Protein structure prediction based on a domain clustering database

Homology modeling, as a successful protein structure prediction method, has two major deficiencies, i.e., the lack of the templates (known structures), and the accuracy of alignment between the query (unknown structure) and its templates. To solve these problems, we have constructed a conservative domain clustering template database, and proposed a profile-based alignment algorithm based on the profile extracted from each domain clustering in the database. The extracted profile can well represent the information of the sequence and structure as well. Compared with other alignment methods, such as T-coffee and Smith-Water man, our results show that with this method it's possible to obtain a higher hit rate for template searching and a more accurate and reliable query-template alignment. Therefore, the quality of protein structure prediction can be improved.