Roll: a new algorithm for the detection of protein pockets and cavities with a rolling probe sphere.
basic_science · Level V
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- Record sourced from PubMed, PMID 19846440.
- Also identified by DOI 10.1093/bioinformatics/btp599.
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Abstract
Prediction of ligand binding sites of proteins is significant as it can provide insight into biological functions and reaction mechanisms of proteins. It is also a prerequisite for protein-ligand docking and an important step in structure-based drug design. We present a new algorithm, Roll, implemented in a program named POCASA, which can predict binding sites by detecting pockets and cavities of proteins with a rolling sphere. To evaluate the performance of POCASA, a test with the same data set as used in several existing methods was carried out. POCASA achieved a high success rate of 77%. In addition, the test results indicated that POCASA can predict good shapes of ligand binding sites. A web version of POCASA is freely available at http://altair.sci.hokudai.ac.jp/g6/Research/POCASA_e.html.
Medical subject headings
- Algorithms
- Models, Chemical
- Models, Molecular
- Protein Interaction Mapping
- Proteins
- Software