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DOI 10.1016/j.compbiolchem.2025.108737

Медицинская библиотека · Computational biology and chemistry · 2025

Identification of sulfonamide drugs as allosteric inhibitor of Chikungunya virus envelope glycoprotein: An in silico approach for drug repurposing.

Gaur Mahendra, Dash Rudra Narayan, Subudhi Bharat Bhusan

СтатьяПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

Chikungunya virus (CHIKV) causes chronic arthritis affecting millions across over 100 countries, yet no approved antivirals exist, necessitating drug repurposing strategies. The CHIKV envelope protein E2 plays dual roles in viral entry and inflammatory responses but remains underexplored as a therapeutic target due to limited accessibility of binding cavities in the E2-E1 complex. This study aimed to identify druggable allosteric site in E2 and screen approved sulfonamide drugs as potential repurposing candidates. Computational analysis revealed a novel druggable cavity between domains A and B of E2, distinct from previously reported sites. Virtual screening of sulfonamide drug libraries using consensus scoring identified bosentan as the top candidate, demonstrating superior binding affinity, favorable bioavailability, low toxicity and established antiviral and anti-inflammatory properties. Molecular dynamics simulations validated bosentan's stability within the allosteric site, with real-time hydrogen bond analysis revealing sustained interactions with key residues Phe141, Ile136, Ser143 and Arg104, supported by hydrophobic contacts and sulfur-aromatic interactions. These findings suggest bosentan's potential as a CHIKV inhibitor through allosteric modulation of E2 function. The study demonstrates the viability of targeting allosteric sites in CHIKV E2 and prioritizes bosentan for experimental validation as a repurposed antiviral therapy.

Для цитирования: Gaur Mahendra, Dash Rudra Narayan, Subudhi Bharat Bhusan. Identification of sulfonamide drugs as allosteric inhibitor of Chikungunya virus envelope glycoprotein: An in silico approach for drug repurposing.. Computational biology and chemistry. 2025. DOI: 10.1016/j.compbiolchem.2025.108737.

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