跨甲状腺素突变景观的综合结构分析和配体优化。

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Ugo Lomoio, Valentina Carbonari, Federico Manuel Giorgi, Francesco Ortuso, Pietro Lió, Pierangelo Veltri, Pietro Hiram Guzzi
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引用次数: 0

摘要

转甲状腺素淀粉样变性(ATTR)是一种由转甲状腺素(TTR)蛋白不稳定突变引起的遗传多样性疾病,导致病理性聚集。虽然像他法米迪斯和acoramidis这样的稳定剂已被批准,但它们对TTR变体的疗效仍不清楚。本研究提出了一个集成了AlphaFold3进行结构预测、ESM2进行序列嵌入、DiffDock-L和AutoDock Vina进行分子对接以及DiffSBDD进行配体生成的硅管道。模拟结果表明,在TTR变异体中,被批准的配体的结合亲和力存在显著差异,一些突变(如W61L、Y98F)尽管距离结合位点较远,但仍能降低结合。基于嵌入的聚类突出了潜在的良性突变,并支持可扩展的变体分类。此外,定制配体优化可以在特定情况下恢复结合亲和力,尽管效果依赖于突变。这些发现强调了变体感知治疗策略的必要性。这种综合方法为ATTR的精确药物设计提供了基础,使开发针对个体突变谱的个性化稳定剂成为可能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrative structural profiling and ligand optimisation across the transthyretin mutational landscape.

Transthyretin amyloidosis (ATTR) is a genetically diverse disorder caused by destabilising mutations in the transthyretin (TTR) protein, leading to pathological aggregation. While stabilisers like tafamidis and acoramidis are approved, their efficacy across TTR variants remains unclear. This study presents an in silico pipeline combining AlphaFold3 for structure prediction, ESM2 for sequence embeddings, DiffDock-L and AutoDock Vina for molecular docking, and DiffSBDD for ligand generation. Simulations show that binding affinities of approved ligands vary significantly among TTR variants, with some mutations (e.g., W61L, Y98F) reducing binding despite being distant from the binding site. Embedding-based clustering highlights potential benign mutations and supports scalable variant classification. Additionally, customised ligand optimisation can recover binding affinity in specific cases, though effects are mutation-dependent. These findings emphasise the need for variant-aware therapeutic strategies. This integrative approach offers a foundation for precision drug design in ATTR, enabling the development of personalised stabilisers tailored to individual mutational profiles.

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来源期刊
NPJ Systems Biology and Applications
NPJ Systems Biology and Applications Mathematics-Applied Mathematics
CiteScore
5.80
自引率
0.00%
发文量
46
审稿时长
8 weeks
期刊介绍: npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.
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