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. 2023 Apr 5;80(5):165.
doi: 10.1007/s00284-023-03282-4.

Identification of Potential Drug Targets in Erythrocyte Invasion Pathway of Plasmodium falciparum

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Identification of Potential Drug Targets in Erythrocyte Invasion Pathway of Plasmodium falciparum

Mohammad Mustafa Kazan et al. Curr Microbiol. .

Abstract

The erythrocyte invasion phase plays a critical role in multiplication, sexual determination, and drug resistance in Plasmodium falciparum. In order to identify the critical genes and pathways in the erythrocyte invasion phase, the gene set (GSE129949) and the RNA-Seq count data for the W2mef strain were used for further analysis. An integrative bioinformatics study was performed to scrutinize genes as potential drug targets. 487 differentially expressed genes (DEGs) with an adjusted P value < 0.001 enriched 47 Gene Ontology (GO) terms that were over-represented based on hyper-geometric analysis P value < 0.01. Protein-Protein interaction network analysis was done using DEGs with higher confidence interactions (PPI score threshold = 0.7). MCODE and cytoHubba apps were utilized to define the hub proteins and rank them based on multiple topological analyses and MCODE scores. Furthermore, Gene Set Enrichment Analysis (GSEA) was carried out by using 322 gene sets from the MPMP database. The genes involved in multiple significant gene sets were determined by leading-edge analysis. Our study identified six genes encoding proteins that could be potential drug targets involved in the erythrocyte invasion phase related to merozoites motility, cell-cycle regulation, G-dependent protein kinase phosphorylation in schizonts, control of microtubule assembly, and sexual commitment. The druggability of those proteins was calculated based on the DCI (Drug Confidence Index) and predicted binding pockets' values. The protein that showed the best binding pocket value was subjected to deep learning-based virtual screening. The study identified the best small molecule inhibitors in terms of drug-binding score against the proteins for inhibitor identification.

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