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

dihydrofolate reductase enzyme (DHFR) is counted as one of the attractive and validated antimalarial drug targets. However, the point mutations in the active site of wild-type DHFR 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 DHFR. 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 DHFR (3QGT); double-mutant DHFR (3UM5 and 1J3J) and quadruple-mutant DHFR (1J3K) enzymes. A total of eight common 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 DHFR and could be further exploited as a scaffold to develop novel antimalarials. Communicated by Ramaswamy H. Sarma.