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DOI 10.1016/j.compbiolchem.2024.108048

Медицинская библиотека · Computational biology and chemistry · 2024

Unveiling potential repurposed drug candidates for Plasmodium falciparum through in silico evaluation: A synergy of structure-based approaches, structure prediction, and molecular dynamics simulations.

Das Abhichandan, Rajkhowa Sanchaita, Sinha Subrata, Zaki Magdi E A

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Аннотация

The rise of drug resistance in Plasmodium falciparum, rendering current treatments ineffective, has hindered efforts to eliminate malaria. To address this issue, the study employed a combination of Systems Biology approach and a structure-based pharmacophore method to identify a target against P. falciparum. Through text mining, 448 genes were extracted, and it was discovered that plasmepsins, found in the Plasmodium genus, play a crucial role in the parasite's survival. The metabolic pathways of these proteins were determined using the PlasmoDB genomic database and recreated using CellDesigner 4.4.2. To identify a potent target, Plasmepsin V (PF13_0133) was selected and examined for protein-protein interactions (PPIs) using the STRING Database. Topological analysis and global-based methods identified PF13_0133 as having the highest centrality. Moreover, the static protein knockout PPIs demonstrated the essentiality of PF13_0133 in the modeled network. Due to the unavailability of the protein's crystal structure, it was modeled and subjected to a molecular dynamics simulation study. The structure-based pharmacophore modeling utilized the modeled PF13_0133 (PfPMV), generating 10 pharmacophore hypotheses with a library of active and inactive compounds against PfPMV. Through virtual screening, two potential candidates, hesperidin and rutin, were identified as potential drugs which may be repurposed as potential anti-malarial agents.

Для цитирования: Das Abhichandan, Rajkhowa Sanchaita, Sinha Subrata, Zaki Magdi E A. Unveiling potential repurposed drug candidates for Plasmodium falciparum through in silico evaluation: A synergy of structure-based approaches, structure prediction, and molecular dynamics simulations.. Computational biology and chemistry. 2024. DOI: 10.1016/j.compbiolchem.2024.108048.

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