Data-driven discovery of chemical signatures for developing new inhibitors against human influenza viruses.

IF 4.3 2区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY
Levon Kharatyan, Smbat Gevorgyan, Hamlet Khachatryan, Anastasiya Shavina, Astghik Hakobyan, Mher Matevosyan, Hovakim Zakaryan
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引用次数: 0

Abstract

This study presents cheminformatics analysis of the antiviral chemical space targeting human influenza A and B viruses. By curating 407,366 small molecules from ChEMBL and PubChem, we evaluated physicochemical properties, structural motifs, and activity trends across phenotypic and target-based assays. We found that 90.6% of evaluated molecules met Lipinski's Rule of Five, with active compounds exhibiting higher topological polar surface area and hydrogen bond donor groups. Target-specific analyses revealed distinct profiles for neuraminidase (NA) and hemagglutinin (HA) inhibitors, including larger molecular weights and increased rotatable bonds. Structural characterization identified cyclohexene, dihydropyran, and pyrimidine rings as prevalent in highly active molecules, while phthalimide motifs correlated with inactivity. Clustering of phenotypic assay data highlighted four promising and unique antiviral candidates, with unexplored chemical space. We also identified five multi-target scaffolds, including the curcumin-like scaffold, demonstrating dual inhibitory potential against two viral proteins. Molecular docking experiments on molecules within one of these multi-target scaffolds indicated their potential as initial hit candidates. Combined RMSD, PDF and DCCM analyses across molecular dynamics simulations elucidated the binding behaviour of five curcumin-like candidates. Two ligands remained as stable as the reference antivirals, one showed target-specific loss of affinity, and two dissociated rapidly, indicating that the stable pair should be prioritised for subsequent in vitro validation. Overall, the findings of this study can aid computer-aided drug design efforts, contributing to the development of novel antiviral agents against human influenza viruses.

数据驱动的化学特征发现,用于开发新的人类流感病毒抑制剂。
本研究对针对甲型和乙型流感病毒的抗病毒化学空间进行了化学信息学分析。通过筛选来自ChEMBL和PubChem的407,366个小分子,我们通过表型和靶向性分析评估了物理化学性质、结构基序和活性趋势。我们发现90.6%的被评估分子符合Lipinski的五定律,活性化合物具有更高的拓扑极性表面积和氢键给基。目标特异性分析揭示了神经氨酸酶(NA)和血凝素(HA)抑制剂的不同特征,包括更大的分子量和增加的可旋转键。结构表征发现环己烯、二氢吡喃和嘧啶环在高活性分子中普遍存在,而邻苯二甲酸亚胺基序与不活性相关。表型分析数据的聚类突出了四种有前途和独特的抗病毒候选药物,具有未开发的化学空间。我们还鉴定了五种多靶点支架,包括姜黄素样支架,显示出对两种病毒蛋白的双重抑制潜力。对这些多靶点支架内的分子进行的分子对接实验表明,它们具有作为初始靶点候选者的潜力。结合RMSD、PDF和DCCM分析,在分子动力学模拟中阐明了五种姜黄素样候选物的结合行为。两个配体保持与参考抗病毒药物一样稳定,一个表现出靶向特异性亲和力丧失,两个解离迅速,表明稳定的对应该优先用于随后的体外验证。总的来说,这项研究的发现可以帮助计算机辅助药物设计工作,有助于开发针对人类流感病毒的新型抗病毒药物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
BMC Chemistry
BMC Chemistry Chemistry-General Chemistry
CiteScore
5.30
自引率
2.20%
发文量
92
审稿时长
27 weeks
期刊介绍: BMC Chemistry, formerly known as Chemistry Central Journal, is now part of the BMC series journals family. Chemistry Central Journal has served the chemistry community as a trusted open access resource for more than 10 years – and we are delighted to announce the next step on its journey. In January 2019 the journal has been renamed BMC Chemistry and now strengthens the BMC series footprint in the physical sciences by publishing quality articles and by pushing the boundaries of open chemistry.
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