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Computational Design of Protein-Based Inhibitors of Plasmodium vivax Subtilisin-Like 1 Protease

BACKGROUND: Malaria remains a major global health concern. The development of novel therapeutic strategies is critical to overcome the selection of multiresistant parasites. The subtilisin-like protease (SUB1) involved in the egress of daughter Plasmodium parasites from infected erythrocytes and in...

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Detalles Bibliográficos
Autores principales: Bastianelli, Giacomo, Bouillon, Anthony, Nguyen, Christophe, Le-Nguyen, Dung, Nilges, Michael, Barale, Jean-Christophe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4208747/
https://www.ncbi.nlm.nih.gov/pubmed/25343504
http://dx.doi.org/10.1371/journal.pone.0109269
Descripción
Sumario:BACKGROUND: Malaria remains a major global health concern. The development of novel therapeutic strategies is critical to overcome the selection of multiresistant parasites. The subtilisin-like protease (SUB1) involved in the egress of daughter Plasmodium parasites from infected erythrocytes and in their subsequent invasion into fresh erythrocytes has emerged as an interesting new drug target. FINDINGS: Using a computational approach based on homology modeling, protein–protein docking and mutation scoring, we designed protein–based inhibitors of Plasmodium vivax SUB1 (PvSUB1) and experimentally evaluated their inhibitory activity. The small peptidic trypsin inhibitor EETI-II was used as scaffold. We mutated residues at specific positions (P4 and P1) and calculated the change in free-energy of binding with PvSUB1. In agreement with our predictions, we identified a mutant of EETI-II (EETI-II-P4LP1W) with a Ki in the medium micromolar range. CONCLUSIONS: Despite the challenges related to the lack of an experimental structure of PvSUB1, the computational protocol we developed in this study led to the design of protein-based inhibitors of PvSUB1. The approach we describe in this paper, together with other examples, demonstrates the capabilities of computational procedures to accelerate and guide the design of novel proteins with interesting therapeutic applications.