Roll: a new algorithm for the detection of protein pockets and cavities with a rolling probe sphere.
BACKGROUND
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.


RESULTS
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.


BACKGROUND
A web version of POCASA is freely available at http://altair.sci.hokudai.ac.jp/g6/Research/POCASA_e.html.
Yu
Jian
J
Graduate School of Life Science, Hokkaido University, Kita-Ku Kita-10 Nishi-8, Sapporo 0600810, Japan.
Zhou
Yong
Y
Tanaka
Isao
I
Yao
Min
M
D000465:Algorithms; D001665:Binding Sites; D003198:Computer Simulation; D008956:Models, Chemical; D008958:Models, Molecular; D011485:Protein Binding; D025941:Protein Interaction Mapping / Q000379:methods*; D011506:Proteins / Q000737:chemistry* / Q000648:ultrastructure*; D012984:Software
D011506:Proteins