Gerasimavicius Lukas, Teichmann Sarah A, Marsh Joseph A
MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom.
Cambridge Stem Cell Institute & Dept Medicine, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom; Canadian Institute for Advanced Research, Toronto, Canada.
Curr Opin Struct Biol. 2025 Jun;92:103023. doi: 10.1016/j.sbi.2025.103023. Epub 2025 Feb 22.
Despite massive sequencing efforts, understanding the difference between human pathogenic and benign variants remains a challenge. Computational variant effect predictors (VEPs) have emerged as essential tools for assessing the impact of genetic variants, although their performance varies. Initially, sequence-based methods dominated the field, but recent advances, particularly in protein structure prediction technologies like AlphaFold, have led to an increased utilization of structural information by VEPs aimed at scoring human missense variants. This review highlights the progress in integrating structural information into VEPs, showcasing novel models such as AlphaMissense, PrimateAI-3D, and CPT-1 that demonstrate improved variant evaluation. Structural data offers more interpretability, especially for non-loss-of-function variants, and provides insights into complex variant interactions in vivo. As the field advances, utilizing biomolecular complex structures will be pivotal for future VEP development, with recent breakthroughs in protein-ligand and protein-nucleic acid complex prediction offering new avenues.
尽管进行了大规模的测序工作，但理解人类致病变异和良性变异之间的差异仍然是一项挑战。计算变异效应预测器（VEP）已成为评估遗传变异影响的重要工具，尽管它们的性能各不相同。最初，基于序列的方法主导了该领域，但最近的进展，特别是在像AlphaFold这样的蛋白质结构预测技术方面，导致旨在对人类错义变异进行评分的VEP对结构信息的利用有所增加。本综述强调了将结构信息整合到VEP中的进展，展示了诸如AlphaMissense、PrimateAI-3D和CPT-1等新型模型，这些模型展示了改进的变异评估。结构数据提供了更多的可解释性，特别是对于非功能丧失变异，并深入了解了体内复杂的变异相互作用。随着该领域的发展，利用生物分子复合物结构对于未来VEP的发展至关重要，蛋白质-配体和蛋白质-核酸复合物预测方面的最新突破提供了新的途径。
