LIGSITEcsc: predicting ligand binding sites using the Connolly surface and degree of conservation.

LIGSITEcsc: predicting ligand binding sites using the Connolly surface and degree of conservation.
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DOI:
10.1186/1472-6807-6-19
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发表时间:
2006-09-24
影响因子:
--
通讯作者:
Schroeder M
Schroeder M
中科院分区:
生物4区
文献类型:
--
作者:
Huang B;Schroeder M

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识别蛋白质表面的口袋对于许多基于结构的药物设计应用和蛋白质配体对接算法具有重要意义。在过去的十年里,已经发展了许多几何方法来预测配体结合位置。提出了LIGSITECSC算法,它是LIGSITE算法的扩展和实现。LIGSITEcsc基于表面-溶剂-表面事件的概念和所涉及的表面残基的保守程度。我们将我们的算法与其他四种方法(LIGSITE、CAST、PASS和SURFNET)进行了比较,并在包含48个未绑定/绑定结构和210个绑定结构的数据集上评估了ALL。LIGSITEcsc的性能略好于其他工具,成功率分别为71%和75%。使用Connolly表面导致了轻微的改进,预测根据保守性重新排序,从而显著改进了结合位点的预测。LIGSITEcsc的Web服务器及其源代码可在scope pi.Biotec.tu-resden.de/Pocket上找到。
Identifying pockets on protein surfaces is of great importance for many structure-based drug design applications and protein-ligand docking algorithms. Over the last ten years, many geometric methods for the prediction of ligand-binding sites have been developed. We present LIGSITEcsc, an extension and implementation of the LIGSITE algorithm. LIGSITEcsc is based on the notion of surface-solvent-surface events and the degree of conservation of the involved surface residues. We compare our algorithm to four other approaches, LIGSITE, CAST, PASS, and SURFNET, and evaluate all on a dataset of 48 unbound/bound structures and 210 bound-structures. LIGSITEcsc performs slightly better than the other tools and achieves a success rate of 71% and 75%, respectively. The use of the Connolly surface leads to slight improvements, the prediction re-ranking by conservation to significant improvements of the binding site predictions. A web server for LIGSITEcsc and its source code is available at scoppi.biotec.tu-dresden.de/pocket.
DOI: 10.1107/s0021889883010985
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