CMASA: an accurate algorithm for detecting local protein structural similarity and its application to enzyme catalytic site annotation.

KIZ OpenIR > 结构生物信息学

	CMASA: an accurate algorithm for detecting local protein structural similarity and its application to enzyme catalytic site annotation.
	Li GH 1,2,3; Huang JF*1,3; huangjf@mail.kiz.ac.cn
	2010
发表期刊	BMC BIOINFORMATICS
卷号	11 期号:X 页码:e439
合作性质	其它
摘要	BACKGROUND: The rapid development of structural genomics has resulted in many "unknown function" proteins being deposited in Protein Data Bank (PDB), thus, the functional prediction of these proteins has become a challenge for structural bioinformatics. Several sequence-based and structure-based methods have been developed to predict protein function, but these methods need to be improved further, such as, enhancing the accuracy, sensitivity, and the computational speed. Here, an accurate algorithm, the CMASA (Contact MAtrix based local Structural Alignment algorithm), has been developed to predict unknown functions of proteins based on the local protein structural similarity. This algorithm has been evaluated by building a test set including 164 enzyme families, and also been compared to other methods. RESULTS: The evaluation of CMASA shows that the CMASA is highly accurate (0.96), sensitive (0.86), and fast enough to be used in the large-scale functional annotation. Comparing to both sequence-based and global structure-based methods, not only the CMASA can find remote homologous proteins, but also can find the active site convergence. Comparing to other local structure comparison-based methods, the CMASA can obtain the better performance than both FFF (a method using geometry to predict protein function) and SPASM (a local structure alignment method); and the CMASA is more sensitive than PINTS and is more accurate than JESS (both are local structure alignment methods). The CMASA was applied to annotate the enzyme catalytic sites of the non-redundant PDB, and at least 166 putative catalytic sites have been suggested, these sites can not be observed by the Catalytic Site Atlas (CSA). CONCLUSIONS: The CMASA is an accurate algorithm for detecting local protein structural similarity, and it holds several advantages in predicting enzyme active sites. The CMASA can be used in large-scale enzyme active site annotation. The CMASA can be available by the mail-based server (http://159.226.149.45/other1/CMASA/CMASA.htm).
资助者	This work was supported by the National Basic Research Program of China (Grant No. 2007CB815705; 2009CB941300), the National Natural Science Foundation of China (Grant No. 30623007) and Chinese Academy of Sciences (Grant No. 2007211311091). ; This work was supported by the National Basic Research Program of China (Grant No. 2007CB815705; 2009CB941300), the National Natural Science Foundation of China (Grant No. 30623007) and Chinese Academy of Sciences (Grant No. 2007211311091). ; This work was supported by the National Basic Research Program of China (Grant No. 2007CB815705; 2009CB941300), the National Natural Science Foundation of China (Grant No. 30623007) and Chinese Academy of Sciences (Grant No. 2007211311091). ; This work was supported by the National Basic Research Program of China (Grant No. 2007CB815705; 2009CB941300), the National Natural Science Foundation of China (Grant No. 30623007) and Chinese Academy of Sciences (Grant No. 2007211311091).
收录类别	SCI
语种	英语
资助者	This work was supported by the National Basic Research Program of China (Grant No. 2007CB815705; 2009CB941300), the National Natural Science Foundation of China (Grant No. 30623007) and Chinese Academy of Sciences (Grant No. 2007211311091). ; This work was supported by the National Basic Research Program of China (Grant No. 2007CB815705; 2009CB941300), the National Natural Science Foundation of China (Grant No. 30623007) and Chinese Academy of Sciences (Grant No. 2007211311091). ; This work was supported by the National Basic Research Program of China (Grant No. 2007CB815705; 2009CB941300), the National Natural Science Foundation of China (Grant No. 30623007) and Chinese Academy of Sciences (Grant No. 2007211311091). ; This work was supported by the National Basic Research Program of China (Grant No. 2007CB815705; 2009CB941300), the National Natural Science Foundation of China (Grant No. 30623007) and Chinese Academy of Sciences (Grant No. 2007211311091).
文献类型	期刊论文
条目标识符	http://ir.kiz.ac.cn/handle/152453/6343
专题	结构生物信息学遗传资源与进化国家重点实验室
通讯作者	huangjf@mail.kiz.ac.cn
作者单位	1.State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, 32, Eastern Jiaochang Road, Kunming, Yunnan 650223, China 2.Graduate School of Chinese Academy of Sciences, Beijing 100039, China 3.Kunming Institute of Zoology-Chinese University of Hongkong Joint Research Center for Bio-resources and Human Disease Mechanisms, Kunming 650223, China
推荐引用方式 GB/T 7714	Li GH,Huang JF*,huangjf@mail.kiz.ac.cn. CMASA: an accurate algorithm for detecting local protein structural similarity and its application to enzyme catalytic site annotation.[J]. BMC BIOINFORMATICS,2010,11(X):e439.
APA	Li GH,Huang JF*,&huangjf@mail.kiz.ac.cn.(2010).CMASA: an accurate algorithm for detecting local protein structural similarity and its application to enzyme catalytic site annotation..BMC BIOINFORMATICS,11(X),e439.
MLA	Li GH,et al."CMASA: an accurate algorithm for detecting local protein structural similarity and its application to enzyme catalytic site annotation.".BMC BIOINFORMATICS 11.X(2010):e439.

条目包含的文件
文件名称/大小	文献类型	版本类型	开放类型	使用许可
2010110104.pdf（1456KB）	期刊论文	出版稿	开放获取	CC BY-NC-SA	请求全文