RVP-net：从单序列在线预测蛋白质的实值可及表面积

RVP-net: online prediction of real valued accessible surface area of proteins from single sequences.

作者信息

Ahmad Shandar, Gromiha M Michael, Sarai Akinori

机构信息

Department of Biochemical Engineering and Science, Kyushu Institute of Technology, IZUKA, 820 8502, Fukuoka-ken, Japan and Computational Biology Research Center (CBRC), AIST, 2-41-6, Koto-ku, Tokyo 135 0064, Japan.

出版信息

Bioinformatics. 2003 Sep 22;19(14):1849-51. doi: 10.1093/bioinformatics/btg249.

DOI:10.1093/bioinformatics/btg249

PMID:14512359

Abstract

SUMMARY

RVP-net is an online program for the prediction of real valued solvent accessibility. All previous methods of accessible surface area (ASA) predictions classify amino acid residues into exposure states and named them buried or exposed based on different thresholds. Real values in some cases were generated by taking the mid points of these state thresholds. This is the first method, which provides a direct prediction of ASA without making exposure categories and achieves results better than 19% mean absolute error. To facilitate batch processing of several sequences, a standalone version of this tool is also provided.

AVAILABILITY

Online predictions are available at http://www.netasa.org/rvp-net/. Standalone version of the program can be obtained from the corresponding author by E-mail request.

摘要

RVP-net是一个用于预测实际溶剂可及性的在线程序。之前所有可及表面积（ASA）预测方法都是将氨基酸残基分类为暴露状态，并根据不同阈值将它们命名为埋藏或暴露。在某些情况下，实际值是通过取这些状态阈值的中点生成的。这是第一种无需进行暴露类别划分就能直接预测ASA的方法，其结果的平均绝对误差优于19%。为便于对多个序列进行批量处理，还提供了该工具的独立版本。