随着全基因组技术的快速发展及基因测序成本的显著降低，产生了大量的基因组数据。然而，对于基因组数据的解释以及遗传变异与疾病和表型之间关联的预测，仍需要显著提高。错义突变可以使蛋白质失去功能，可能导致许多疾病的发生和发展。由错义突变造成的影响可以通过计算机模拟来确定，更可行地找到治疗手段并逆转效应。特异性人类表型在很大程度上由蛋白质的稳定性，活性和与其它生物分子的相互作用共同决定，以此提供特定的细胞功能。因此，分析错义突变对蛋白质及其复合物的影响，将为我们识别功能重要的错义突变和了解疾病的分子机制提供重要的线索。在这个项目中，课题组将继续从事计算方法和工具的开发，以估计序列变体和疾病突变对蛋白质稳定性，结合亲和力和功能的影响，并调查突变影响的分子作用机制。同时，我们将积极与实验课题组和医院合作，促进计算预测与实验调查之间的有效互动，为疾病诊断，预防和治疗做出贡献。

There has been a rapid development of genome-wide techniques in the last decade along with significant lowering of the cost of gene sequencing, which generated widely available genomic data. However, the interpretation of genomic data and prediction of the association of genetic variations with diseases and phenotypes still require significant improvement. Missense mutations can render proteins nonfunctional and may be responsible for many diseases. The effects caused by missense mutations can be pinpointed by in silico modeling that makes it more feasible to find a treatment and reverse the effect. Specific human phenotype is largely determined by stability, activity, and interactions between proteins and with other biomolecules which work together to provide specific cellular functions. Therefore, the analysis of the effects of missense mutations on proteins and their complexes would give us important clues for identifying functionally important missense mutations and understanding the molecular mechanisms of diseases. In this project, we will continue our research towards developing powerful computational methods and tools to estimate the effects of sequence variants and disease mutations on protein stability, binding affinity and function, and provide a mechanistic understanding for impact of each mutation. Meanwhile, we will actively collaborate with experimental groups and hospitals to promote fruitful interplay between computational prediction and experimental investigation and contribute to the disease diagnose, prevention and treatment.