Medicinal fungal secondary metabolites as potential inhibitors of the Chikungunya virus nsP2 protease: an integrated computational study

Chikungunya virus (CHIKV) is an emerging mosquito-borne alphavirus that causes millions of infections and severe arthralgia annually. Due to the lack of specific antiviral medications, analgesics and NSAIDs are used for symptomatic relief but are associated with potential hepatic, gastrointestinal, cardiovascular, and renal toxicities. This study investigated natural fungal secondary metabolites selected to target nsP2 protease (PDB ID: 3TRK), a key protein involved in chikungunya virus replication. 1830 fungal secondary metabolites were screened using intensive in silico approaches to identify potential nsP2 inhibitors. Based on their binding affinity, ADMET profiles, and post-docking MM-GBSA, HOMO-LUMO, and QSAR analyses, three lead compounds (MSIDs 000670, 001323, and 001565) were selected for further investigation alongside the control (Withaferin A). The 200 ns MD simulations provided insights into their stability, while DCCM, PCA, and post-simulation MM-GBSA analyses further supported their favorable dynamic behavior and binding stability. Among these candidates, MSID000670 (Erinacerin Q) and MSID001565 (Caputmedusin F) exhibited optimal ADME properties, reduced toxicity, higher binding scores, and a consistently stable MD simulation profile. Since these compounds are reported here for the first time as promising drug candidates, they need special attention in chikungunya antiviral drug development. However, experimental validation is needed to confirm their therapeutic potential.

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Journal
Scientific Reports
Published
2026-10-30
DOI
https://doi.org/10.1038/s41598-026-78703-y
Primary Topic
Computational Drug Discovery Methods
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article
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article

Medicinal fungal secondary metabolites as potential inhibitors of the Chikungunya virus nsP2 protease: an integrated computational study

Noimul Hasan Siddiquee, Lamia Islam, Md. Faysal, Md Uzzal Hosen et al.
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Scientific Reports
Computational Drug Discovery Methods
article

Medicinal fungal secondary metabolites as potential inhibitors of the Chikungunya virus nsP2 protease: an integrated computational study

Noimul Hasan Siddiquee, Lamia Islam, Md. Faysal, Md Uzzal Hosen, Khan Md Muhibul Alam Mueed, Md. Golam Rabby Ragu, Sajeda Aktery, Saad Ibn Omor, Afrida Anan
article en

Abstract

Chikungunya virus (CHIKV) is an emerging mosquito-borne alphavirus that causes millions of infections and severe arthralgia annually. Due to the lack of specific antiviral medications, analgesics and NSAIDs are used for symptomatic relief but are associated with potential hepatic, gastrointestinal, cardiovascular, and renal toxicities. This study investigated natural fungal secondary metabolites selected to target nsP2 protease (PDB ID: 3TRK), a key protein involved in chikungunya virus replication. 1830 fungal secondary metabolites were screened using intensive in silico approaches to identify potential nsP2 inhibitors. Based on their binding affinity, ADMET profiles, and post-docking MM-GBSA, HOMO-LUMO, and QSAR analyses, three lead compounds (MSIDs 000670, 001323, and 001565) were selected for further investigation alongside the control (Withaferin A). The 200 ns MD simulations provided insights into their stability, while DCCM, PCA, and post-simulation MM-GBSA analyses further supported their favorable dynamic behavior and binding stability. Among these candidates, MSID000670 (Erinacerin Q) and MSID001565 (Caputmedusin F) exhibited optimal ADME properties, reduced toxicity, higher binding scores, and a consistently stable MD simulation profile. Since these compounds are reported here for the first time as promising drug candidates, they need special attention in chikungunya antiviral drug development. However, experimental validation is needed to confirm their therapeutic potential.

Scientific Reports
Noakhali Science and Technology University (BD), Mawlana Bhashani Science and Technology University (BD), Jagannath University (BD), University of Chittagong (BD), Jashore University of Science and Technology (BD)
Good health and well-being
Openalex Percentile: Top 14%
Computational Drug Discovery Methods
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