高通量虚拟筛选链霉菌代谢物作为尼帕病毒基质蛋白的抗病毒抑制剂。

IF 2.6 4区 生物学 Q2 BIOLOGY
Mark Andrian B. Macalalad , Nyzar Mabeth O. Odchimar , Fredmoore L. Orosco
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引用次数: 0

摘要

尼帕病毒(Nipah virus,NiV)对农业和人类健康都有影响,造成了严重的经济和健康后果,因此仍然是全球关注的一个重大问题。目前,该病毒尚无治愈方法或商业化疫苗。因此,必须优先发现新的有效治疗方案,以防止其继续传播。链霉菌属是代谢产物的丰富来源,它们对某些疾病具有生物活性;然而,它们作为抗尼帕病毒药物的潜力仍有待开发。在这项研究中,通过硅学方法筛选了 6524 种链霉菌代谢物,以确定它们对尼帕病毒基质蛋白(NiV-M)的抑制作用。在虚拟筛选过程中使用了不同的计算机辅助工具:ADMET分析揭示了913种安全性和有效性极佳的化合物;分子对接预测了配体在各自靶标中的结合位置和相关对接得分;MD模拟证实了在100 ns全原子模拟中得分最高的前十种配体的结合稳定性;PCA阐明了模拟的收敛性;MMPB(GB)SA计算估算了最终候选化合物的结合能,并确定了形成复合物的关键残基。通过使用硅学方法,我们确定了 6 个靶向主要底物结合位点的代谢物和 5 个靶向二聚化位点的代谢物,它们都表现出极佳的稳定性和很强的结合亲和力。我们建议在下一阶段的药物开发中测试这些化合物,以确认它们作为尼帕病毒治疗剂的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
High-throughput virtual screening of Streptomyces spp. metabolites as antiviral inhibitors against the Nipah virus matrix protein

Nipah virus (NiV) remains a significant global concern due to its impact on both the agricultural industry and human health, resulting in substantial economic and health consequences. Currently, there is no cure or commercially available vaccine for the virus. Therefore, it is crucial to prioritize the discovery of new and effective treatment options to prevent its continued spread. Streptomyces spp. are rich sources of metabolites known for their bioactivity against certain diseases; however, their potential as antiviral drugs against the Nipah virus remain unexplored. In this study, 6524 Streptomyces spp. metabolites were screened through in silico methods for their inhibitory effects against the Nipah virus matrix (NiV-M) protein, which assists in virion assembly of Nipah virus. Different computer-aided tools were utilized to carry out the virtual screening process: ADMET profiling revealed 913 compounds with excellent safety and efficacy profiles, molecular docking predicted the binding poses and associated docking scores of the ligands in their respective targets, MD simulations confirmed the binding stability of the top ten highest-scoring ligands in a 100 ns all-atom simulation, PCA elucidated simulation convergence, and MMPB(GB)SA calculations estimated the binding energies of the final candidate compounds and determined the key residues crucial for complex formation. Using in silico methods, we identified six metabolites targeting the main substrate-binding site and five targeting the dimerization site that exhibited excellent stability and strong binding affinity. We recommend testing these compounds in the next stages of drug development to confirm their effectiveness as therapeutic agents against Nipah virus.

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来源期刊
Computational Biology and Chemistry
Computational Biology and Chemistry 生物-计算机:跨学科应用
CiteScore
6.10
自引率
3.20%
发文量
142
审稿时长
24 days
期刊介绍: Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered. Given their inherent uncertainty, protein modeling and molecular docking studies should be thoroughly validated. In the absence of experimental results for validation, the use of molecular dynamics simulations along with detailed free energy calculations, for example, should be used as complementary techniques to support the major conclusions. Submissions of premature modeling exercises without additional biological insights will not be considered. Review articles will generally be commissioned by the editors and should not be submitted to the journal without explicit invitation. However prospective authors are welcome to send a brief (one to three pages) synopsis, which will be evaluated by the editors.
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