In silico elucidation and inhibition studies of selected phytoligands against Mitogen activated protein kinases of protozoan parasites

Abstract

Parasitic MAPKs exhibiting significant divergence with humans and playing an imperative role in parasitic metabolic activities have been exploited from several years as important targets for development of novel therapeutics. In addition, the emergence of the drug resistant variants of parasitic diseases in the recent years has aroused a great need for the development of potent inhibitors against them. In the present study we selected the metabolically active MAPKs LmxMPK4, PfMAP2 and TbMAPK5 of the three parasitic protozoans Leishmania mexicana, Plasmodium falciparum and Trypanosoma brucei respectively. The homology modeling technique was used to develop the 3D structures of these proteins and the same was validated by PROCHECK, ERRAT, ProQ and ProSA web servers to check the reliability. Ten phytoligands were employed for molecular docking studies with these proteins to search for potent phytoligand as a broad spectrum inhibitor. In this regard two phytoligands (Aspidocarpine for LmxMPK4 & TbMAPK5 and Cubebin for PfMAP2) were found to be more effective inhibitors, in term of robust binding energy, strong inhibition constant and better interactions between protein-ligand complexes. Furthermore predicted ADME & Toxicity properties suggested that these identified phytoligands exhibited comparable results to control drugs potentiating them as persuasive therapeutic agents for Leishmania, Trypanosoma and Plasmodium sp.

Genome-wide identification and characterization of protein phosphatase 2C (PP2C) gene family in sunflower (Helianthus annuus L.) and their expression profiles in response to multiple abiotic stresses

“…The prediction of the 3D homology modeling of a protein structure is widely used due to its reliability, sensitive, time-saving, cost-effectiveness, and rapidity when compared with NMR or X-ray diffraction analyses. This alternative emerges from the advancement of in silico analysis tools [67][68][69]. Further, based on the transcriptomic expression analysis under different stress conditions, a total of six HanPP2C proteins (HanPP2C47, HanPP2C48, HanPP2C53, HanPP2C54, HanPP2C59, and HanPP2C73) were selected to construct the 3D homology models (Fig 9).…”

Diversity and Molecular Evolution of Antimicrobial Peptides in Caecilian Amphibians

“…In this context, the in silico characterisation of AMP 3D structures is certainly a cost-effective initial step for shedding light in the mechanisms of action of these diverse molecules. In fact, 3D-modelling techniques are nowadays used regularly in drug design, protein and peptide engineering, and targeted mutagenesis [75].…”

“…In contrast, the histone H2A-hipposin peptide (Figure 10) shows the opposite trend, with the caecilian sequence having good antimicrobial potential but with 3D-conformational differences to the database AMP. This may indicate a change in the mechanism of action, which is strongly related to the 3D conformation [75,76] or a change in functionality. These peptides with distinct 3D conformations may be relevant because they might represent novel AMPs exclusive to caecilians, potentially attracting pharmacological interest.…”

In Silico Molecular Docking and Dynamic Investigations of Bioactive Phytoconstituents from Fenugreek Seeds as a Potent Drug against DPP-IV Enzyme

“…Therefore, by implementing such advanced machine learning approaches, it is feasible to create a wide range of protein related data that can serve the purpose of sustainable protein concepts. 32,33 In this study, we employed machine learning approaches to identify potential therapeutics from the fenugreek seeds to inhibit DPP-IV enzyme.…”