很多蛋白质的空间构象既不是唯一确定的，也非随机的无规卷曲，而是在不同有序状态之间动态变化；此外，一些天然或设计蛋白在环境改变或氨基酸序列细微改变时能呈现截然不同的稳定构象。类似构象多样性被认为赋予蛋白质通过突变产生新结构和功能的进化能力。另一方面，在蛋白质工程研究中，如何获得有新结构和功能的蛋白是重要但十分困难的课题。我们前期发现用统计能量函数从头设计的序列可呈现出构象多样性。本项目将在此基础上，发展主动设计蛋白质构象多样性的计算方法，并采用高效的在体实验方法进行检验；将从通过构象多样性获得恰当进化潜力的设计序列出发，采用蛋白互补分析的在体定向进化方法获得新的、能够与靶蛋白相互作用的人工蛋白，进一步分析其与靶蛋白相互作用的序列、结构基础。项目通过具体实例深入认识构象多样性的序列结构基础、对蛋白-蛋白相互作用等功能进化的可能意义，并为人工设计与定向进化蛋白质功能提供新思路与方法。

For many proteins, their three dimensional conformations are neither unique nor completely random. Instead, they change dynamically between different ordered conformational states. Some natural or designed proteins present stable, distinctive conformations upon small changes of environments or of amino acid sequences. Such conformational diversity is believed to be important for protein evolvability, by which proteins develop new structures and functions through sequence mutations. On the other hand, how to engineer proteins with novel structures and functions is an important but difficult subject of protein engineering. We have previously found that proteins designed de novo with a statistical energy function can be of conformational diversity. Built on this progress, the proposed research will develop computational methods that design conformational diversity on purpose. The designs will be verified with an efficient in vivo experimental approach. From sequences designed to have desired conformational diversity and thus strong evolutionary potentials, directed evolution with an in vivo protein complementarity analysis approach will be employed to engineer artificial proteins that can interact with selected protein targets. Further analysis will be carried out to understand the sequence and structure dependence of the engineered interactions. This research can deepen our understanding of protein conformational diversity in terms of its dependences on sequence and structure, its potential roles in the evolution of functions such as new protein-protein interactions. The research also aims at providing new strategies and methods for the rational design and directed evolution of novel protein functions.