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161. Choi Y, Lee SW, Kim A, Jang K, Nam H, Cho YL, Yu K-S, Jang I-J, Chung J-Y (2017)
Safety, tolerability and pharmacokinetics of 21 day multiple oral administration of a new
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J Infect Dis 202:745–751
164. Aagaard C, Hoang T, Dietrich J, Cardona P-J, Izzo A, Dolganov G, Schoolnik GK,
Cassidy JP, Billeskov R, Andersen P (2011) A multistage tuberculosis vaccine that confers
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lead generation: beyond high-throughput screening. Nat Rev Drug Discov 2:369–378
166. Agatonovic-Kustrin S, Beresford R (2000) Basic concepts of artificial neural network
(ANN) modeling and its application in pharmaceutical research. J Pharm Biomed Anal
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167. Cherkasov A, Hilpert K, Jenssen H, Fjell CD, Waldbrook M, Mullaly SC, Volkmer R,
Hancock RE (2008) Use of artificial intelligence in the design of small peptide antibiotics
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design and discovery. Curr Pharm Des 13:1497–1508
169. Martínez-Romero M, Vázquez-Naya JM, Rabunal RJ, Pita-Fernández S, Macenlle R,
Castro-Alvariño J, López-Roses L, Ulla LJ, Martinez-Calvo VA, Vázquez S (2010) Artificial
intelligence techniques for colorectal cancer drug metabolism: ontologies and complex
networks. Curr Drug Metab 11:347–368
170. Fujiwara T, Kamada M, Okuno Y (2018) Artificial intelligence in drug discovery. Gan to
kagaku ryoho Cancer Chemother 45:593–596
346
A. C. Pushkaran et al.
mining in the search of a motif responsible for the activity of a diverse class of
antituberculosis agents. J Chem Inf Model 46:17–23
156. Dalecki AG, Wolschendorf F (2016) Development of a web-based tool for automated
processing and cataloging of a unique combinatorial drug screen. J Microbiol Methods
126:30–34
157. Sharma A, Dutta P, Sharma M, Rajput NK, Dodiya B, Georrge JJ, Kholia T, Bhardwaj A
(2014) BioPhytMol: a drug discovery community resource on anti-mycobacterial phytomolecules and plant extracts. J Cheminform 6:46
158. Lin K, O’Brien KM, Trujillo C, Wang R, Wallach JB, Schnappinger D, Ehrt S (2016)
Mycobacterium tuberculosis thioredoxin reductase is essential for thiol redox homeostasis
but plays a minor role in antioxidant defense. PLoS Pathog 12:e1005675
159. Shigyo K, Ocheretina O, Merveille YM, Johnson WD, Pape JW, Nathan CF, Fitzgerald DW
(2013) Efficacy of nitazoxanide against clinical isolates of Mycobacterium tuberculosis.
Antimicrob Agents Chemother 2834–2837
160. Li X, Hernandez V, Rock FL, Choi W, Mak YS, Mohan M, Mao W, Zhou Y, Easom EE,
Plattner JJ (2017) Discovery of a potent and specific M. tuberculosis Leucyl-tRNA
synthetase inhibitor:(S)-3-(Aminomethyl)-4-chloro-7-(2-hydroxyethoxy) benzo [c][1, 2]
oxaborol-1 (3 H)-ol (GSK656). J Med Chem 60:8011–8026
161. Choi Y, Lee SW, Kim A, Jang K, Nam H, Cho YL, Yu K-S, Jang I-J, Chung J-Y (2017)
Safety, tolerability and pharmacokinetics of 21 day multiple oral administration of a new
oxazolidinone antibiotic, LCB01-0371, in healthy male subjects. J Antimicrob Chemother
73:183–190
162. Shoen C, DeStefano M, Hafkin B, Cynamon M (2018) In vitro and in vivo activity of
contezolid (MRX-I) against Mycobacterium tuberculosis. Antimicrob Agents Chemother
00493-18
163. Wallis RS, Jakubiec WM, Kumar V, Silvia AM, Paige D, Dimitrova D, Li X, Ladutko L,
Campbell S, Friedland G (2010) Pharmacokinetics and whole-blood bactericidal activity
against Mycobacterium tuberculosis of single doses of PNU-100480 in healthy volunteers.
J Infect Dis 202:745–751
164. Aagaard C, Hoang T, Dietrich J, Cardona P-J, Izzo A, Dolganov G, Schoolnik GK,
Cassidy JP, Billeskov R, Andersen P (2011) A multistage tuberculosis vaccine that confers
efficient protection before and after exposure. Nat Med 17:189–194
165. Bleicher KH, Böhm H-J, Müller K, Alanine AI (2003) A guide to drug discovery: hit and
lead generation: beyond high-throughput screening. Nat Rev Drug Discov 2:369–378
166. Agatonovic-Kustrin S, Beresford R (2000) Basic concepts of artificial neural network
(ANN) modeling and its application in pharmaceutical research. J Pharm Biomed Anal
22:717–727
167. Cherkasov A, Hilpert K, Jenssen H, Fjell CD, Waldbrook M, Mullaly SC, Volkmer R,
Hancock RE (2008) Use of artificial intelligence in the design of small peptide antibiotics
effective against a broad spectrum of highly antibiotic-resistant superbugs. ACS Chem Biol
4:65–74
168. Duch W, Swaminathan K, Meller J (2007) Artificial intelligence approaches for rational drug
design and discovery. Curr Pharm Des 13:1497–1508
169. Martínez-Romero M, Vázquez-Naya JM, Rabunal RJ, Pita-Fernández S, Macenlle R,
Castro-Alvariño J, López-Roses L, Ulla LJ, Martinez-Calvo VA, Vázquez S (2010) Artificial
intelligence techniques for colorectal cancer drug metabolism: ontologies and complex
networks. Curr Drug Metab 11:347–368
170. Fujiwara T, Kamada M, Okuno Y (2018) Artificial intelligence in drug discovery. Gan to
kagaku ryoho Cancer Chemother 45:593–596
346
A. C. Pushkaran et al.