Suppr超能文献

DEPTH:一个用于计算蛋白质深度并预测小分子结合腔的网络服务器。

DEPTH: a web server to compute depth and predict small-molecule binding cavities in proteins.

机构信息

Bioinformatics Institute, 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore.

出版信息

Nucleic Acids Res. 2011 Jul;39(Web Server issue):W242-8. doi: 10.1093/nar/gkr356. Epub 2011 May 16.

Abstract

Depth measures the extent of atom/residue burial within a protein. It correlates with properties such as protein stability, hydrogen exchange rate, protein-protein interaction hot spots, post-translational modification sites and sequence variability. Our server, DEPTH, accurately computes depth and solvent-accessible surface area (SASA) values. We show that depth can be used to predict small molecule ligand binding cavities in proteins. Often, some of the residues lining a ligand binding cavity are both deep and solvent exposed. Using the depth-SASA pair values for a residue, its likelihood to form part of a small molecule binding cavity is estimated. The parameters of the method were calibrated over a training set of 900 high-resolution X-ray crystal structures of single-domain proteins bound to small molecules (molecular weight <1.5  KDa). The prediction accuracy of DEPTH is comparable to that of other geometry-based prediction methods including LIGSITE, SURFNET and Pocket-Finder (all with Matthew's correlation coefficient of ∼0.4) over a testing set of 225 single and multi-chain protein structures. Users have the option of tuning several parameters to detect cavities of different sizes, for example, geometrically flat binding sites. The input to the server is a protein 3D structure in PDB format. The users have the option of tuning the values of four parameters associated with the computation of residue depth and the prediction of binding cavities. The computed depths, SASA and binding cavity predictions are displayed in 2D plots and mapped onto 3D representations of the protein structure using Jmol. Links are provided to download the outputs. Our server is useful for all structural analysis based on residue depth and SASA, such as guiding site-directed mutagenesis experiments and small molecule docking exercises, in the context of protein functional annotation and drug discovery.

摘要

深度衡量了原子/残基在蛋白质中的埋藏程度。它与蛋白质稳定性、氢交换率、蛋白质-蛋白质相互作用热点、翻译后修饰位点和序列可变性等性质相关。我们的服务器 DEPTH 可以准确地计算深度和溶剂可及表面积 (SASA) 值。我们表明,深度可用于预测蛋白质中的小分子配体结合腔。通常,一些排列在配体结合腔周围的残基既深又暴露于溶剂中。使用残基的深度-SASA 对值,可以估计其形成小分子结合腔的可能性。该方法的参数是通过对 900 个结合小分子(分子量<1.5 kDa)的单域蛋白质的高分辨率 X 射线晶体结构的训练集进行校准的。在 225 个单链和多链蛋白质结构的测试集中,DEPTH 的预测准确性与其他基于几何形状的预测方法(包括 LIGSITE、SURFNET 和 Pocket-Finder)相当(所有方法的马修相关系数都约为 0.4)。用户可以选择调整几个参数以检测不同大小的腔,例如,几何上平坦的结合位点。服务器的输入是 PDB 格式的蛋白质 3D 结构。用户可以选择调整与残基深度计算和结合腔预测相关的四个参数的值。计算出的深度、SASA 和结合腔预测以 2D 图显示,并使用 Jmol 映射到蛋白质结构的 3D 表示上。提供了下载输出的链接。我们的服务器对于所有基于残基深度和 SASA 的结构分析都很有用,例如指导定点突变实验和小分子对接练习,这在蛋白质功能注释和药物发现方面非常有用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c39/3125764/c1d0ff85fbf5/gkr356f1a.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验