Malaria is a life-threatening disease caused by parasites of the genus Plasmodium that are transmitted through the bite of infected female Anopheles mosquitoes. The essential role of fatty acids in the malarial parasite's liver and blood stages makes it a promising target for combating P. falciparum. However, the emergence of strains of the malarial parasite has limited the efficacy of currently available drugs against malaria. Therefore, there is an urgent need to develop new drugs that can target the parasite and overcome drug resistance. This study aimed to identify potential dipeptide inhibitors for the PfENR enzyme using in-silico methods. Virtual screening was performed using thelibrary of 400 dipeptides to identify lead dipeptides with an affinity towards PfENR. We observed dipeptides Trp-Trp, Trp-Phe, Trp-Tyr, Tyr-Phe are showing the best affinity against PfENR. Density Functional Theory (DFT) analysis was used to reveal the electronic structure and reactivity of the top dipeptides by calculating the HOMO-LUMO gap. Additionally, we assessed the pharmacokinetic and other relevant properties of the lead dipeptides. All the lead dipeptides followed Lipinski's rule of five (Ro5). Our findings suggest that the identified dipeptides have significant potential as inhibitors of PfENR and could lead to the development of a novel class of antimalarial drugs. This research provides valuable insights into developing effective drugs to combat malaria.
Keywords
PfENR; P. Falciparum; Dipeptide inhibitors; DFT.
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