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Dihydrofolate reductase (DHFR) is a well-known enzyme of the folate metabolic pathway and it is a validated drug target for leishmaniasis. However, only a few leads are reported against DHFR (DHFR), and thus, there is a need to identify new inhibitors. In this article, pharmacoinformatic tools such as molecular docking, virtual screening, absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiling, and molecular dynamics (MD) simulations were utilized to identify potential DHFR inhibitors. Initially, a natural DHFR substrate (dihydrofolate), a classical DHFR inhibitor (methotrexate), and a potent DHFR inhibitor, that is, "5-(3-(octyloxy)benzyl)pyrimidine-2,4-diamine" (LEAD) were docked in the active site of the DHFR and MD simulated to understand the binding mode characteristics of the substrates/inhibitors in the DHFR. The shape of the LEAD molecule was used as a query for shape-based virtual screening, while the three-dimensional structure of DHFR was utilized for docking-based virtual screening. In silico ADMET factors were also considered during virtual screening. These two screening processes yielded 25 suitable hits, which were further validated for their selectivity toward DHFR using molecular docking and prime molecular mechanics/generalized born surface area analysis in the human DHFR (DHFR). Best six hits, which were selective and energetically favorable for the DHFR, were chosen for MD simulations. The MD analysis showed that four of the hits exhibited very good binding affinity for DHFR with respect to DHFR, and two hits were found to be more selective than the reported potent DHFR inhibitor. The present study thus identifies hits that can be further designed and modified as potent DHFR inhibitors.
This article was published in the following journal.
Name: Journal of computational biology : a journal of computational molecular cell biology
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