Abstract
BackgroundIdentifying the location of binding sites on proteins is of fundamental importance for a wide range of applications including molecular docking, de novo drug design, structure identification and comparison of functional sites. Structural genomic projects are beginning to produce protein structures with unknown functions. Therefore, efficient methods are required if all these structures are to be properly annotated. Lots of methods for finding binding sites involve 3D structure comparison. Here we design a method to find protein binding sites by direct comparison of protein 3D structures.ResultsWe have developed an efficient heuristic approach for finding similar binding sites from the surface of given proteins. Our approach consists of three steps: local sequence alignment, protein surface detection, and 3D structures comparison. We implement the algorithm and produce a software package that works well in practice. When comparing a complete protein with all complete protein structures in the PDB database, experiments show that the average recall value of our approach is 82% and the average precision value of our approach is also significantly better than the existing approaches.ConclusionsOur program has much higher recall values than those existing programs. Experiments show that all the existing approaches have recall values less than 50%. This implies that more than 50% of real binding sites cannot be reported by those existing approaches. The software package is available at http://sites.google.com/site/guofeics/bsfinder.
Highlights
Identifying the location of binding sites on proteins is of fundamental importance for a wide range of applications including molecular docking, de novo drug design, structure identification and comparison of functional sites
Efficient methods are required if all these structures are to be properly annotated
When comparing a complete protein with all complete protein structures in the PDB database, experiments show that all the existing approaches have recall values less than 50% implying that more than 50% of real binding sites cannot be reported by those existing approaches
Summary
Identifying the location of binding sites on proteins is of fundamental importance for a wide range of applications including molecular docking, de novo drug design, structure identification and comparison of functional sites. Lots of methods for finding binding sites involve 3D structure comparison. We design a method to find protein binding sites by direct comparison of protein 3D structures. Many methods have been proposed for identifying the location of binding sites on proteins. Laurie and Jackson give an energy-based method for the prediction of protein-ligand binding sites [1]. Guo and Wang identify the binding sites by finding two similar 3D substructures [7]
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