Potent Inhibition of Chikungunya Virus Entry by a Pyrazole–Benzene Derivative: A Computational Study Targeting the E1–E2 Glycoprotein Complex

The Chikungunya virus (CHIKV) continues to pose a significant global health challenge due to the absence of effective antiviral treatments and limited vaccine availability. This study employed a comprehensive in silico workflow, incorporating high-throughput virtual screening, binding free-energy calculations, ADMET (absorption, distribution, metabolism, excretion, and toxicity) analysis, and 200 ns molecular dynamics (MD) simulations, to identify new inhibitors targeting the E1-E2 glycoprotein complex, crucial for CHIKV entry and membrane fusion. Four promising candidates were identified from a library of 20,000 compounds, with CID 136801451 showing the most potent binding (docking score: -10.227; ΔG_bind: -51.53 kcal/mol). The top four compounds exhibited favorable ADMET profiles, meeting nearly all criteria. MD simulations confirmed stable binding and strong interactions between CID 136801451 and the E1-E2 complex, evidenced by consistently low RMSD values. These findings highlight CID 136801451 as a promising CHIKV entry inhibitor, warranting further in vitro and in vivo evaluation to advance the development of effective anti-CHIKV therapeutics.

Authors

Institutions

Publication Details

Journal
International Journal of Molecular Sciences
Published
2025-07-05
DOI
https://doi.org/10.3390/ijms26136480
Citations
1
Primary Topic
Mosquito-borne diseases and control
Type
article
Field-Weighted Citation Impact
1.88

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Potent Inhibition of Chikungunya Virus Entry by a Pyrazole–Benzene Derivative: A Computational Study Targeting the E1–E2 Glycoprotein Complex

Md. Belayet Hasan Limon, Afsana Nahid, Mohammad Mamun Alam, Mohammed Ziaur Rahman et al.
1 citations
International Journal of Molecular Sciences
Mosquito-borne diseases and control
1.88
article

Potent Inhibition of Chikungunya Virus Entry by a Pyrazole–Benzene Derivative: A Computational Study Targeting the E1–E2 Glycoprotein Complex

Md. Belayet Hasan Limon, Afsana Nahid, Mohammad Mamun Alam, Mohammed Ziaur Rahman, Pradip Kumar Saha, Tanvir Ahmed Saikat, Md. Mahbubur Rahman
article en
1 citations

Abstract

The Chikungunya virus (CHIKV) continues to pose a significant global health challenge due to the absence of effective antiviral treatments and limited vaccine availability. This study employed a comprehensive in silico workflow, incorporating high-throughput virtual screening, binding free-energy calculations, ADMET (absorption, distribution, metabolism, excretion, and toxicity) analysis, and 200 ns molecular dynamics (MD) simulations, to identify new inhibitors targeting the E1-E2 glycoprotein complex, crucial for CHIKV entry and membrane fusion. Four promising candidates were identified from a library of 20,000 compounds, with CID 136801451 showing the most potent binding (docking score: -10.227; ΔG_bind: -51.53 kcal/mol). The top four compounds exhibited favorable ADMET profiles, meeting nearly all criteria. MD simulations confirmed stable binding and strong interactions between CID 136801451 and the E1-E2 complex, evidenced by consistently low RMSD values. These findings highlight CID 136801451 as a promising CHIKV entry inhibitor, warranting further in vitro and in vivo evaluation to advance the development of effective anti-CHIKV therapeutics.

International Journal of Molecular SciencesVol. 26(13)
University of Louisville (US), International Centre for Diarrhoeal Disease Research (BD)
Global Affairs Canada, International Centre for Diarrhoeal Disease Research, Bangladesh
Openalex Percentile: Top 14%
Mosquito-borne diseases and control
1.88
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.