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Research Article

Multicomplex-based pharmacophore modeling in conjunction with multi-target docking and molecular dynamics simulations for the identification of PfDHFR inhibitors

ORCID Icon, ORCID Icon & ORCID Icon
Pages 4181-4199 | Received 24 Jul 2018, Accepted 15 Oct 2018, Published online: 16 Jan 2019
 

Abstract

Plasmodium falciparum dihydrofolate reductase enzyme (PfDHFR) is counted as one of the attractive and validated antimalarial drug targets. However, the point mutations in the active site of wild-type PfDHFR have developed resistance against the well-known antifolates. Therefore, there is a dire need for the development of inhibitors that can inhibit both wild-type and mutant-type DHFR enzyme. In the present contribution, we have constructed the common feature pharmacophore models from the available PfDHFR. A representative hypothesis was prioritized and then employed for the screening of natural product library to search for the molecules with complementary features responsible for the inhibition. The screened candidates were processed via drug-likeness filters and molecular docking studies. The docking was carried out on the wild-type PfDHFR (3QGT); double-mutant PfDHFR (3UM5 and 1J3J) and quadruple-mutant PfDHFR (1J3K) enzymes. A total of eight common hits were obtained from the docking calculations that could be the potential inhibitors for both wild and mutant type DHFR enzymes. Eventually, the stability of these candidates with the selected proteins was evaluated via molecular dynamics simulations. Except for SPECS14, all the prioritized candidates were found to be stable throughout the simulation run. Overall, the strategy employed in the present work resulted in the retrieval of seven candidates that may show inhibitory activity against PfDHFR and could be further exploited as a scaffold to develop novel antimalarials.

Communicated by Ramaswamy H. Sarma

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

Anu Manhas and PCJ acknowledge Science and Engineering Research Board (SERB), Department of Science and Technology (DST) for project grant through grant number [EMR/2016/003025]. Mohsin Yousuf Lone acknowledge the University Grants Commission (UGC), Govt. of India for the financial assistance.

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