Calibur: a tool for clustering large numbers of protein decoys

Background: Ab initio protein structure prediction methods generate numerous structural candidates, which are referred to as decoys. The decoy with the most number of neighbors of up to a threshold distance is typically identified as the most representative decoy. However, the clustering of decoys needed for this criterion involves computations with runtimes that are at best quadratic in the number of decoys. As a result currently there is no tool that is designed to exactly cluster very large numbers of decoys, thus creating a bottleneck in the analysis. Results: Using three strategies aimed at enhancing performance (proximate decoys organization, preliminary screening via lower and upper bounds, outliers filtering) we designed and implemented a software tool for clustering decoys called Calibur. We show empirical results indicating the effectiveness of each of the strategies employed. The strategies are further fine-tuned according to their effectiveness. Calibur demonstrated the ab...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Shuai Cheng Li, Yen Kaow Ng
• Keywords: BMCBI 2010, Decoys, Initio Protein Structure, Protein Structure Prediction