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Variational Bayesian Clustering on Protein Cavity Conformations for Detecting Influential Amino Acids
| Content Provider | CiteSeerX |
|---|---|
| Author | Guo, Ziyi Chen, Brian Y. |
| Abstract | Proteins are large flexible biological molecules and confor-mational flexibility is a shared challenge in comparisons of protein structure. Many tools have been developed to iden-tify remote homologs in cases where backbone flexibilities are considered. However, these methods require compar-isons of structures of more than one proteins, and this is not always available. To assist this process, this paper presents an unsupervised method to predict amino acids that exhibit substantial flexibility to change the binding site when only one protein structure is available. Our method is applied on conformational samples of sequentially nonredundant struc-tures of the serine protease proteins. We observed that influ-ential amino acids can be predicted with high specificities in our whole data set. The results suggest our method as a tool to detect significant side chain motions that affect binding specificity of one protein in the presence of great flexibility. |
| File Format | |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
