Identify High-Quality Protein Structural Models by Enhanced K-Means.

ABSTRACT: Background. One critical issue in protein three-dimensional structure prediction using either ab initio or comparative modeling involves identification of high-quality protein structural models from generated decoys. Currently, clustering algorithms are widely used to identify near-native models; however, their performance is dependent upon different conformational decoys, and, for some algorithms, the accuracy declines when the decoy population increases. Results. Here, we proposed two enhanced K-means clustering algorithms capable of robustly identifying high-quality protein structural models. The first one employs the clustering algorithm SPICKER to determine the initial centroids for basic K-means clustering (SK-means), whereas the other employs squar

SUBMITTER: Wu H 

PROVIDER: S-EPMC5381204 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature