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Discovery of novel and potent InhA inhibitors by an in silico screening and pharmacokinetic prediction
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Document Title
Discovery of novel and potent InhA inhibitors by an in silico screening and pharmacokinetic prediction
Author
Hanwarinroj C, Phusi N, Kamsri B, Kamsri P, Punkvang A, Ketrat S, Saparpakorn P, Hannongbua S, Suttisintong K, Kittakoop P, Spencer J, Mulholland AJ, Pungpo P
Name from Authors Collection
Affiliations
Ubon Ratchathani University; Nakhon Phanom University; Vidyasirimedhi Institute of Science & Technology; Kasetsart University; National Science & Technology Development Agency - Thailand; National Nanotechnology Center (NANOTEC); Chulabhorn Research Institute; Chulabhorn Graduate Institute; Chulabhorn Royal Academy; University of Bristol; University of Bristol
Type
Article
Source Title
FUTURE MEDICINAL CHEMISTRY
Year
2022
Volume
14
Issue
10
Page
717-729
Open Access
hybrid, Green Published
Publisher
FUTURE SCI LTD
DOI
10.4155/fmc-2021-0348
Format
Abstract
Aim: In silico screening approaches were performed to discover novel InhA inhibitors. Methods: Candidate InhA inhibitors were obtained from the combination of virtual screening and pharmacokinetic prediction. In addition, molecular mechanics Poisson-Boltzmann surface area, molecular mechanics Generalized Born surface area and WaterSwap methods were performed to investigate the binding interactions and binding energy of candidate compounds. Results: Four candidate compounds with suitable physicochemical, pharmacokinetic and antibacterial properties are proposed. The crucial interactions of the candidate compounds were H-bond, pi-pi and sigma-pi interactions observed in the InhA binding site. The binding affinity of these compounds was improved by hydrophobic interactions with hydrophobic side chains in the InhA pocket. Conclusion: The four newly identified InhA inhibitors reported in this study could serve as promising hit compounds against Mycobacterium tuberculosis and may be considered for further experimental studies.
Industrial Classification
Knowledge Taxonomy Level 1
Knowledge Taxonomy Level 2
Knowledge Taxonomy Level 3
Funding Sponsor
Thailand Research Fund [RSA5980057]; RGJ Advanced Programme [RAP60K0009]; Ubon Ratchathani University; Thailand Graduate Institute of Science and Technology (TGIST) [SCA-CO-2560-4375TH, SCACO-2563-12135-TH]; Royal Golden Jubilee PhD Program [PHD/0132/2559]; EPSRC [EP/M027546/1, EP/M022609/1]
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Publication Source
WOS