 10.1038/ncomms5757  0.92
2014 Blatt J, Farag S, Corey SJ, Sarrimanolis Z, Muratov E, Fourches D, Tropsha A, Janzen WP. Expanding the scope of drug repurposing in pediatrics: the Children's Pharmacy Collaborative. Drug Discovery Today. 19: 1696-8. PMID 25149597 DOI: 10.1016/j.drudis.2014.08.003  0.92
2014 Politi R, Rusyn I, Tropsha A. Prediction of binding affinity and efficacy of thyroid hormone receptor ligands using QSAR and structure-based modeling methods. Toxicology and Applied Pharmacology. 280: 177-89. PMID 25058446 DOI: 10.1016/j.taap.2014.07.009  0.92
2014 Mu Q, Jiang G, Chen L, Zhou H, Fourches D, Tropsha A, Yan B. Chemical basis of interactions between engineered nanoparticles and biological systems. Chemical Reviews. 114: 7740-81. PMID 24927254 DOI: 10.1021/cr400295a  0.92
2014 Low YS, Sedykh AY, Rusyn I, Tropsha A. Integrative approaches for predicting in vivo effects of chemicals from their structural descriptors and the results of short-term biological assays. Current Topics in Medicinal Chemistry. 14: 1356-64. PMID 24805064 DOI: 10.2174/1568026614666140506121116  0.92
2014 Braga RC, Alves VM, Silva MF, Muratov E, Fourches D, Tropsha A, Andrade CH. Tuning HERG out: antitarget QSAR models for drug development. Current Topics in Medicinal Chemistry. 14: 1399-415. PMID 24805060 DOI: 10.2174/1568026614666140506124442  0.92
2014 Thompson CG, Sedykh A, Nicol MR, Muratov E, Fourches D, Tropsha A, Kashuba AD. Short communication: cheminformatics analysis to identify predictors of antiviral drug penetration into the female genital tract. Aids Research and Human Retroviruses. 30: 1058-64. PMID 24512359 DOI: 10.1089/AID.2013.0254  0.92
2014 Luo M, Wang XS, Roth BL, Golbraikh A, Tropsha A. Application of quantitative structure-activity relationship models of 5-HT1A receptor binding to virtual screening identifies novel and potent 5-HT1A ligands. Journal of Chemical Information and Modeling. 54: 634-47. PMID 24410373 DOI: 10.1021/ci400460q  0.92
2014 Fourches D, Sassano MF, Roth BL, Tropsha A. HTS navigator: freely accessible cheminformatics software for analyzing high-throughput screening data. Bioinformatics (Oxford, England). 30: 588-9. PMID 24376084 DOI: 10.1093/bioinformatics/btt718  0.92
2014 Cherkasov A, Muratov EN, Fourches D, Varnek A, Baskin II, Cronin M, Dearden J, Gramatica P, Martin YC, Todeschini R, Consonni V, Kuz'min VE, Cramer R, Benigni R, Yang C, ... ... Tropsha A, et al. QSAR modeling: where have you been? Where are you going to? Journal of Medicinal Chemistry. 57: 4977-5010. PMID 24351051 DOI: 10.1021/jm4004285  0.92
2014 Nile AH, Tripathi A, Yuan P, Mousley CJ, Suresh S, Wallace IM, Shah SD, Pohlhaus DT, Temple B, Nislow C, Giaever G, Tropsha A, Davis RW, St Onge RP, Bankaitis VA. PITPs as targets for selectively interfering with phosphoinositide signaling in cells. Nature Chemical Biology. 10: 76-84. PMID 24292071 DOI: 10.1038/nchembio.1389  0.92
2014 Golbraikh A, Muratov E, Fourches D, Tropsha A. Data set modelability by QSAR. Journal of Chemical Information and Modeling. 54: 1-4. PMID 24251851 DOI: 10.1021/ci400572x  0.92
2014 Cern A, Barenholz Y, Tropsha A, Goldblum A. Computer-aided design of liposomal drugs: In silico prediction and experimental validation of drug candidates for liposomal remote loading. Journal of Controlled Release : Official Journal of the Controlled Release Society. 173: 125-31. PMID 24184343 DOI: 10.1016/j.jconrel.2013.10.029  0.92
2014 Khashan R, Zheng W, Tropsha A. The development of novel chemical fragment-based descriptors using frequent common subgraph mining approach and their application in QSAR modeling Molecular Informatics. 33: 201-215. DOI: 10.1002/minf.201300165  0.92
2013 May EE, Leitão A, Tropsha A, Oprea TI. A systems chemical biology study of malate synthase and isocitrate lyase inhibition in Mycobacterium tuberculosis during active and NRP growth. Computational Biology and Chemistry. 47: 167-80. PMID 24121675 DOI: 10.1016/j.compbiolchem.2013.07.002  0.92
2013 Low Y, Sedykh A, Fourches D, Golbraikh A, Whelan M, Rusyn I, Tropsha A. Integrative chemical-biological read-across approach for chemical hazard classification. Chemical Research in Toxicology. 26: 1199-208. PMID 23848138 DOI: 10.1021/tx400110f  0.92
2013 Fourches D, Muratov E, Ding F, Dokholyan NV, Tropsha A. Predicting binding affinity of CSAR ligands using both structure-based and ligand-based approaches. Journal of Chemical Information and Modeling. 53: 1915-22. PMID 23809015 DOI: 10.1021/ci400216q  0.92
2013 Zhang L, Sedykh A, Tripathi A, Zhu H, Afantitis A, Mouchlis VD, Melagraki G, Rusyn I, Tropsha A. Identification of putative estrogen receptor-mediated endocrine disrupting chemicals using QSAR- and structure-based virtual screening approaches. Toxicology and Applied Pharmacology. 272: 67-76. PMID 23707773 DOI: 10.1016/j.taap.2013.04.032  0.92
2013 Yang K, Köck K, Sedykh A, Tropsha A, Brouwer KL. An updated review on drug-induced cholestasis: mechanisms and investigation of physicochemical properties and pharmacokinetic parameters. Journal of Pharmaceutical Sciences. 102: 3037-57. PMID 23653385 DOI: 10.1002/jps.23584  0.92
2013 Zhu XW, Sedykh A, Zhu H, Liu SS, Tropsha A. The use of pseudo-equilibrium constant affords improved QSAR models of human plasma protein binding. Pharmaceutical Research. 30: 1790-8. PMID 23568522 DOI: 10.1007/s11095-013-1023-6  0.92
2013 Sedykh A, Fourches D, Duan J, Hucke O, Garneau M, Zhu H, Bonneau P, Tropsha A. Human intestinal transporter database: QSAR modeling and virtual profiling of drug uptake, efflux and interactions. Pharmaceutical Research. 30: 996-1007. PMID 23269503 DOI: 10.1007/s11095-012-0935-x  0.92
2013 Zhang L, Fourches D, Sedykh A, Zhu H, Golbraikh A, Ekins S, Clark J, Connelly MC, Sigal M, Hodges D, Guiguemde A, Guy RK, Tropsha A. Discovery of novel antimalarial compounds enabled by QSAR-based virtual screening. Journal of Chemical Information and Modeling. 53: 475-92. PMID 23252936 DOI: 10.1021/ci300421n  0.92
2013 Huang J, Huan J, Tropsha A, Dang J, Zhang H, Xiong M. Semantics-driven frequent data pattern mining on electronic health records for effective adverse drug event monitoring Proceedings - 2013 Ieee International Conference On Bioinformatics and Biomedicine, Ieee Bibm 2013. 608-611. DOI: 10.1109/BIBM.2013.6732567  0.92
2013 Fourches D, Tropsha A. Using graph indices for the analysis and comparison of chemical datasets Molecular Informatics. 32: 827-842. DOI: 10.1002/minf.201300076  0.92
2012 Martin TM, Harten P, Young DM, Muratov EN, Golbraikh A, Zhu H, Tropsha A. Does rational selection of training and test sets improve the outcome of QSAR modeling? Journal of Chemical Information and Modeling. 52: 2570-8. PMID 23030316 DOI: 10.1021/ci300338w  0.92
2012 Tropsha A. Recent trends in statistical QSAR modeling of environmental chemical toxicity. Exs. 101: 381-411. PMID 22945576 DOI: 10.1007/978-3-7643-8340-4_13  0.92
2012 Khashan R, Zheng W, Tropsha A. Scoring protein interaction decoys using exposed residues (SPIDER): a novel multibody interaction scoring function based on frequent geometric patterns of interfacial residues. Proteins. 80: 2207-17. PMID 22581643 DOI: 10.1002/prot.24110  0.92
2012 Hajjo R, Setola V, Roth BL, Tropsha A. Chemocentric informatics approach to drug discovery: identification and experimental validation of selective estrogen receptor modulators as ligands of 5-hydroxytryptamine-6 receptors and as potential cognition enhancers. Journal of Medicinal Chemistry. 55: 5704-19. PMID 22537153 DOI: 10.1021/jm2011657  0.92
2012 Rusyn I, Sedykh A, Low Y, Guyton KZ, Tropsha A. Predictive modeling of chemical hazard by integrating numerical descriptors of chemical structures and short-term toxicity assay data. Toxicological Sciences : An Official Journal of the Society of Toxicology. 127: 1-9. PMID 22387746 DOI: 10.1093/toxsci/kfs095  0.92
2012 Tang H, Wang XS, Hsieh JH, Tropsha A. Do crystal structures obviate the need for theoretical models of GPCRs for structure-based virtual screening? Proteins. 80: 1503-21. PMID 22275072 DOI: 10.1002/prot.24035  0.92
2012 Lock EF, Abdo N, Huang R, Xia M, Kosyk O, O'Shea SH, Zhou YH, Sedykh A, Tropsha A, Austin CP, Tice RR, Wright FA, Rusyn I. Quantitative high-throughput screening for chemical toxicity in a population-based in vitro model. Toxicological Sciences : An Official Journal of the Society of Toxicology. 126: 578-88. PMID 22268004 DOI: 10.1093/toxsci/kfs023  0.92
2012 Proctor EA, Yin S, Tropsha A, Dokholyan NV. Discrete molecular dynamics distinguishes nativelike binding poses from decoys in difficult targets. Biophysical Journal. 102: 144-51. PMID 22225808 DOI: 10.1016/j.bpj.2011.11.4008  0.92
2012 Cern A, Golbraikh A, Sedykh A, Tropsha A, Barenholz Y, Goldblum A. Quantitative structure-property relationship modeling of remote liposome loading of drugs. Journal of Controlled Release : Official Journal of the Controlled Release Society. 160: 147-57. PMID 22154932 DOI: 10.1016/j.jconrel.2011.11.029  0.92
2012 Hsieh JH, Yin S, Wang XS, Liu S, Dokholyan NV, Tropsha A. Cheminformatics meets molecular mechanics: a combined application of knowledge-based pose scoring and physical force field-based hit scoring functions improves the accuracy of structure-based virtual screening. Journal of Chemical Information and Modeling. 52: 16-28. PMID 22017385 DOI: 10.1021/ci2002507  0.92
2011 Samarov D, Marron JS, Liu Y, Grulke C, Tropsha A. LOCAL KERNEL CANONICAL CORRELATION ANALYSIS WITH APPLICATION TO VIRTUAL DRUG SCREENING. The Annals of Applied Statistics. 5: 2169-2196. PMID 22121408 DOI: 10.1214/11-AOAS472  0.92
2011 Fleishman SJ, Whitehead TA, Strauch EM, Corn JE, Qin S, Zhou HX, Mitchell JC, Demerdash ON, Takeda-Shitaka M, Terashi G, Moal IH, Li X, Bates PA, Zacharias M, Park H, ... ... Tropsha A, et al. Community-wide assessment of protein-interface modeling suggests improvements to design methodology. Journal of Molecular Biology. 414: 289-302. PMID 22001016 DOI: 10.1016/j.jmb.2011.09.031  0.92
2011 Hsieh JH, Yin S, Liu S, Sedykh A, Dokholyan NV, Tropsha A. Combined application of cheminformatics- and physical force field-based scoring functions improves binding affinity prediction for CSAR data sets. Journal of Chemical Information and Modeling. 51: 2027-35. PMID 21780807 DOI: 10.1021/ci200146e  0.92
2011 Low Y, Uehara T, Minowa Y, Yamada H, Ohno Y, Urushidani T, Sedykh A, Muratov E, Kuz'min V, Fourches D, Zhu H, Rusyn I, Tropsha A. Predicting drug-induced hepatotoxicity using QSAR and toxicogenomics approaches. Chemical Research in Toxicology. 24: 1251-62. PMID 21699217 DOI: 10.1021/tx200148a  0.92
2011 Fourches D, Pu D, Tropsha A. Exploring quantitative nanostructure-activity relationships (QNAR) modeling as a tool for predicting biological effects of manufactured nanoparticles. Combinatorial Chemistry & High Throughput Screening. 14: 217-25. PMID 21275889 DOI: 10.2174/138620711794728743  0.92
2011 Ebalunode JO, Zheng W, Tropsha A. Application of QSAR and shape pharmacophore modeling approaches for targeted chemical library design. Methods in Molecular Biology (Clifton, N.J.). 685: 111-33. PMID 20981521 DOI: 10.1007/978-1-60761-931-4_6  0.92
2011 Sedykh A, Zhu H, Tang H, Zhang L, Richard A, Rusyn I, Tropsha A. Use of in vitro HTS-derived concentration-response data as biological descriptors improves the accuracy of QSAR models of in vivo toxicity. Environmental Health Perspectives. 119: 364-70. PMID 20980217 DOI: 10.1289/ehp.1002476  0.92
2011 Oprea TI, May EE, Leitão A, Tropsha A. Computational systems chemical biology. Methods in Molecular Biology (Clifton, N.J.). 672: 459-88. PMID 20838980 DOI: 10.1007/978-1-60761-839-3_18  0.92
2011 Tropsha A, Golbraikh A, Cho WJ. Development of kNN QSAR models for 3-arylisoquinoline antitumor agents Bulletin of the Korean Chemical Society. 32: 2397-2404. DOI: 10.5012/bkcs.2011.32.7.2397  0.92
2010 Sushko I, Novotarskyi S, Körner R, Pandey AK, Cherkasov A, Li J, Gramatica P, Hansen K, Schroeter T, Müller KR, Xi L, Liu H, Yao X, Öberg T, Hormozdiari F, ... ... Tropsha A, et al. Applicability domains for classification problems: Benchmarking of distance to models for Ames mutagenicity set. Journal of Chemical Information and Modeling. 50: 2094-111. PMID 21033656 DOI: 10.1021/ci100253r  0.92
2010 Hajjo R, Grulke CM, Golbraikh A, Setola V, Huang XP, Roth BL, Tropsha A. Development, validation, and use of quantitative structure-activity relationship models of 5-hydroxytryptamine (2B) receptor ligands to identify novel receptor binders and putative valvulopathic compounds among common drugs. Journal of Medicinal Chemistry. 53: 7573-86. PMID 20958049 DOI: 10.1021/jm100600y  0.92
2010 Walker T, Grulke CM, Pozefsky D, Tropsha A. Chembench: a cheminformatics workbench. Bioinformatics (Oxford, England). 26: 3000-1. PMID 20889496 DOI: 10.1093/bioinformatics/btq556  0.92
2010 Fourches D, Pu D, Tassa C, Weissleder R, Shaw SY, Mumper RJ, Tropsha A. Quantitative nanostructure-activity relationship modeling. Acs Nano. 4: 5703-12. PMID 20857979 DOI: 10.1021/nn1013484  0.92
2010 Fourches D, Muratov E, Tropsha A. Trust, but verify: on the importance of chemical structure curation in cheminformatics and QSAR modeling research. Journal of Chemical Information and Modeling. 50: 1189-204. PMID 20572635 DOI: 10.1021/ci100176x  0.92
2010 Bandyopadhyay D, Huan J, Liu J, Prins J, Snoeyink J, Wang W, Tropsha A. Functional neighbors: inferring relationships between nonhomologous protein families using family-specific packing motifs. Ieee Transactions On Information Technology in Biomedicine : a Publication of the Ieee Engineering in Medicine and Biology Society. 14: 1137-43. PMID 20570776 DOI: 10.1109/TITB.2010.2053550  0.92
2010 Rodgers AD, Zhu H, Fourches D, Rusyn I, Tropsha A. Modeling liver-related adverse effects of drugs using knearest neighbor quantitative structure-activity relationship method. Chemical Research in Toxicology. 23: 724-32. PMID 20192250 DOI: 10.1021/tx900451r  0.92
2010 Fourches D, Barnes JC, Day NC, Bradley P, Reed JZ, Tropsha A. Cheminformatics analysis of assertions mined from literature that describe drug-induced liver injury in different species. Chemical Research in Toxicology. 23: 171-83. PMID 20014752 DOI: 10.1021/tx900326k  0.92
2010 Tropsha A. Best practices for QSAR model development, validation, and exploitation Molecular Informatics. 29: 476-488. DOI: 10.1002/minf.201000061  0.92
2009 Zhu H, Martin TM, Ye L, Sedykh A, Young DM, Tropsha A. Quantitative structure-activity relationship modeling of rat acute toxicity by oral exposure. Chemical Research in Toxicology. 22: 1913-21. PMID 19845371 DOI: 10.1021/tx900189p  0.92
2009 Zhu H, Ye L, Richard A, Golbraikh A, Wright FA, Rusyn I, Tropsha A. A novel two-step hierarchical quantitative structure-activity relationship modeling work flow for predicting acute toxicity of chemicals in rodents. Environmental Health Perspectives. 117: 1257-64. PMID 19672406 DOI: 10.1289/ehp.0800471  0.92
2009 Bandyopadhyay D, Huan J, Prins J, Snoeyink J, Wang W, Tropsha A. Identification of family-specific residue packing motifs and their use for structure-based protein function prediction: II. Case studies and applications. Journal of Computer-Aided Molecular Design. 23: 785-97. PMID 19548090 DOI: 10.1007/s10822-009-9277-0  0.92
2009 Bandyopadhyay D, Huan J, Prins J, Snoeyink J, Wang W, Tropsha A. Identification of family-specific residue packing motifs and their use for structure-based protein function prediction: I. Method development. Journal of Computer-Aided Molecular Design. 23: 773-84. PMID 19543979 DOI: 10.1007/s10822-009-9273-4  0.92
2009 Peterson YK, Wang XS, Casey PJ, Tropsha A. Discovery of geranylgeranyltransferase-I inhibitors with novel scaffolds by the means of quantitative structure-activity relationship modeling, virtual screening, and experimental validation. Journal of Medicinal Chemistry. 52: 4210-20. PMID 19537691 DOI: 10.1021/jm8013772  0.92
2009 Tang H, Wang XS, Huang XP, Roth BL, Butler KV, Kozikowski AP, Jung M, Tropsha A. Novel inhibitors of human histone deacetylase (HDAC) identified by QSAR modeling of known inhibitors, virtual screening, and experimental validation. Journal of Chemical Information and Modeling. 49: 461-76. PMID 19182860 DOI: 10.1021/ci800366f  0.92
2009 Ekins S, Tropsha A. A turning point for blood-brain barrier modeling. Pharmaceutical Research. 26: 1283-4. PMID 19165578 DOI: 10.1007/s11095-009-9832-3  0.92
2009 Tropsha A, Fourches D. Graph representation of molecular datasets: Applications to dataset visualization and comparison using graph indices Chemistry Central Journal. 3. DOI: 10.1186/1752-153X-3-S1-O9  0.92
2009 Williams AJ, Tkachenko V, Lipinski C, Tropsha A, Ekins S. Free online resources enabling crowd-sourced drug discovery Drug Discovery World. 11: 33-39.  0.92
2008 Tetko IV, Sushko I, Pandey AK, Zhu H, Tropsha A, Papa E, Oberg T, Todeschini R, Fourches D, Varnek A. Critical assessment of QSAR models of environmental toxicity against Tetrahymena pyriformis: focusing on applicability domain and overfitting by variable selection. Journal of Chemical Information and Modeling. 48: 1733-46. PMID 18729318 DOI: 10.1021/ci800151m  0.92
2008 Zhang L, Zhu H, Oprea TI, Golbraikh A, Tropsha A. QSAR modeling of the blood-brain barrier permeability for diverse organic compounds. Pharmaceutical Research. 25: 1902-14. PMID 18553217 DOI: 10.1007/s11095-008-9609-0  0.92
2008 Zhang S, Kaplan AH, Tropsha A. HIV-1 protease function and structure studies with the simplicial neighborhood analysis of protein packing method. Proteins. 73: 742-53. PMID 18498108 DOI: 10.1002/prot.22094  0.92
2008 Wang XS, Tang H, Golbraikh A, Tropsha A. Combinatorial QSAR modeling of specificity and subtype selectivity of ligands binding to serotonin receptors 5HT1E and 5HT1F. Journal of Chemical Information and Modeling. 48: 997-1013. PMID 18470978 DOI: 10.1021/ci700404c  0.92
2008 Zhu H, Rusyn I, Richard A, Tropsha A. Use of cell viability assay data improves the prediction accuracy of conventional quantitative structure-activity relationship models of animal carcinogenicity. Environmental Health Perspectives. 116: 506-13. PMID 18414635 DOI: 10.1289/ehp.10573  0.92
2008 Karthikeyan M, Krishnan S, Pandey AK, Bender A, Tropsha A. Distributed chemical computing using ChemStar: an open source java remote method invocation architecture applied to large scale molecular data from PubChem. Journal of Chemical Information and Modeling. 48: 691-703. PMID 18402434 DOI: 10.1021/ci700334f  0.92
2008 Hsieh JH, Wang XS, Teotico D, Golbraikh A, Tropsha A. Differentiation of AmpC beta-lactamase binders vs. decoys using classification kNN QSAR modeling and application of the QSAR classifier to virtual screening. Journal of Computer-Aided Molecular Design. 22: 593-609. PMID 18338225 DOI: 10.1007/s10822-008-9199-2  0.92
2008 Zhu H, Tropsha A, Fourches D, Varnek A, Papa E, Gramatica P, Oberg T, Dao P, Cherkasov A, Tetko IV. Combinatorial QSAR modeling of chemical toxicants tested against Tetrahymena pyriformis. Journal of Chemical Information and Modeling. 48: 766-84. PMID 18311912 DOI: 10.1021/ci700443v  0.92
2008 Bandyopadhyay D, Huan J, Liu J, Prins J, Snoeyink J, Wang W, Tropsha A. Functional neighbors: Inferring relationships between non-homologous protein families using family-specific packing motifs Proceedings - Ieee International Conference On Bioinformatics and Biomedicine, Bibm 2008. 199-206. DOI: 10.1109/BIBM.2008.84  0.92
2007 Tropsha A, Golbraikh A. Predictive QSAR modeling workflow, model applicability domains, and virtual screening. Current Pharmaceutical Design. 13: 3494-504. PMID 18220786 DOI: 10.2174/138161207782794257  0.92
2007 Oprea TI, Tropsha A, Faulon JL, Rintoul MD. Systems chemical biology. Nature Chemical Biology. 3: 447-50. PMID 17637771 DOI: 10.1038/nchembio0807-447  0.92
2007 Zhang S, Wei L, Bastow K, Zheng W, Brossi A, Lee KH, Tropsha A. Antitumor agents 252. Application of validated QSAR models to database mining: discovery of novel tylophorine derivatives as potential anticancer agents. Journal of Computer-Aided Molecular Design. 21: 97-112. PMID 17340042 DOI: 10.1007/s10822-007-9102-6  0.92
2006 Chen X, Tropsha A. Calculation of the Relative Binding Affinity of Enzyme Inhibitors Using the Generalized Linear Response Method. Journal of Chemical Theory and Computation. 2: 1435-43. PMID 26626851 DOI: 10.1021/ct600071z  0.92
2006 Tropsha A, Wang SX. QSAR modeling of GPCR ligands: methodologies and examples of applications Ernst Schering Foundation Symposium Proceedings. 49-73. PMID 17703577  0.92
2006 Huan J, Bandyopadhyay D, Prins J, Snoeyink J, Tropsha A, Wang W. Distance-based identification of structure motifs in proteins using constrained frequent subgraph mining. Computational Systems Bioinformatics / Life Sciences Society. Computational Systems Bioinformatics Conference. 227-38. PMID 17369641  0.92
2006 Votano JR, Parham M, Hall LM, Hall LH, Kier LB, Oloff S, Tropsha A. QSAR modeling of human serum protein binding with several modeling techniques utilizing structure-information representation. Journal of Medicinal Chemistry. 49: 7169-81. PMID 17125269 DOI: 10.1021/jm051245v  0.92
2006 Zhang S, Golbraikh A, Oloff S, Kohn H, Tropsha A. A novel automated lazy learning QSAR (ALL-QSAR) approach: method development, applications, and virtual screening of chemical databases using validated ALL-QSAR models. Journal of Chemical Information and Modeling. 46: 1984-95. PMID 16995729 DOI: 10.1021/ci060132x  0.92
2006 Kozikowski AP, Roth B, Tropsha A. Why academic drug discovery makes sense. Science (New York, N.Y.). 313: 1235-6. PMID 16946051 DOI: 10.1126/science.313.5791.1235c  0.92
2006 Ghoneim OM, Legere JA, Golbraikh A, Tropsha A, Booth RG. Novel ligands for the human histamine H1 receptor: synthesis, pharmacology, and comparative molecular field analysis studies of 2-dimethylamino-5-(6)-phenyl-1,2,3,4-tetrahydronaphthalenes. Bioorganic & Medicinal Chemistry. 14: 6640-58. PMID 16782354 DOI: 10.1016/j.bmc.2006.05.077  0.92
2006 Bandyopadhyay D, Huan J, Liu J, Prins J, Snoeyink J, Wang W, Tropsha A. Structure-based function inference using protein family-specific fingerprints. Protein Science : a Publication of the Protein Society. 15: 1537-43. PMID 16731985 DOI: 10.1110/ps.062189906  0.92
2006 de Cerqueira Lima P, Golbraikh A, Oloff S, Xiao Y, Tropsha A. Combinatorial QSAR modeling of P-glycoprotein substrates. Journal of Chemical Information and Modeling. 46: 1245-54. PMID 16711744 DOI: 10.1021/ci0504317  0.92
2006 Zhang S, Golbraikh A, Tropsha A. Development of quantitative structure-binding affinity relationship models based on novel geometrical chemical descriptors of the protein-ligand interfaces. Journal of Medicinal Chemistry. 49: 2713-24. PMID 16640331 DOI: 10.1021/jm050260x  0.92
2006 Oloff S, Zhang S, Sukumar N, Breneman C, Tropsha A. Chemometric analysis of ligand receptor complementarity: identifying Complementary Ligands Based on Receptor Information (CoLiBRI). Journal of Chemical Information and Modeling. 46: 844-51. PMID 16563016 DOI: 10.1021/ci050065r  0.92
2006 Tropsha A. Chapter 7 Variable Selection QSAR Modeling, Model Validation, and Virtual Screening Annual Reports in Computational Chemistry. 2: 113-126. DOI: 10.1016/S1574-1400(06)02007-X  0.92
2006 Oprea TI, Tropsha A. Cheminformatics and drug discovery Drug Discovery Today: Technologies. 3: 355-356. DOI: 10.1016/j.ddtec.2006.12.005  0.92
2006 Oprea TI, Tropsha A. Target, chemical and bioactivity databases - integration is key Drug Discovery Today: Technologies. 3: 357-365. DOI: 10.1016/j.ddtec.2006.12.003  0.92
2006 Tropsha A. Predictive quantitative structure-activity relationship modeling Comprehensive Medicinal Chemistry Ii. 4: 149-165.  0.92
2005 Oloff S, Mailman RB, Tropsha A. Application of validated QSAR models of D1 dopaminergic antagonists for database mining. Journal of Medicinal Chemistry. 48: 7322-32. PMID 16279792 DOI: 10.1021/jm049116m  0.92
2005 Medina-Franco JL, Golbraikh A, Oloff S, Castillo R, Tropsha A. Quantitative structure-activity relationship analysis of pyridinone HIV-1 reverse transcriptase inhibitors using the k nearest neighbor method and QSAR-based database mining. Journal of Computer-Aided Molecular Design. 19: 229-42. PMID 16163450 DOI: 10.1007/s10822-005-4789-8  0.92
2005 Huan J, Bandyopadhyay D, Wang W, Snoeyink J, Prins J, Tropsha A. Comparing graph representations of protein structure for mining family-specific residue-based packing motifs. Journal of Computational Biology : a Journal of Computational Molecular Cell Biology. 12: 657-71. PMID 16108709 DOI: 10.1089/cmb.2005.12.657  0.92
2005 Itskowitz P, Tropsha A. kappa Nearest neighbors QSAR modeling as a variational problem: theory and applications. Journal of Chemical Information and Modeling. 45: 777-85. PMID 15921467 DOI: 10.1021/ci049628+  0.92
2005 Kovatcheva A, Golbraikh A, Oloff S, Feng J, Zheng W, Tropsha A. QSAR modeling of datasets with enantioselective compounds using chirality sensitive molecular descriptors. Sar and Qsar in Environmental Research. 16: 93-102. PMID 15844445 DOI: 10.1080/10629360412331319844  0.92
2005 Tropsha A, Edelsbrunner H. Biogeometry: applications of computational geometry to molecular structure. Pacific Symposium On Biocomputing. Pacific Symposium On Biocomputing. 1-3. PMID 15759608  0.92
2004 Votano JR, Parham M, Hall LH, Kier LB, Oloff S, Tropsha A, Xie Q, Tong W. Three new consensus QSAR models for the prediction of Ames genotoxicity. Mutagenesis. 19: 365-77. PMID 15388809 DOI: 10.1093/mutage/geh043  0.92
2004 Xiao Z, Varma S, Xiao YD, Tropsha A. Modeling of p38 mitogen-activated protein kinase inhibitors using the Catalyst HypoGen and k-nearest neighbor QSAR methods. Journal of Molecular Graphics & Modelling. 23: 129-38. PMID 15363455 DOI: 10.1016/j.jmgm.2004.05.001  0.92
2004 Ng C, Xiao Y, Putnam W, Lum B, Tropsha A. Quantitative structure-pharmacokinetic parameters relationships (QSPKR) analysis of antimicrobial agents in humans using simulated annealing k-nearest-neighbor and partial least-square analysis methods. Journal of Pharmaceutical Sciences. 93: 2535-44. PMID 15349962 DOI: 10.1002/jps.20117  0.92
2004 Sherman DB, Zhang S, Pitner JB, Tropsha A. Evaluation of the relative stability of liganded versus ligand-free protein conformations using Simplicial Neighborhood Analysis of Protein Packing (SNAPP) method. Proteins. 56: 828-38. PMID 15281134 DOI: 10.1002/prot.20131  0.92
2004 Edavettal SC, Carrick K, Shah RR, Pedersen LC, Tropsha A, Pope RM, Liu J. A conformational change in heparan sulfate 3-O-sulfotransferase-1 is induced by binding to heparan sulfate. Biochemistry. 43: 4680-8. PMID 15096036 DOI: 10.1021/bi0499112  0.92
2004 Shen M, Béguin C, Golbraikh A, Stables JP, Kohn H, Tropsha A. Application of predictive QSAR models to database mining: identification and experimental validation of novel anticonvulsant compounds. Journal of Medicinal Chemistry. 47: 2356-64. PMID 15084134 DOI: 10.1021/jm030584q  0.92
2004 Kovatcheva A, Golbraikh A, Oloff S, Xiao YD, Zheng W, Wolschann P, Buchbauer G, Tropsha A. Combinatorial QSAR of ambergris fragrance compounds. Journal of Chemical Information and Computer Sciences. 44: 582-95. PMID 15032539 DOI: 10.1021/ci034203t  0.92
2004 Huan J, Wang W, Washington A, Prins J, Shah R, Tropsha A. Accurate classification of protein structural families using coherent subgraph analysis Pacific Symposium On Biocomputing. Pacific Symposium On Biocomputing. 411-422. PMID 14992521  0.92
2004 Pendergraft WF, Preston GA, Shah RR, Tropsha A, Carter CW, Jennette JC, Falk RJ. Autoimmunity is triggered by cPR-3(105-201), a protein complementary to human autoantigen proteinase-3. Nature Medicine. 10: 72-9. PMID 14661018 DOI: 10.1038/nm968  0.92
2004 Huan J, Wang W, Bandyopadhyay D, Snoeyink J, Prins J, Tropsha A. Mining protein family specific residue packing patterns from protein structure graphs Proceedings of the Annual International Conference On Computational Molecular Biology, Recomb. 8: 308-315.  0.92
2004 Oloff S, Reihl E, Tropsha A, Kessler C, O'Brien T, Blocksome M, Gombar M, Batra V, Dulaney R. Novel automated, grid based, web accessible technology for computer-aided drug discovery Technology For Life: North Carolina Symposium On Biotechnology and Bioinformatics - 2004 Proceedings. 141-152.  0.92
2003 Tropsha A, Carter CW, Cammer S, Vaisman II. Simplicial neighborhood analysis of protein packing (SNAPP): a computational geometry approach to studying proteins. Methods in Enzymology. 374: 509-44. PMID 14696387 DOI: 10.1016/S0076-6879(03)74022-1  0.92
2003 Golbraikh A, Shen M, Xiao Z, Xiao YD, Lee KH, Tropsha A. Rational selection of training and test sets for the development of validated QSAR models. Journal of Computer-Aided Molecular Design. 17: 241-53. PMID 13677490 DOI: 10.1023/A:1025386326946  0.92
2003 Krishnamoorthy B, Tropsha A. Development of a four-body statistical pseudo-potential to discriminate native from non-native protein conformations. Bioinformatics (Oxford, England). 19: 1540-8. PMID 12912835 DOI: 10.1093/bioinformatics/btg186  0.92
2003 Shen M, Xiao Y, Golbraikh A, Gombar VK, Tropsha A. Development and validation of k-nearest-neighbor QSPR models of metabolic stability of drug candidates. Journal of Medicinal Chemistry. 46: 3013-20. PMID 12825940 DOI: 10.1021/jm020491t  0.92
2003 Golbraikh A, Tropsha A. QSAR modeling using chirality descriptors derived from molecular topology. Journal of Chemical Information and Computer Sciences. 43: 144-54. PMID 12546547 DOI: 10.1021/ci025516b  0.92
2003 Tropsha A, Gramatica P, Gombar VK. The importance of being earnest: Validation is the absolute essential for successful application and interpretation of QSPR models Qsar and Combinatorial Science. 22: 69-77.  0.92
2002 Golbraikh A, Tropsha A. Predictive QSAR modeling based on diversity sampling of experimental datasets for the training and test set selection. Molecular Diversity. 5: 231-43. PMID 12549674 DOI: 10.1023/A:1021372108686  0.92
2002 Golbraikh A, Tropsha A. Predictive QSAR modeling based on diversity sampling of experimental datasets for the training and test set selection. Journal of Computer-Aided Molecular Design. 16: 357-69. PMID 12489684 DOI: 10.1023/A:1020869118689  0.92
2002 Golbraikh A, Bonchev D, Tropsha A. Novel ZE-isomerism descriptors derived from molecular topology and their application to QSAR analysis. Journal of Chemical Information and Computer Sciences. 42: 769-87. PMID 12132878 DOI: 10.1021/ci0103469  0.92
2002 Shen M, LeTiran A, Xiao Y, Golbraikh A, Kohn H, Tropsha A. Quantitative structure-activity relationship analysis of functionalized amino acid anticonvulsant agents using k nearest neighbor and simulated annealing PLS methods. Journal of Medicinal Chemistry. 45: 2811-23. PMID 12061883 DOI: 10.1021/jm010488u  0.92
2002 Xiao Z, Xiao YD, Feng J, Golbraikh A, Tropsha A, Lee KH. Antitumor agents. 213. Modeling of epipodophyllotoxin derivatives using variable selection k nearest neighbor QSAR method. Journal of Medicinal Chemistry. 45: 2294-309. PMID 12014968 DOI: 10.1021/jm0105427  0.92
2002 Tropsha A, Zheng W. Rational principles of compound selection for combinatorial library design. Combinatorial Chemistry & High Throughput Screening. 5: 111-23. PMID 11966420  0.92
2002 Golbraikh A, Tropsha A. Beware of q2! Journal of Molecular Graphics & Modelling. 20: 269-76. PMID 11858635 DOI: 10.1016/S1093-3263(01)00123-1  0.92
2002 Tropsha A, Reynolds CH. Designing focused libraries for drug discovery: Hit to lead to drug Journal of Molecular Graphics and Modelling. 20: 427-428. DOI: 10.1016/S1093-3263(01)00143-7  0.92
2001 Carter CW, LeFebvre BC, Cammer SA, Tropsha A, Edgell MH. Four-body potentials reveal protein-specific correlations to stability changes caused by hydrophobic core mutations. Journal of Molecular Biology. 311: 625-38. PMID 11518520 DOI: 10.1006/jmbi.2001.4906  0.92
2001 Pilger C, Bartolucci C, Lamba D, Tropsha A, Fels G. Accurate prediction of the bound conformation of galanthamine in the active site of Torpedo californica acetylcholinesterase using molecular docking Journal of Molecular Graphics and Modelling. 19: 288-296. PMID 11449566 DOI: 10.1016/S1093-3263(00)00056-5  0.92
2001 Tropsha A, Zheng W. Identification of the descriptor pharmacophores using variable selection QSAR: Applications to database mining Current Pharmaceutical Design. 7: 599-612. PMID 11375770 DOI: 10.2174/1381612013397834  0.92
2001 Gan HH, Tropsha A, Schlick T. Lattice protein folding with two and four-body statistical potentials Proteins: Structure, Function and Genetics. 43: 161-174. PMID 11276086 DOI: 10.1002/1097-0134(20010501)43:2<161::AID-PROT1028>3.0.CO;2-F  0.92
2001 Golbraikh A, Bonchev D, Tropsha A. Novel Chirality Descriptors Derived from Molecular Topology Journal of Chemical Information and Computer Sciences. 41: 147-158. PMID 11206367 DOI: 10.1021/ci000082a  0.92
2001 Reynolds CH, Tropsha A, Pfahler LB, Druker R, Chakravorty S, Ethiraj G, Zheng W. Diversity and Coverage of Structural Sublibraries Selected Using the SAGE and SCA Algorithms Journal of Chemical Information and Computer Sciences. 41: 1470-1477. DOI: 10.1021/ci010041u  0.92
2000 Dexuan X, Tropsha A, Schlick T. An Efficient Projection Protocol for Chemical Databases: Singular Value Decomposition Combined with Truncated-Newton Minimization Journal of Chemical Information and Computer Sciences. 40: 167-177. PMID 10661564  0.92
2000 Zhang SX, Feng J, Kuo SC, Brossi A, Hamel E, Tropsha A, Lee KH. Antitumor agents. 199. Three-dimensional quantitative structure-activity relationship study of the colchicine binding site ligands using comparative molecular field analysis. Journal of Medicinal Chemistry. 43: 167-76. PMID 10649972 DOI: 10.1021/jm990333a  0.92
2000 Gan HH, Tropsha A, Schlick T. Generating folded protein structures with a lattice chain growth algorithm Journal of Chemical Physics. 113: 5511-5524. DOI: 10.1063/1.1289822  0.92
2000 Tropsha A. Recent trends in computer-aided drug discovery Current Opinion in Drug Discovery and Development. 3: 310-313.  0.92
2000 Zheng W, Tropsha A. Novel Variable Selection Quantitative Structure-Property Relationship Approach Based on the k-Nearest-Neighbor Principle Journal of Chemical Information and Computer Sciences. 40: 185-194.  0.92
1999 Chen X, Rusinko A, Tropsha A, Young SS. Automated pharmacophore identification for large chemical data sets Journal of Chemical Information and Computer Sciences. 39: 887-896. PMID 10529987  0.92
1999 Hoffman B, Cho SJ, Zheng W, Wyrick S, Nichols DE, Mailman RB, Tropsha A. Quantitative structure-activity relationship modeling of dopamine D(1) antagonists using comparative molecular field analysis, genetic algorithms-partial least-squares, and K nearest neighbor methods. Journal of Medicinal Chemistry. 42: 3217-26. PMID 10464009 DOI: 10.1021/jm980415j  0.92
1999 O'Connell TM, Wang L, Tropsha A, Hermans J. The "random-coil" state of proteins: comparison of database statistics and molecular simulations. Proteins. 36: 407-18. PMID 10450082 DOI: 10.1002/(SICI)1097-0134(19990901)36:4<407::AID-PROT4>3.0.CO;2-1  0.92
1999 Bucholtz EC, Brown RL, Tropsha A, Booth RG, Wyrick SD. Synthesis, evaluation, and comparative molecular field analysis of 1- phenyl-3-amino-1,2,3,4-tetrahydronaphthalenes as ligands for histamine H1 receptors Journal of Medicinal Chemistry. 42: 3041-3054. PMID 10447948 DOI: 10.1021/jm980428x  0.92
1999 Zheng W, Cho SJ, Waller CL, Tropsha A. Rational combinatorial library design. 3. Simulated annealing guided evaluation (SAGE) of molecular diversity: A novel computational tool for universal library design and database mining Journal of Chemical Information and Computer Sciences. 39: 738-746. PMID 10443027 DOI: 10.1021/ci980103p  0.92
1999 Chen X, Tropsha A. Generalized linear response method: Application to hydration free energy calculations Journal of Computational Chemistry. 20: 749-759.  0.92
1999 Bucholtz EC, Tropsha A. The effect of region size on CoMFA analyses Medicinal Chemistry Research. 9: 675-685.  0.92
1999 Tropsha A, Cho SJ, Zheng W. "New tricks for an old dog": Development and application of novel QSAR methods for rational design of combinatorial chemical libraries and database mining Acs Symposium Series. 719: 198-211.  0.92
1998 Cho SJ, Zheng W, Tropsha A. Focus-2D: a new approach to the design of targeted combinatorial chemical libraries Pacific Symposium On Biocomputing. Pacific Symposium On Biocomputing. 305-316. PMID 9697191  0.92
1998 Mansfield SG, Cammer S, Alexander SC, Muehleisen DP, Gray RS, Tropsha A, Bollenbacher WE. Molecular cloning and characterization of an invertebrate cellular retinoic acid binding protein. Proceedings of the National Academy of Sciences of the United States of America. 95: 6825-30. PMID 9618497 DOI: 10.1073/pnas.95.12.6825  0.92
1998 Cho SJ, Zheng W, Tropsha A. Rational combinatorial library design. 2. Rational design of targeted combinatorial peptide libraries using chemical similarity probe and the inverse QSAR approaches Journal of Chemical Information and Computer Sciences. 38: 259-268. PMID 9538521  0.92
1998 Zheng W, Cho SJ, Tropsha A. Rational combinatorial library design. 1. Focus-2D: A new approach to the design of targeted combinatorial chemical libraries Journal of Chemical Information and Computer Sciences. 38: 251-258. PMID 9538520  0.92
1998 Tropsha A, Cho SJ. Cross-Validated R2 Guided Region Selection for CoMFA Studies Perspectives in Drug Discovery and Design. 12: 57-69.  0.92
1998 Zheng W, Cho SJ, Tropsha A. Rational design of a targeted combinatorial chemical library with opiatelike activity International Journal of Quantum Chemistry. 69: 65-75.  0.92
1998 Shi Q, Chen K, Chen X, Brossi A, Verdier-Pinard P, Hamel E, McPhail AT, Tropsha A, Lee KH. Antitumor Agents. 183. Syntheses, Conformational Analyses, and Antitubulin Activity of Allothiocolchicinoids Journal of Organic Chemistry. 63: 4018-4025.  0.92
1997 Zheng W, Cho SJ, Vaisman II, Tropsha A. A new approach to protein fold recognition based on Delaunay tessellation of protein structure Pacific Symposium On Biocomputing. Pacific Symposium On Biocomputing. 486-497. PMID 9390317  0.92
1996 Tropsha A, Singh RK, Vaisman II, Zheng W. Statistical geometry analysis of proteins: implications for inverted structure prediction Pacific Symposium On Biocomputing. Pacific Symposium On Biocomputing. 614-623. PMID 9390262  0.92
1996 Cho SJ, Garsia ML, Bier J, Tropsha A. Structure-based alignment and comparative molecular field analysis of acetylcholinesterase inhibitors. Journal of Medicinal Chemistry. 39: 5064-71. PMID 8978837 DOI: 10.1021/jm950771r  0.92
1996 Wang L, O'Connell T, Tropsha A, Hermans J. Energetic decomposition of the alpha-helix-coil equilibrium of a dynamic model system. Biopolymers. 39: 479-89. PMID 8837515 DOI: 10.1002/(SICI)1097-0282(199610)39:4<479::AID-BIP1>3.0.CO;2-U  0.92
1996 Wang L, O'Connell T, Tropsha A, Hermans J. Molecular simulations of beta-sheet twisting. Journal of Molecular Biology. 262: 283-93. PMID 8831794 DOI: 10.1006/jmbi.1996.0513  0.92
1996 Cho SJ, Tropsha A, Sufness M, Cheng YC, Lee KH. Antitumor agents. 163. Three-dimensional quantitative structure-activity relationship study of 4′-O-demethylepipodophyllotoxin analogs using the modified CoMFA/q2-GRS approach Journal of Medicinal Chemistry. 39: 1383-1395. PMID 8691468  0.92
1996 Mottola DM, Laiter S, Watts VJ, Tropsha A, Wyrick SD, Nichols DE, Mailman RB. Conformational analysis of D1 dopamine receptor agonists: pharmacophore assessment and receptor mapping. Journal of Medicinal Chemistry. 39: 285-96. PMID 8568818 DOI: 10.1021/jm9502100  0.92
1995 Hoffman DL, Laiter S, Singh RK, Vaisman II, Tropsha A. Rapid protein structure classification using one-dimensional structure profiles on the BioSCAN parallel computer Bioinformatics. 11: 675-679. PMID 8808584 DOI: 10.1093/bioinformatics/11.6.675  0.92
1995 Laiter S, Hoffman DL, Singh RK, Vaisman II, Tropsha A. Pseudotorsional OCCO backbone angle as a single descriptor of protein secondary structure Protein Science. 4: 1633-1643. PMID 8520489  0.92
1995 Chen X, Tropsha A. Relative binding free energies of peptide inhibitors of HIV-1 protease: The influence of the active site protonation state Journal of Medicinal Chemistry. 38: 42-48. PMID 7837238  0.92
1995 Cho SJ, Tropsha A. Cross-validated R2-guided region selection for comparative molecular field analysis: A simple method to achieve consistent results Journal of Medicinal Chemistry. 38: 1060-1066. PMID 7707309  0.92
1995 Wang L, O'Connell T, Tropsha A, Hermans J. Thermodynamic parameters for the helix-coil transition of oligopeptides: Molecular dynamics simulation with the peptide growth method Proceedings of the National Academy of Sciences of the United States of America. 92: 10924-10928. PMID 7479911 DOI: 10.1073/pnas.92.24.10924  0.92
1995 Krishnaswami K, Tropsha A, Smith PC. Semi-empirical calculations of intramolecular acyl transfer in cis-enols of O-aroyl acetylacetones Journal of Molecular Structure: Theochem. 332: 85-91. DOI: 10.1016/0166-1280(94)03899-V  0.92
1995 Yan Y, Erickson BW, Tropsha A. Free energies for folding and refolding of four types of β turns: Simulation of the role of D/L chirality Journal of the American Chemical Society. 117: 7592-7599.  0.92
1994 Zhang YL, Tropsha A, McPhail AT, Lee KH. Antitumor agents. 152. In vitro inhibitory activity of etoposide derivative NPF against human tumor cell lines and a study of its conformation by X-ray crystallography, molecular modeling, and NMR spectroscopy Journal of Medicinal Chemistry. 37: 1460-1464. PMID 8182704  0.92
1994 Rozzelle JE, Tropsha A, Erickson BW. Rational design of a three-heptad coiled-coil protein and comparison by molecular dynamics simulation with the GCN4 coiled coil: presence of interior three-center hydrogen bonds. Protein Science : a Publication of the Protein Society. 3: 345-55. PMID 8003969 DOI: 10.1002/pro.5560030217  0.92
1994 Edgerton MD, Tropsha A, Jones AM. Modelling the auxin-binding site of auxin-binding protein 1 of maize Phytochemistry. 35: 1111-1123. DOI: 10.1016/S0031-9422(00)94807-6  0.92
1994 Vaisman II, Brown FK, Tropsha A. Distance dependence of water structure around model solutes Journal of Physical Chemistry. 98: 5559-5564.  0.92
1993 Yan Y, Tropsha A, Hermans J, Erickson BW. Free energies for refolding of the common beta turn into the inverse-common beta turn: simulation of the role of D/L chirality. Proceedings of the National Academy of Sciences of the United States of America. 90: 7898-902. PMID 8356099  0.92
1992 Tropsha A, Hermans J. Application of free energy simulations to the binding of a transition-state-analogue inhibitor to HTV protease Protein Engineering, Design and Selection. 5: 29-33. PMID 1631042 DOI: 10.1093/protein/5.1.29  0.92
1992 Tropsha A, Kizer JS, Chaiken IM. Making sense from antisense: a review of experimental data and developing ideas on sense--antisense peptide recognition. Journal of Molecular Recognition : Jmr. 5: 43-54. PMID 1472380 DOI: 10.1002/jmr.300050202  0.92
1991 Kizer JS, Tropsha A. A motif found in propeptides and prohormones that may target them to secretory vesicles. Biochemical and Biophysical Research Communications. 174: 586-92. PMID 1993056 DOI: 10.1016/0006-291X(91)91457-N  0.92
1991 Tropsha A, Bowen JP, Brown FK, Kizer JS. Do interhelical side chain-backbone hydrogen bonds participate in formation of leucine zipper coiled coils? Proceedings of the National Academy of Sciences of the United States of America. 88: 9488-92. PMID 1946362  0.92
1985 Tropsha AE, Nizhniǐ SV, Iaguzhinskiǐ LS. Structure-activity relationship in the series of muscarinic acetylcholine receptor antagonists: four types of antagonist-receptor binding Bioorganicheskaia Khimiia. 11: 1402-1416. PMID 4074400  0.92
1985 Tropsha AE, Nizhniǐ SV, Iaguzhinskiǐ LS. Structure-activity relationship in the series of muscarinic acetylcholine receptor agonists: three types of agonist-receptor complexes Bioorganicheskaia Khimiia. 11: 1391-1401. PMID 4074399  0.92
1984 Tsybulskaya MV, Antonenko Yu. N, Tropsha AE, Yaguzhinsky LS. Iodine-containing hormones are dipole modifiers of the phospholipid membranes Biofizika. 29: 801-805. PMID 6509098  0.92
1984 Tropsha AE, Rakhmaninova AB, Iaguzhinskiǐ LS. Configuration and properties of a binding site for thyroid hormones on a specific receptor Bioorganicheskaia Khimiia. 10: 483-492. PMID 6093814  0.92
1984 Tsybul'skaya MV, Antonenko YN, Tropsha AE, Yaguzhinskii LS. Iodine-containing hormones-Dipole modifiers of phospholipid membranes Biophysics. 29: 875-880.  0.92
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