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孟德尔罕见病中蛋白质编码错义突变的分析:来自结构生物信息学的线索

Profiling of Protein-Coding Missense Mutations in Mendelian Rare Diseases: Clues from Structural Bioinformatics.

作者信息

Visibelli Anna, Finetti Rebecca, Niccolai Piero, Trezza Alfonso, Spiga Ottavia, Santucci Annalisa, Niccolai Neri

机构信息

Department of Biotechnology, Chemistry and Pharmacy, University of Siena, 53100 Siena, Italy.

Le Ricerche del BarLume Free Association, Ville di Corsano, Monteroni d'Arbia, 53014 Siena, Italy.

出版信息

Int J Mol Sci. 2025 Apr 25;26(9):4072. doi: 10.3390/ijms26094072.

DOI:10.3390/ijms26094072
PMID:40362311
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12071383/
Abstract

The growing availability of protein structural data from experimental methods and accurate predictive models provides the opportunity to investigate the molecular origins of rare diseases (RDs) reviewed in the Orpha.net database. In this study, we analyzed the topology of 5728 missense mutation sites involved in Mendelian RDs (MRDs), forming the basis of our structural bioinformatics investigation. Each mutation site was characterized by side-chain position within the overall 3D protein structure and side-chain orientation. Atom depth quantitation, achieved by using SADIC v2.0, allowed the classification of all the mutation sites listed in our database. Particular attention was given to mutations where smaller amino acids replaced bulky, outward-oriented residues in the outer structural layers. Our findings reveal that structural features that could lead to the formation of void spaces in the outer protein region are very frequent. Notably, we identified 722 cases where MRD-associated mutations could generate new surface pockets with the potential to accommodate pharmaceutical ligands. Molecular dynamics (MD) simulations further supported the prevalence of cryptic pocket formation in a subset of drug-binding protein candidates, underscoring their potential for structure-based drug discovery in RDs.

摘要

通过实验方法和精确预测模型获得的蛋白质结构数据越来越多,这为研究《孤儿病数据库》中所综述的罕见病(RD)的分子起源提供了机会。在本研究中,我们分析了5728个参与孟德尔罕见病(MRD)的错义突变位点的拓扑结构,这构成了我们结构生物信息学研究的基础。每个突变位点都由其在整个三维蛋白质结构中的侧链位置和侧链方向来表征。通过使用SADIC v2.0进行原子深度定量分析,我们能够对数据库中列出的所有突变位点进行分类。我们特别关注那些较小的氨基酸取代了外部结构层中体积较大、向外定向残基的突变。我们的研究结果表明,在蛋白质外部区域可能导致形成空隙空间的结构特征非常常见。值得注意的是,我们发现了722个案例,其中与MRD相关的突变可能会产生新的表面口袋,有潜力容纳药物配体。分子动力学(MD)模拟进一步支持了在一部分药物结合蛋白候选物中存在隐秘口袋形成的普遍性,强调了它们在基于结构的罕见病药物发现中的潜力。

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