Looking back to the future: Predicting in vivo efficacy of small molecules versus Mycobacterium tuberculosis

Journal of Chemical Information and Modeling

Volumn 54, Issue 4, 2014, Pages 1070-1082

  Ekins, Sean ^a,b   Pottorf, Richard ^c   Reynolds, Robert C ^d   Williams, Antony J ^e   Clark, Alex M ^f   Freundlich, Joel S ^c  

^a Collaborative Drug Discovery ^*  (United States)

^b Collaborations in Chemistry ^*  (United States)

^c RUTGERS NEW JERSEY MEDICAL SCHOOL   (United States)

^d UNIVERSITY OF ALABAMA AT BIRMINGHAM   (United States)

^e ROYAL SOCIETY OF CHEMISTRY   (United Kingdom)

^f Molecular Materials Informatics   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN NETWORKS; COST EFFECTIVENESS; MOLECULES; REGRESSION ANALYSIS; SUPPORT VECTOR MACHINES;

BAYESIAN MODEL; COMPUTATIONAL MODEL; COST EFFECTIVE; INACTIVE COMPOUNDS; MACHINE LEARNING CLASSIFICATION; MYCOBACTERIUM TUBERCULOSIS; RECURSIVE PARTITIONING; SMALL MOLECULES;

STATISTICAL TESTS;

MOLECULAR LIBRARY; TUBERCULOSTATIC AGENT;

DRUG EFFECTS; MOLECULAR LIBRARY; MYCOBACTERIUM TUBERCULOSIS; PHARMACOLOGY; PRINCIPAL COMPONENT ANALYSIS; STRUCTURE ACTIVITY RELATION; THEORETICAL MODEL;

ANTITUBERCULAR AGENTS; MODELS, THEORETICAL; MYCOBACTERIUM TUBERCULOSIS; PRINCIPAL COMPONENT ANALYSIS; SMALL MOLECULE LIBRARIES; STRUCTURE-ACTIVITY RELATIONSHIP;

EID: 84899872338     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci500077v     Document Type: Article

References (84)

1. Nuermberger, E. L.; Spigelman, M. K.; Yew, W. W. Current development and future prospects in chemotherapy of tuberculosis Respirology 2010, 15 (5) 764-778
2. Global Tuberculosis Report 2013. World Health Organization. http://www.who.int/tb/publications/global-report/en/.
3. Zhang, Y. The magic bullets and tuberculosis drug targets Annu. Rev. Pharmacol. Toxicol. 2005, 45, 529-564
4. Ballel, L.; Field, R. A.; Duncan, K.; Young, R. J. New small-molecule synthetic antimycobacterials Antimicrob. Agents Chemother. 2005, 49, 2153-2163
5. Ma, Z.; Lienhardt, C.; McIlleron, H.; Nunn, A. J.; Wang, X. Global tuberculosis drug development pipeline: The need and the reality Lancet 2010, 375 (9731) 2100-2109
6. Wong, E. B.; Cohen, K. A.; Bishai, W. R. Rising to the challenge: New therapies for tuberculosis Trends Microbiol. 2013, 21 (9) 493-501
7. Gold, B.; Pingle, M.; Brickner, S. J.; Shah, N.; Roberts, J.; Rundell, M.; Bracken, W. C.; Warrier, T.; Somersan, S.; Venugopal, A.; Darby, C.; Jiang, X.; Warren, J. D.; Fernandez, J.; Ouerfelli, O.; Nuermberger, E. L.; Cunningham-Bussel, A.; Rath, P.; Chidawanyika, T.; Deng, H.; Realubit, R.; Glickman, J. F.; Nathan, C. F. Nonsteroidal anti-inflammatory drug sensitizes Mycobacterium tuberculosis to endogenous and exogenous antimicrobials Proc. Natl. Acad. Sci. U.S.A. 2012, 109 (40) 16004-16011
8. Ekins, S.; Reynolds, R.; Kim, H.; Koo, M.-S.; Ekonomidis, M.; Talaue, M.; Paget, S. D.; Woolhiser, L. K.; Lenaerts, A. J.; Bunin, B. A.; Connell, N.; Freundlich, J. S. Bayesian models leveraging bioactivity and cytotoxicity information for drug discovery Chem. Biol. 2013, 20, 370-378
9. Bruhin, H.; Buhlmann, X.; Hook, W. H.; Hoyle, W.; Orford, B.; Vischer, W. Antituberculosis activity of some nitrofuran derivatives J. Pharm. Pharmacol. 1969, 21 (7) 423-33
10. Hoffmann, K.; Onoz, E. Inhibitory effect of oxyphenbutazone against Mycobacterium tuberculosis in vitro Arzneimittelforschung 1969, 19 (2) 241-242
11. Rao, S. P.; Lakshminarayana, S. B.; Kondreddi, R. R.; Herve, M.; Camacho, L. R.; Bifani, P.; Kalapala, S. K.; Jiricek, J.; Ma, N. L.; Tan, B. H.; Ng, S. H.; Nanjundappa, M.; Ravindran, S.; Seah, P. G.; Thayalan, P.; Lim, S. H.; Lee, B. H.; Goh, A.; Barnes, W. S.; Chen, Z.; Gagaring, K.; Chatterjee, A. K.; Pethe, K.; Kuhen, K.; Walker, J.; Feng, G.; Babu, S.; Zhang, L.; Blasco, F.; Beer, D.; Weaver, M.; Dartois, V.; Glynne, R.; Dick, T.; Smith, P. W.; Diagana, T. T.; Manjunatha, U. H. Indolcarboxamide is a preclinical candidate for treating multidrug-resistant tuberculosis Sci. Transl. Med. 2013, 5 (214) 214ra168
12. Ballell, L.; Bates, R. H.; Young, R. J.; Alvarez-Gomez, D.; Alvarez-Ruiz, E.; Barroso, V.; Blanco, D.; Crespo, B.; Escribano, J.; Gonzalez, R.; Lozano, S.; Huss, S.; Santos-Villarejo, A.; Martin-Plaza, J. J.; Mendoza, A.; Rebollo-Lopez, M. J.; Remuinan-Blanco, M.; Lavandera, J. L.; Perez-Herran, E.; Gamo-Benito, F. J.; Garcia-Bustos, J. F.; Barros, D.; Castro, J. P.; Cammack, N. Fueling open-source drug discovery: 177 small-molecule leads against tuberculosis ChemMedChem 2013, 8, 313-321
13. Ananthan, S.; Faaleolea, E. R.; Goldman, R. C.; Hobrath, J. V.; Kwong, C. D.; Laughon, B. E.; Maddry, J. A.; Mehta, A.; Rasmussen, L.; Reynolds, R. C.; Secrist, J. A., 3rd; Shindo, N.; Showe, D. N.; Sosa, M. I.; Suling, W. J.; White, E. L. High-throughput screening for inhibitors of Mycobacterium tuberculosis H37Rv Tuberculosis (Edinb) 2009, 89, 334-353
14. Maddry, J. A.; Ananthan, S.; Goldman, R. C.; Hobrath, J. V.; Kwong, C. D.; Maddox, C.; Rasmussen, L.; Reynolds, R. C.; Secrist, J. A., 3rd; Sosa, M. I.; White, E. L.; Zhang, W. Antituberculosis activity of the molecular libraries screening center network library Tuberculosis (Edinb) 2009, 89, 354-363
15. Reynolds, R. C.; Ananthan, S.; Faaleolea, E.; Hobrath, J. V.; Kwong, C. D.; Maddox, C.; Rasmussen, L.; Sosa, M. I.; Thammasuvimol, E.; White, E. L.; Zhang, W.; Secrist, J. A., 3rd High throughput screening of a library based on kinase inhibitor scaffolds against Mycobacterium tuberculosis H37Rv Tuberculosis (Edinb) 2012, 92, 72-83
16. Grant, S. S.; Kawate, T.; Nag, P. P.; Silvis, M. R.; Gordon, K.; Stanley, S. A.; Kazyanskaya, E.; Nietupski, R.; Golas, A.; Fitzgerald, M.; Cho, S.; Franzblau, S. G.; Hung, D. T. Identification of novel inhibitors of nonreplicating Mycobacterium tuberculosis using a carbon starvation model ACS Chem. Biol. 2013, 8 (10) 2224-2234
17. Stanley, S. A.; Grant, S. S.; Kawate, T.; Iwase, N.; Shimizu, M.; Wivagg, C.; Silvis, M.; Kazyanskaya, E.; Aquadro, J.; Golas, A.; Fitzgerald, M.; Dai, H.; Zhang, L.; Hung, D. T. Identification of novel inhibitors of M. tuberculosis growth using whole cell based high-throughput screening ACS Chem. Biol. 2012, 7, 1377-1384
18. Lee, R. E.; Protopopova, M.; Crooks, E.; Slayden, R. A.; Terrot, M.; Barry, C. E., 3rd Combinatorial lead optimization of [1,2]-diamines based on ethambutol as potential antituberculosis preclinical candidates J. Comb. Chem. 2003, 5 (2) 172-187
19. Andries, K.; Verhasselt, P.; Guillemont, J.; Gohlmann, H. W.; Neefs, J. M.; Winkler, H.; Van Gestel, J.; Timmerman, P.; Zhu, M.; Lee, E.; Williams, P.; de Chaffoy, D.; Huitric, E.; Hoffner, S.; Cambau, E.; Truffot-Pernot, C.; Lounis, N.; Jarlier, V. A diarylquinoline drug active on the ATP synthase of Mycobacterium tuberculosis Science 2005, 307 (5707) 223-227
20. Collins, F. S. Reengineering translational science: The time is right Sci. Transl. Med. 2011, 3 (90) 90cm17
21. Macarron, R.; Banks, M. N.; Bojanic, D.; Burns, D. J.; Cirovic, D. A.; Garyantes, T.; Green, D. V.; Hertzberg, R. P.; Janzen, W. P.; Paslay, J. W.; Schopfer, U.; Sittampalam, G. S. Impact of high-throughput screening in biomedical research Nat. Rev. Drug Discovery 2011, 10 (3) 188-195
22. Ekins, S.; Freundlich, J. S.; Hobrath, J. V.; White, E. L.; Reynolds, R. C. Combining computational methods for hit to lead optimization in Mycobacterium tuberculosis drug discovery Pharm. Res. 2013, 31, 414-435
23. Chang, K. C.; Leung, C. C.; Grosset, J.; Yew, W. W. Treatment of tuberculosis and optimal dosing schedules Thorax 2011, 66 (11) 997-1007
24. Lenaerts, A. J.; Gruppo, V.; Brooks, J. V.; Orme, I. M. Rapid in vivo screening of experimental drugs for tuberculosis using gamma interferon gene-disrupted mice Antimicrob. Agents Chemother. 2003, 47 (2) 783-5
25. Franzblau, S. G.; DeGroote, M. A.; Cho, S. H.; Andries, K.; Nuermberger, E.; Orme, I. M.; Mdluli, K.; Angulo-Barturen, I.; Dick, T.; Dartois, V.; Lenaerts, A. J. Comprehensive analysis of methods used for the evaluation of compounds against Mycobacterium tuberculosis Tuberculosis (Edinb) 2012, 92 (6) 453-488
26. Ekins, S.; Freundlich, J. S. Validating new tuberculosis computational models with public whole cell screening aerobic activity datasets Pharm. Res. 2011, 28, 1859-1869
27. Sarker, M.; Talcott, C.; Madrid, P.; Chopra, S.; Bunin, B. A.; Lamichhane, G.; Freundlich, J. S.; Ekins, S. Combining cheminformatics methods and pathway analysis to identify molecules with whole-cell activity against Mycobacterium tuberculosis Pharm. Res. 2012, 29, 2115-2127
28. Ekins, S.; Reynolds, R. C.; Franzblau, S. G.; Wan, B.; Freundlich, J. S.; Bunin, B. A. Enhancing hit identification in Mycobacterium tuberculosis drug discovery using validated dual-event Bayesian models PLoS One 2013, 8, e63240
29. Ekins, S.; Freundlich, J. S.; Reynolds, R. C. Fusing dual-event datasets for Mycobacterium tuberculosis machine learning models and their evaluation J. Chem. Inf. Model. 2013, 53, 3054-3063
30. Clark, A. M. Mobile Molecular DataSheet (MMDS). http://molmatinf.com/ products.html#mmds.
31. Ekins, S.; Bradford, J.; Dole, K.; Spektor, A.; Gregory, K.; Blondeau, D.; Hohman, M.; Bunin, B. A collaborative database and computational models for tuberculosis drug discovery Mol BioSyst. 2010, 6, 840-851
32. Ekins, S.; Clark, A. M.; Sarker, M. TB Mobile: A mobile app for anti-tuberculosis molecules with known targets J. Cheminform. 2013, 5, 13
33. Prathipati, P.; Ma, N. L.; Keller, T. H. Global Bayesian models for the prioritization of antitubercular agents J. Chem. Inf. Model. 2008, 48 (12) 2362-2370
34. Bender, A.; Scheiber, J.; Glick, M.; Davies, J. W.; Azzaoui, K.; Hamon, J.; Urban, L.; Whitebread, S.; Jenkins, J. L. Analysis of pharmacology data and the prediction of adverse drug reactions and off-target effects from chemical structure ChemMedChem 2007, 2 (6) 861-873
35. Klon, A. E.; Lowrie, J. F.; Diller, D. J. Improved naive Bayesian modeling of numerical data for absorption, distribution, metabolism and excretion (ADME) property prediction J. Chem. Inf. Model. 2006, 46 (5) 1945-1956
36. Hassan, M.; Brown, R. D.; Varma-O'brien, S.; Rogers, D. Cheminformatics analysis and learning in a data pipelining environment Mol. Diversity 2006, 10 (3) 283-299
37. Rogers, D.; Brown, R. D.; Hahn, M. Using extended-connectivity fingerprints with Laplacian-modified Bayesian analysis in high-throughput screening follow-up J. Biomol. Screening 2005, 10 (7) 682-686
38. Jones, D. R.; Ekins, S.; Li, L.; Hall, S. D. Computational approaches that predict metabolic intermediate complex formation with CYP3A4 (+b5) Drug Metab. Dispos. 2007, 35 (9) 1466-1475
39. The R Project for Statistical Computing. http://www.r-project.org/.
40. Youmans, G. P.; Doub, l.; Youmans, A. S. The Bacteriostatic Activity of 3500 Organic Compounds for Mycobacterium tuberculosis var. Hominis; National Research Council: Washington, DC, 1953.
41. Ellis, S.; Kalinowski, D. S.; Leotta, L.; Huang, M. L.; Jelfs, P.; Sintchenko, V.; Richardson, D. R.; Triccas, J. A. Potent anti-mycobacterial activity of the pyridoxal isonicotinoyl hydrazone analogue, 2- pyridylcarboxaldehyde isonicotinoyl hydrazone: A lipophilic transport vehicle for isonicotinic acid hydrazide Mol. Pharmacol. 2014, 85, 269-278
42. Shirude, P. S.; Shandil, R.; Sadler, C.; Naik, M.; Hosagrahara, V.; Hameed, S.; Shinde, V.; Bathula, C.; Humnabadkar, V.; Kumar, N.; Reddy, J.; Panduga, V.; Sharma, S.; Ambady, A.; Hegde, N.; Whiteaker, J.; McLaughlin, R. E.; Gardner, H.; Madhavapeddi, P.; Ramachandran, V.; Kaur, P.; Narayan, A.; Guptha, S.; Awasthy, D.; Narayan, C.; Mahadevaswamy, J.; Vishwas, K.; Ahuja, V.; Srivastava, A.; Prabhakar, K.; Bharath, S.; Kale, R.; Ramaiah, M.; Choudhury, N. R.; Sambandamurthy, V. K.; Solapure, S.; Iyer, P. S.; Narayanan, S.; Chatterji, M. Azaindoles: Noncovalent DprE1 inhibitors from scaffold morphing efforts, kill Mycobacterium tuberculosis and are efficacious in vivo J. Med. Chem. 2013, 56, 9701-9708
43. Ekins, S. Progress in computational toxicology J. Pharmacol. Toxicol. Methods 2014, 69, 115-140
44. Clark, A. M. SAR Table. http://molmatinf.com/products.html#sartable.
45. Blaser, A.; Palmer, B. D.; Sutherland, H. S.; Kmentova, I.; Franzblau, S. G.; Wan, B.; Wang, Y.; Ma, Z.; Thompson, A. M.; Denny, W. A. Structure-activity relationships for amide-, carbamate-, and urea-linked analogues of the tuberculosis drug (6S)-2-nitro-6-{[4-(trifluoromethoxy)benzyl]oxy}-6,7-dihydro- 5H-imidazo[2,1-b][1, 3]oxazine (PA-824) J. Med. Chem. 2012, 55 (1) 312-326
46. Thompson, A. M.; Sutherland, H. S.; Palmer, B. D.; Kmentova, I.; Blaser, A.; Franzblau, S. G.; Wan, B.; Wang, Y.; Ma, Z.; Denny, W. A. Synthesis and structure-activity relationships of varied ether linker analogues of the antitubercular drug (6S)-2-nitro-6-{[4-(trifluoromethoxy)benzyl]oxy}-6,7- dihydro-5h-imidazo[2,1-b][1, 3]oxazine (PA-824) J. Med. Chem. 2012, 54 (19) 6563-6585
47. Palmer, B. D.; Thompson, A. M.; Sutherland, H. S.; Blaser, A.; Kmentova, I.; Franzblau, S. G.; Wan, B.; Wang, Y.; Ma, Z.; Denny, W. A. Synthesis and structure-activity studies of biphenyl analogues of the tuberculosis drug (6S)-2-nitro-6-{[4-(trifluoromethoxy)benzyl]oxy}-6,7-dihydro-5H-imidazo[2,1-b] [1, 3]oxazine (PA-824) J. Med. Chem. 2010, 53 (1) 282-294
48. Thompson, A. M.; Blaser, A.; Anderson, R. F.; Shinde, S. S.; Franzblau, S. G.; Ma, Z.; Denny, W. A.; Palmer, B. D. Synthesis, reduction potentials, and antitubercular activity of ring A/B analogues of the bioreductive drug (6S)-2-nitro-6-{[4-(trifluoromethoxy)benzyl]oxy}-6,7-dihydro-5H-imidazo[2,1-b] [1, 3]oxazine (PA-824) J. Med. Chem. 2009, 52 (3) 637-645
49. Thompson, A. M.; Sutherland, H. S.; Palmer, B. D.; Kmentova, I.; Blaser, A.; Franzblau, S. G.; Wan, B.; Wang, Y.; Ma, Z.; Denny, W. A. Synthesis and structure-activity relationships of varied ether linker analogues of the antitubercular drug (6S)-2-nitro-6-{[4-(trifluoromethoxy)benzyl]oxy}-6,7- dihydro-5h-imidazo[2,1-b][1, 3]oxazine (PA-824) J. Med. Chem. 2011, 54 (19) 6563-6585
50. Kmentova, I.; Sutherland, H. S.; Palmer, B. D.; Blaser, A.; Franzblau, S. G.; Wan, B.; Wang, Y.; Ma, Z.; Denny, W. A.; Thompson, A. M. Synthesis and structure-activity relationships of aza- and diazabiphenyl analogues of the antitubercular drug (6S)-2-nitro-6-{[4-(trifluoromethoxy)benzyl]oxy}-6,7- dihydro-5H-imidazo[2,1-b][1, 3]oxazine (PA-824) J. Med. Chem. 2010, 53, 8421-8439
51. Caspi, R.; Foerster, H.; Fulcher, C. A.; Kaipa, P.; Krummenacker, M.; Latendresse, M.; Paley, S.; Rhee, S. Y.; Shearer, A. G.; Tissier, C.; Walk, T. C.; Zhang, P.; Karp, P. D. The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases Nucleic Acids Res. 2008, 36 (Database issue) D623-D631
52. Galagan, J. E.; Sisk, P.; Stolte, C.; Weiner, B.; Koehrsen, M.; Wymore, F.; Reddy, T. B.; Zucker, J. D.; Engels, R.; Gellesch, M.; Hubble, J.; Jin, H.; Larson, L.; Mao, M.; Nitzberg, M.; White, J.; Zachariah, Z. K.; Sherlock, G.; Ball, C. A.; Schoolnik, G. K. TB database 2010: overview and update Tuberculosis (Edinb) 2010, 90 (4) 225-235
53. Bruhin, H.; Buhlmann, X.; Hook, W. H.; Hoyle, W.; Orford, B.; Vischer, W. Antituberculosis activity of some nitrofuran derivatives J. Pharm. Pharmacol. 1969, 21 (7) 423-433
54. Ekins, S.; Freundlich, J. S. Computational models for tuberculosis drug discovery Methods Mol. Biol. 2013, 993, 245-262
55. Ekins, S.; Casey, A. C.; Roberts, D.; Parish, T.; Bunin, B. A. Bayesian models for screening and TB Mobile for target inference with Mycobacterium tuberculosis Tuberculosis (Edinb) 2014, 94 (2) 162-169
56. Paolini, G. V.; Shapland, R. H.; van Hoorn, W. P.; Mason, J. S.; Hopkins, A. L. Global mapping of pharmacological space Nat. Biotechnol. 2006, 24 (7) 805-815
57. Ghose, A. K.; Viswanadhan, V. N.; Wendoloski, J. J. Prediction of hydrophobic (lipophilic) properties of small organic molecules using fragmental methods: An analysis of ALOGP and CLOGP methods J. Phys. Chem. 1998, 102, 3762-3772
58. Lun, S.; Guo, H.; Onajole, O. K.; Pieroni, M.; Gunosewoyo, H.; Chen, G.; Tipparaju, S. K.; Ammerman, N. C.; Kozikowski, A. P.; Bishai, W. R. Indoleamides are active against drug-resistant Mycobacterium tuberculosis Nat Commun 2013, 4, 2907
59. Remuinan, M. J.; Perez-Herran, E.; Rullas, J.; Alemparte, C.; Martinez-Hoyos, M.; Dow, D. J.; Afari, J.; Mehta, N.; Esquivias, J.; Jimenez, E.; Ortega-Muro, F.; Fraile-Gabaldon, M. T.; Spivey, V. L.; Loman, N. J.; Pallen, M. J.; Constantinidou, C.; Minick, D. J.; Cacho, M.; Rebollo-Lopez, M. J.; Gonzalez, C.; Sousa, V.; Angulo-Barturen, I.; Mendoza-Losana, A.; Barros, D.; Besra, G. S.; Ballell, L.; Cammack, N. Tetrahydropyrazolo[1,5-a]pyrimidine- 3-carboxamide and N-benzyl-6′,7′-dihydrospiro[piperidine-4,4′- thieno[3,2-c]pyran] analogues with bactericidal efficacy against Mycobacterium tuberculosis targeting MmpL3 PLoS One 2013, 8 (4) e60933
60. Villemagne, B.; Crauste, C.; Flipo, M.; Baulard, A. R.; Deprez, B.; Willand, N. Tuberculosis: The drug development pipeline at a glance Eur. J. Med. Chem. 2012, 51, 1-16
61. Dheda, K.; Migliori, G. B. The global rise of extensively drug-resistant tuberculosis: is the time to bring back sanatoria now overdue? Lancet 2012, 379 (9817) 773-775
62. Sassetti, C. M.; Rubin, E. J. Genetic requirements for mycobacterial survival during infection Proc. Natl. Acad. Sci. U.S.A. 2003, 100 (22) 12989-94
63. Sassetti, C. M.; Boyd, D. H.; Rubin, E. J. Genes required for mycobacterial growth defined by high density mutagenesis Mol. Microbiol. 2003, 48 (1) 77-84
64. Dartois, V.; Barry, C. E., 3rd A medicinal chemists' guide to the unique difficulties of lead optimization for tuberculosis Bioorg. Med. Chem. Lett. 2013, 23 (17) 4741-4750
65. Franco, N. H.; Correia-Neves, M.; Olsson, I. A. Animal welfare in studies on murine tuberculosis: assessing progress over a 12-year period and the need for further improvement PLoS One 2012, 7 (10) e47723
66. Guner, O. F.; Bowen, J. P. Pharmacophore modeling for ADME Curr. Top. Med. Chem. 2013, 13 (11) 1327-1342
67. Gombar, V. K.; Hall, S. D. Quantitative structure-activity relationship models of clinical pharmacokinetics: Clearance and volume of distribution J. Chem. Inf. Model. 2013, 53 (4) 948-957
68. Cheng, F.; Li, W.; Zhou, Y.; Shen, J.; Wu, Z.; Liu, G.; Lee, P. W.; Tang, Y. admetSAR: a comprehensive source and free tool for assessment of chemical ADMET properties J. Chem. Inf. Model. 2012, 52 (11) 3099-3105
69. Sushko, I.; Novotarskyi, S.; Korner, R.; Pandey, A. K.; Rupp, M.; Teetz, W.; Brandmaier, S.; Abdelaziz, A.; Prokopenko, V. V.; Tanchuk, V. Y.; Todeschini, R.; Varnek, A.; Marcou, G.; Ertl, P.; Potemkin, V.; Grishina, M.; Gasteiger, J.; Schwab, C.; Baskin, I. I.; Palyulin, V. A.; Radchenko, E. V.; Welsh, W. J.; Kholodovych, V.; Chekmarev, D.; Cherkasov, A.; Aires-de-Sousa, J.; Zhang, Q. Y.; Bender, A.; Nigsch, F.; Patiny, L.; Williams, A.; Tkachenko, V.; Tetko, I. V. Online chemical modeling environment (OCHEM): Web platform for data storage, model development and publishing of chemical information J. Comput.-Aided Mol. Des. 2011, 25 (6) 533-54
70. Gleeson, M. P.; Hersey, A.; Montanari, D.; Overington, J. Probing the links between in vitro potency, ADMET and physicochemical parameters Nat. Rev. Drug Discovery 2011, 10 (3) 197-208
71. Gupta, R. R.; Gifford, E. M.; Liston, T.; Waller, C. L.; Bunin, B.; Ekins, S. Using open source computational tools for predicting human metabolic stability and additional ADME/TOX properties Drug Metab. Dispos. 2010, 38, 2083-2090
72. Ekins, S.; Williams, A. J. Precompetitive preclinical ADME/Tox data: Set it free on the Web to facilitate computational model building to assist drug development Lab Chip 2010, 10, 13-22
73. Ekins, S.; Honeycutt, J. D.; Metz, J. T. Evolving molecules using multi-objective optimization: Applying to ADME Drug Discovery Today 2010, 15, 451-460
74. Lagorce, D.; Sperandio, O.; Galons, H.; Miteva, M. A.; Villoutreix, B. O. FAF-Drugs2: free ADME/tox filtering tool to assist drug discovery and chemical biology projects BMC Bioinform. 2008, 9, 396
75. Ekins, S.; Swaan, P. W. Computational models for enzymes, transporters, channels and receptors relevant to ADME/TOX Rev. Comput. Chem. 2004, 20, 333-415
76. Ekins, S.; Kaneko, T.; Lipinksi, C. A.; Bradford, J.; Dole, K.; Spektor, A.; Gregory, K.; Blondeau, D.; Ernst, S.; Yang, J.; Goncharoff, N.; Hohman, M.; Bunin, B. Analysis and hit filtering of a very large library of compounds screened against Mycobacterium tuberculosis Mol. BioSyst. 2010, 6, 2316-2324
77. Periwal, V.; Rajappan, J. K.; Jaleel, A. U.; Scaria, V. Predictive models for anti-tubercular molecules using machine learning on high-throughput biological screening datasets BMC Res. Notes 2011, 4, 504
78. Periwal, V.; Kishtapuram, S.; Consortium, O. S.; Scaria, V. Computational models for in-vitro anti-tubercular activity of molecules based on high-throughput chemical biology screening datasets BMC Pharmacol. 2012, 12 (1) 1
79. Lin, P. L. Modeling pathogen and host: In vitro, in vivo and in silico models of latent Mycobacterium tuberculosis infection Drug Discovery Today: Dis. Models 2005, 2, 149-154
80. Toyohara, M. Aspects of the antituberculous activity of 27753-RP, a new semisynthetic derivative of griselimycine Ann. Inst. Pasteur/Microbiol. 1987, 138 (6) 737-744
81. Chekmarev, D. S.; Kholodovych, V.; Balakin, K. V.; Ivanenkov, Y.; Ekins, S.; Welsh, W. J. Shape signatures: new descriptors for predicting cardiotoxicity in silico Chem. Res. Toxicol. 2008, 21 (6) 1304-1314
82. Ekins, S.; Balakin, K. V.; Savchuk, N.; Ivanenkov, Y. Insights for human ether-a-go-go-related gene potassium channel inhibition using recursive partitioning and Kohonen and Sammon mapping techniques J. Med. Chem. 2006, 49 (17) 5059-5071
83. Ekins, S.; Crumb, W. J.; Sarazan, R. D.; Wikel, J. H.; Wrighton, S. A. Three-dimensional quantitative structure-activity relationship for inhibition of human ether-a-go-go-related gene potassium channel J. Pharmacol. Exp. Ther. 2002, 301 (2) 427-434
84. Hawn, T. R.; Matheson, A. I.; Maley, S. N.; Vandal, O. Host-directed therapeutics for tuberculosis: Can we harness the host? Microbiol. Mol. Biol. Rev. 2013, 77, 608-627