Computational modeling and druggability assessment of Aggregatibacter actinomycetemcomitans leukotoxin.

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作者
Hakmi, Mohammed [1 ]
Bouricha, El Mehdi [1 ]
El Harti, Jaouad [2 ]
Amzazi, Said [3 ]
Belyamani, Lahcen [4 ]
Khanfri, Jamal Eddine [1 ]
Ibrahimi, Azeddine [1 ]
机构
[1] Medical Biotechnology Laboratory (MedBiotech), Bioinova Research Center, Faculty of Medicine and Pharmacy, Mohammed V University in Rabat, Morocco
[2] Therapeutic Chemistry Laboratory, Medical Biotechnology Laboratory (MedBiotech), Faculty of Medicine and Pharmacy, Mohammed V University in Rabat, Morocco
[3] Laboratory of Human Pathologies Biology, Department of Biology, Faculty of Sciences, and Genomic Center of Human Pathologies, Faculty of Medicine and Pharmacy, Mohammed V University, Rabat, Morocco
[4] Emergency Department, Military Hospital Mohammed V, Faculty of Medicine and Pharmacy, Mohammed V University, Rabat, Morocco
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Computational chemistry;
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摘要
The leukotoxin (LtxA) of Aggregatibacter actinomycetemcomitans (A. actinomycetemcomitans) is a protein exotoxin belonging to the repeat-in-toxin family (RTX). Numerous studies have demonstrated that LtxA may play a critical role in the pathogenicity of A. actinomycetemcomitans since hyper-leukotoxic strains have been associated with severe disease. Accordingly, considerable effort has been made to elucidate the mechanisms by which LtxA interacts with host cells and induce their death. However, these attempts have been hampered by the unavailability of a tertiary structure of the toxin, which limits the understanding of its molecular properties and mechanisms. In this paper, we used homology and template free modeling algorithms to build the complete tertiary model of LtxA at atomic level in its calcium-bound Holo-state. The resulting model was refined by energy minimization, validated by Molprobity and ProSA tools, and subsequently subjected to a cumulative 600ns of all-atom classical molecular dynamics simulation to evaluate its structural aspects. The druggability of the proposed model was assessed using Fpocket and FTMap tools, resulting in the identification of four putative cavities and fifteen binding hotspots that could be targeted by rational drug design tools to find new ligands to inhibit LtxA activity. © 2022
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