1. Identification of selective mtb DHFR inhibitors by virtual screening and experimental approaches
- Author
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Juan He, Cong Li, Wei Hu, Chungen Li, Song Liu, Jing Sui, Tianyu Zhang, Qingxiang Sun, and Youfu Luo
- Subjects
Molecular Docking Simulation ,Pharmacology ,Databases, Factual ,Drug Discovery ,Organic Chemistry ,Humans ,Pain ,Molecular Medicine ,Computer Simulation ,Biochemistry - Abstract
mtbDHFR-targeting inhibition has become a promising approach for tuberculosis treatment. In the current research, a multi-step virtual screening effort toward ZINC and MCE databases was devoted to discover novel mtbDHFR inhibitors. Based on binding affinity of small molecules through molecular docking study in AutoDock Vina, the number of compounds was reduced to 952,688. Further, these compounds were employed by a step-by-step multiple docking programs of Schrödinger suite and filtered by pharmacokinetics and PAINS parameters. Finally, nine ZINC compounds and 400 MCE compounds were obtained. These compounds of binding ability were tested with mtbDHFR by FluoPol-ABPP approach established in this work. Finally, AF-353 compound was found to have strong binding effect to mtbDHFR. AF-353 was further tested for mtb and hDHFR enzymatic activities, and it was proved to possess 50-fold selectivity toward mtbDHFR over hDHFR. In silico MD simulation results supported this selectivity.
- Published
- 2022