School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK.
Department of Medical Physics and Biomedical Engineering, Malet Place Engineering Building, University College London, Gower Street, London WC1E 6BT, UK.
Brief Funct Genomics. 2024 Sep 27;23(5):517-524. doi: 10.1093/bfgp/elae007.
The expansion of high-quality, low-cost sequencing has created an enormous opportunity to understand how genetic variants alter cellular behaviour in disease. The high diversity of mutations observed has however drawn a spotlight onto the need for predictive modelling of mutational effects on phenotype from variants of uncertain significance. This is particularly important in the clinic due to the potential value in guiding clinical diagnosis and patient treatment. Recent computational modelling has highlighted the importance of mutation induced protein misfolding as a common mechanism for loss of protein or domain function, aided by developments in methods that make large computational screens tractable. Here we review recent applications of this approach to different genes, and how they have enabled and supported subsequent studies. We further discuss developments in the approach and the role for the approach in light of increasingly high throughput experimental approaches.
高通量、低成本测序的发展为研究遗传变异如何改变疾病中的细胞行为提供了巨大的机会。然而，观察到的突变多样性引起了人们对预测不确定意义变异对表型的突变效应的需求。由于在指导临床诊断和患者治疗方面具有潜在价值，这在临床上尤为重要。最近的计算模型强调了突变诱导的蛋白质错误折叠作为蛋白质或结构域功能丧失的常见机制的重要性，这得益于使大规模计算筛选变得可行的方法的发展。在这里，我们回顾了这种方法在不同基因中的最新应用，以及它们如何为随后的研究提供支持和帮助。我们还进一步讨论了该方法的发展以及该方法在越来越高通量的实验方法中的作用。
