Exploring phytochemicals as potential pharmacological inhibitors for NS1 protein of Kyasanur forest disease virus using virtual screening, molecular docking, and molecular simulation approach

利用虚拟筛选、分子对接和分子模拟方法,探索植物化学物质作为基亚努尔森林病病毒NS1蛋白的潜在药理抑制剂。

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Abstract

BACKGROUND: Kyasanur forest disease virus (KFDV) remains a significant public health challenge due to the limitations of existing vaccines, creating a critical need for effective antiviral treatments. KFDV is a tick-borne virus responsible for 400-500 new cases annually, with a mortality rate of 3-5%. The nonstructural protein 1 (NS1), which plays crucial roles in host cell interactions, immune evasion, and viral replication, represents a promising target for antiviral drug development. OBJECTIVE: This study aims to identify potential antiviral compounds that inhibit the activity of KFDV NS1 protein using a computational pharmacological drug design approach. The objectives include determining the 3D structure of the NS1 protein through homology modeling, conducting virtual screening of phytochemicals to identify potential inhibitors, and performing molecular dynamics simulations to assess the stability and binding free energies of the selected compounds. METHODS: The 3D structure of KFDV NS1 protein was predicted using homology modeling and validated using Ramachandran plot analysis. Virtual screening of phytochemicals from the Indian Medicinal Plants, Phytochemistry And Therapeutics (IMPPAT) database was performed to identify potential NS1 inhibitors. The top 15 compounds with the highest binding affinities were selected and subjected to absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis. Molecular dynamics simulations were conducted in duplicates for 200 ns to evaluate the stability of the ligand-NS1 complexes, and an additional independent simulation with randomized initial velocities was performed to ensure statistical robustness. Binding free energies were calculated using the molecular mechanics-generalized born surface area (MM-GBSA) method to determine the binding strength of each compound. RESULTS: The 3D structure of the KFDV NS1 protein was determined using I-Tasser-MTD, Robetta, and Swiss Model servers, and a minimized model of I-Tasser, achieving an ERRAT score of 94.37, was selected. Virtual screening of 11,530 phytochemicals from the IMPPAT database identified the top 115 compounds after three screening phases. Out of the 15 screened compounds, L2, L3, and L5 demonstrated notable binding affinities of -9.34, -9.12, and -9.08 kcal/mol, respectively, compared to the FDA-approved antiviral dasabuvir, which had a binding affinity of -8.0 kcal/mol. Molecular dynamics simulations confirmed the stability of compounds L2 (IMPHY010294), L3 (IMPHY001281), L5 (IMPHY011162), and dasabuvir, with free-energy binding values of -62.97 ± 4.0, -77.22 ± 4.71, -62.07 ± 2.88, and -87.68 ± 4.31 kcal/mol, respectively. CONCLUSION: The computational analysis suggests that compounds L2 and L3 have strong binding affinities comparable to dasabuvir, indicating their potential as pharmacological inhibitors of the KFDV NS1 protein. Further validation through in vitro assays would complement these in silico findings.

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