Pegg Scott C H, Brown Shoshana, Ojha Sunil, Huang Conrad C, Ferrin Thomas E, Babbitt Patricia C
Dept of Biopharmaceutical Sciences, University of California, San Francisco 94143, USA.
Pac Symp Biocomput. 2005:358-69.
The prediction of protein function from structure or sequence data remains a problem best addressed by leveraging information available from previously determined structure-function relationships. In the case of enzymes, the study of mechanistically diverse superfamilies can provide a rich source of structure-function information useful in functional determination and enzyme engineering. To access these relationships using a computational resource, several issues must be addressed regarding the representation of enzyme function, the organization of structure-function relationships in the superfamily context, the handling of misannotations, and reliability of classifications and evidence. We discuss here our approaches to solving these problems in the development of a Structure-Function Linkage Database (SFLD) (online at http://sfld.rbvi.ucsf.edu).
从结构或序列数据预测蛋白质功能仍然是一个最好通过利用先前确定的结构-功能关系中可用信息来解决的问题。就酶而言,对机制多样的超家族的研究可以提供丰富的结构-功能信息来源,有助于功能确定和酶工程。为了使用计算资源获取这些关系,必须解决几个问题,包括酶功能的表示、超家族背景下结构-功能关系的组织、错误注释的处理以及分类和证据的可靠性。我们在此讨论在构建结构-功能联系数据库(SFLD,在线网址为http://sfld.rbvi.ucsf.edu)过程中解决这些问题的方法。