1. Marciniak G, Decolin D, Leclerc G, Decker N, Schwartz J.. (1988) Synthesis and pharmacological properties of "soft drug" derivatives related to perhexiline., 31 (12): [PMID:2903931] [10.1021/jm00120a007] |
2. Keserü GM.. (2003) Prediction of hERG potassium channel affinity by traditional and hologram qSAR methods., 13 (16): [PMID:12873512] [10.1016/s0960-894x(03)00492-x] |
3. Cavalli A, Poluzzi E, De Ponti F, Recanatini M.. (2002) Toward a pharmacophore for drugs inducing the long QT syndrome: insights from a CoMFA study of HERG K(+) channel blockers., 45 (18): [PMID:12190308] [10.1021/jm0208875] |
4. Leclerc G, Decker N, Schwartz J.. (1982) Synthesis and cardiovascular activity of a new series of cyclohexylaralkylamine derivatives related to perhexiline., 25 (6): [PMID:6124638] [10.1021/jm00348a019] |
5. Rajamani R, Tounge BA, Li J, Reynolds CH.. (2005) A two-state homology model of the hERG K+ channel: application to ligand binding., 15 (6): [PMID:15745831] [10.1016/j.bmcl.2005.01.008] |
6. Kornhuber J, Tripal P, Reichel M, Terfloth L, Bleich S, Wiltfang J, Gulbins E.. (2008) Identification of new functional inhibitors of acid sphingomyelinase using a structure-property-activity relation model., 51 (2): [PMID:18027916] [10.1021/jm070524a] |
7. Jia L, Sun H.. (2008) Support vector machines classification of hERG liabilities based on atom types., 16 (11): [PMID:18448342] [10.1016/j.bmc.2008.04.028] |
8. Ermondi G, Visentin S, Caron G.. (2009) GRIND-based 3D-QSAR and CoMFA to investigate topics dominated by hydrophobic interactions: the case of hERG K+ channel blockers., 44 (5): [PMID:19110341] [10.1016/j.ejmech.2008.11.009] |
9. Pelletier DJ, Gehlhaar D, Tilloy-Ellul A, Johnson TO, Greene N.. (2007) Evaluation of a published in silico model and construction of a novel Bayesian model for predicting phospholipidosis inducing potential., 47 (1): [PMID:17428028] [10.1021/ci6004542] |
10. Cerep in vitro phospholipidosis assay data, |
11. Sinha N, Sen S.. (2011) Predicting hERG activities of compounds from their 3D structures: development and evaluation of a global descriptors based QSAR model., 46 (2): [PMID:21185626] [10.1016/j.ejmech.2010.11.042] |
12. Lowe R, Glen RC, Mitchell JB.. (2010) Predicting phospholipidosis using machine learning., 7 (5): [PMID:20799726] [10.1021/mp100103e] |
13. Greene N, Fisk L, Naven RT, Note RR, Patel ML, Pelletier DJ.. (2010) Developing structure-activity relationships for the prediction of hepatotoxicity., 23 (7): [PMID:20553011] [10.1021/tx1000865] |
14. Greene N, Fisk L, Naven RT, Note RR, Patel ML, Pelletier DJ.. (2010) Developing structure-activity relationships for the prediction of hepatotoxicity., 23 (7): [PMID:20553011] [10.1021/tx1000865] |
15. Ekins S, Williams AJ, Xu JJ.. (2010) A predictive ligand-based Bayesian model for human drug-induced liver injury., 38 (12): [PMID:20843939] [10.1124/dmd.110.035113] |
16. Kruhlak NL, Choi SS, Contrera JF, Weaver JL, Willard JM, Hastings KL, Sancilio LF.. (2008) Development of a phospholipidosis database and predictive quantitative structure-activity relationship (QSAR) models., 18 (2): [PMID:20020916] [10.1080/15376510701857262] |
17. (2008) Casarett and Doull's Toxicology The Basic Science of Poisons, 7th edition, |
18. Scott S. Auerbach, DrugMatrix¨ and ToxFX¨ Coordinator National Toxicology Program. DrugMatrix in vitro pharmacology data, |
19. Chen M, Vijay V, Shi Q, Liu Z, Fang H, Tong W.. (2011) FDA-approved drug labeling for the study of drug-induced liver injury., 16 (15-16): [PMID:21624500] [10.1016/j.drudis.2011.05.007] |
20. Liu Z, Shi Q, Ding D, Kelly R, Fang H, Tong W.. (2011) Translating clinical findings into knowledge in drug safety evaluation--drug induced liver injury prediction system (DILIps)., 7 (12): [PMID:22194678] [10.1371/journal.pcbi.1002310] |
21. Fischer H, Atzpodien EA, Csato M, Doessegger L, Lenz B, Schmitt G, Singer T.. (2012) In silico assay for assessing phospholipidosis potential of small druglike molecules: training, validation, and refinement using several data sets., 55 (1): [PMID:22122484] [10.1021/jm201082a] |
22. Sakatis MZ, Reese MJ, Harrell AW, Taylor MA, Baines IA, Chen L, Bloomer JC, Yang EY, Ellens HM, Ambroso JL, Lovatt CA, Ayrton AD, Clarke SE.. (2012) Preclinical strategy to reduce clinical hepatotoxicity using in vitro bioactivation data for >200 compounds., 25 (10): [PMID:22931300] [10.1021/tx300075j] |
23. Ceccarelli SM, Chomienne O, Gubler M, Arduini A.. (2011) Carnitine palmitoyltransferase (CPT) modulators: a medicinal chemistry perspective on 35 years of research., 54 (9): [PMID:21504156] [10.1021/jm100809g] |
24. Unpublished dataset, |
25. Unpublished dataset, |
26. Unpublished dataset, |
27. Unpublished dataset, |
28. Unpublished dataset, |
29. Unpublished dataset, |
30. Biour M, Ben Salem C, Chazouillères O, Grangé JD, Serfaty L, Poupon R.. (2004) [Drug-induced liver injury; fourteenth updated edition of the bibliographic database of liver injuries and related drugs]., 28 (8-9): [PMID:15646539] [10.1016/s0399-8320(04)95062-2] |
31. PubChem BioAssay data set, |
32. Mark Wenlock and Nicholas Tomkinson. Experimental in vitro DMPK and physicochemical data on a set of publicly disclosed compounds, [10.6019/CHEMBL3301361] |
33. WHO Anatomical Therapeutic Chemical Classification, |
34. Open TG-GATES, [10.6019/CHEMBL3885861] |
35. DrugMatrix, [10.6019/CHEMBL3885881] |
36. Warner DJ, Chen H, Cantin LD, Kenna JG, Stahl S, Walker CL, Noeske T.. (2012) Mitigating the inhibition of human bile salt export pump by drugs: opportunities provided by physicochemical property modulation, in silico modeling, and structural modification., 40 (12): [PMID:22961681] [10.1124/dmd.112.047068] |
37. Chen M, Suzuki A, Thakkar S, Yu K, Hu C, Tong W.. (2016) DILIrank: the largest reference drug list ranked by the risk for developing drug-induced liver injury in humans., 21 (4): [PMID:26948801] [10.1016/j.drudis.2016.02.015] |
38. Tseng CC, Noordali H, Sani M, Madhani M, Grant DM, Frenneaux MP, Zanda M, Greig IR.. (2017) Development of Fluorinated Analogues of Perhexiline with Improved Pharmacokinetic Properties and Retained Efficacy., 60 (7): [PMID:28277663] [10.1021/acs.jmedchem.6b01592] |
39. Unpublished dataset, |
40. Sangeun Jeon, Meehyun Ko, Jihye Lee, Inhee Choi, Soo Young Byun, Soonju Park, David Shum, Seungtaek Kim. (2020) Identification of antiviral drug candidates against SARS-CoV-2 from FDA-approved drugs, [10.1101/2020.03.20.999730] |
41. Katie Heiser, Peter F. McLean, Chadwick T. Davis, Ben Fogelson, Hannah B. Gordon, Pamela Jacobson, Brett Hurst, Ben Miller, Ronald W. Alfa, Berton A. Earnshaw, Mason L. Victors, Yolanda T. Chong, Imran S. Haque, Adeline S. Low, Christopher C. Gibson. (2020) Identification of potential treatments for COVID-19 through artificial intelligence-enabled phenomic analysis of human cells infected with SARS-CoV-2, [10.1101/2020.04.21.054387] |
42. Rana P, Will Y, Nadanaciva S, Jones LH.. (2016) Development of a cell viability assay to assess drug metabolite structure-toxicity relationships., 26 (16): [PMID:27397500] [10.1016/j.bmcl.2016.06.088] |
43. Bernhard Ellinger, Justus Dick, Vanessa Lage-Rupprecht, Bruce Schultz, Andrea Zaliani, Marcin Namysl, Stephan Gebel, Ole Pless, Jeanette Reinshagen, Christian Ebeling, Alexander Esser, Marc Jacobs, Carsten Claussen, and Martin Hofmann-Apitius. (2021) HDAC6 screening dataset using tau-based substrate in an enzymatic assay yields selective inhibitors and activators, [10.6019/CHEMBL4808148] |
44. Winter C, Siepe I, Wise A, Dorali A, Barrett AGM, Witschel M.. (2023) Agrochemical Lessons for Infectious Disease Research: New Resistance Breaking Antifungal Hits against Candida auris., 14 (2.0): [PMID:36793433] [10.1021/acsmedchemlett.2c00497] |
45. Sutherland JJ, Yonchev D, Fekete A, Urban L.. (2023) A preclinical secondary pharmacology resource illuminates target-adverse drug reaction associations of marketed drugs., 14 (1): [PMID:37468498] [10.1038/s41467-023-40064-9] |