Nandigrami Prithviraj, Fiser Andras
Departments of Systems & Computational Biology, and Biochemistry, Albert Einstein College of Medicine 1300 Morris Park Ave, Bronx, NY 10461, USA.
bioRxiv. 2023 Jan 27:2023.01.26.525812. doi: 10.1101/2023.01.26.525812.
Many biomedical applications, such as classification of binding specificities or bioengineering, depend on the accurate definition of protein binding interfaces. Depending on the choice of method used, substantially different sets of residues can be classified as belonging to the interface of a protein. A typical approach used to verify these definitions is to mutate residues and measure the impact of these changes on binding. Besides the lack of exhaustive data this approach generates, it also suffers from the fundamental problem that a mutation introduces an unknown amount of alteration into an interface, which potentially alters the binding characteristics of the interface. In this study we explore the impact of alternative binding site definitions on the ability of a protein to recognize its cognate ligand using a pharmacophore approach, which does not affect the interface. The study also provides guidance on the minimum expected accuracy of interface definition that is required to capture the biological function of a protein.
许多生物医学应用,如结合特异性分类或生物工程,都依赖于蛋白质结合界面的准确定义。根据所使用方法的不同,大量不同的残基集可能被归类为属于蛋白质的界面。用于验证这些定义的典型方法是对残基进行突变,并测量这些变化对结合的影响。除了这种方法产生的数据不够详尽之外,它还存在一个根本问题,即突变会在界面中引入未知量的改变,这可能会改变界面的结合特性。在本研究中,我们使用药效团方法探索了替代结合位点定义对蛋白质识别其同源配体能力的影响,该方法不会影响界面。该研究还为捕获蛋白质生物学功能所需的界面定义的最低预期准确性提供了指导。