基于相互作用能和序列守恒的蛋白质-配体结合位点预测方法的建立。

Hiroto Tsujikawa, Kenta Sato, Cao Wei, Gul Saad, Kazuya Sumikoshi, Shugo Nakamura, Tohru Terada, Kentaro Shimizu
{"title":"基于相互作用能和序列守恒的蛋白质-配体结合位点预测方法的建立。","authors":"Hiroto Tsujikawa,&nbsp;Kenta Sato,&nbsp;Cao Wei,&nbsp;Gul Saad,&nbsp;Kazuya Sumikoshi,&nbsp;Shugo Nakamura,&nbsp;Tohru Terada,&nbsp;Kentaro Shimizu","doi":"10.1007/s10969-016-9204-2","DOIUrl":null,"url":null,"abstract":"<p><p>We present a new method for predicting protein-ligand-binding sites based on protein three-dimensional structure and amino acid conservation. This method involves calculation of the van der Waals interaction energy between a protein and many probes placed on the protein surface and subsequent clustering of the probes with low interaction energies to identify the most energetically favorable locus. In addition, it uses amino acid conservation among homologous proteins. Ligand-binding sites were predicted by combining the interaction energy and the amino acid conservation score. The performance of our prediction method was evaluated using a non-redundant dataset of 348 ligand-bound and ligand-unbound protein structure pairs, constructed by filtering entries in a ligand-binding site structure database, LigASite. Ligand-bound structure prediction (bound prediction) indicated that 74.0 % of predicted ligand-binding sites overlapped with real ligand-binding sites by over 25 % of their volume. Ligand-unbound structure prediction (unbound prediction) indicated that 73.9 % of predicted ligand-binding residues overlapped with real ligand-binding residues. The amino acid conservation score improved the average prediction accuracy by 17.0 and 17.6 points for the bound and unbound predictions, respectively. These results demonstrate the effectiveness of the combined use of the interaction energy and amino acid conservation in the ligand-binding site prediction. </p>","PeriodicalId":73957,"journal":{"name":"Journal of structural and functional genomics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s10969-016-9204-2","citationCount":"10","resultStr":"{\"title\":\"Development of a protein-ligand-binding site prediction method based on interaction energy and sequence conservation.\",\"authors\":\"Hiroto Tsujikawa,&nbsp;Kenta Sato,&nbsp;Cao Wei,&nbsp;Gul Saad,&nbsp;Kazuya Sumikoshi,&nbsp;Shugo Nakamura,&nbsp;Tohru Terada,&nbsp;Kentaro Shimizu\",\"doi\":\"10.1007/s10969-016-9204-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>We present a new method for predicting protein-ligand-binding sites based on protein three-dimensional structure and amino acid conservation. This method involves calculation of the van der Waals interaction energy between a protein and many probes placed on the protein surface and subsequent clustering of the probes with low interaction energies to identify the most energetically favorable locus. In addition, it uses amino acid conservation among homologous proteins. Ligand-binding sites were predicted by combining the interaction energy and the amino acid conservation score. The performance of our prediction method was evaluated using a non-redundant dataset of 348 ligand-bound and ligand-unbound protein structure pairs, constructed by filtering entries in a ligand-binding site structure database, LigASite. Ligand-bound structure prediction (bound prediction) indicated that 74.0 % of predicted ligand-binding sites overlapped with real ligand-binding sites by over 25 % of their volume. Ligand-unbound structure prediction (unbound prediction) indicated that 73.9 % of predicted ligand-binding residues overlapped with real ligand-binding residues. The amino acid conservation score improved the average prediction accuracy by 17.0 and 17.6 points for the bound and unbound predictions, respectively. These results demonstrate the effectiveness of the combined use of the interaction energy and amino acid conservation in the ligand-binding site prediction. </p>\",\"PeriodicalId\":73957,\"journal\":{\"name\":\"Journal of structural and functional genomics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1007/s10969-016-9204-2\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of structural and functional genomics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s10969-016-9204-2\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2016/7/11 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of structural and functional genomics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s10969-016-9204-2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2016/7/11 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

摘要

我们提出了一种基于蛋白质三维结构和氨基酸守恒预测蛋白质配体结合位点的新方法。该方法包括计算蛋白质与放置在蛋白质表面的许多探针之间的范德华相互作用能,然后将具有低相互作用能的探针聚类以确定能量最有利的位点。此外,它利用同源蛋白之间的氨基酸守恒。结合相互作用能和氨基酸守恒分数预测配体结合位点。通过筛选配体结合位点结构数据库LigASite中的条目,构建了348对配体结合和非配体结合的蛋白质结构对的非冗余数据集,对我们的预测方法的性能进行了评估。配体结合结构预测(binding prediction)表明,74.0%的预测配体结合位点与实际配体结合位点的重叠量超过其体积的25%。配体非结合结构预测(unbinding prediction)表明,73.9%的预测配体结合残基与实际配体结合残基重叠。氨基酸保守评分将结合和未结合预测的平均预测精度分别提高了17.0和17.6分。这些结果证明了相互作用能与氨基酸守恒相结合在配体结合位点预测中的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Development of a protein-ligand-binding site prediction method based on interaction energy and sequence conservation.

Development of a protein-ligand-binding site prediction method based on interaction energy and sequence conservation.

Development of a protein-ligand-binding site prediction method based on interaction energy and sequence conservation.

Development of a protein-ligand-binding site prediction method based on interaction energy and sequence conservation.

We present a new method for predicting protein-ligand-binding sites based on protein three-dimensional structure and amino acid conservation. This method involves calculation of the van der Waals interaction energy between a protein and many probes placed on the protein surface and subsequent clustering of the probes with low interaction energies to identify the most energetically favorable locus. In addition, it uses amino acid conservation among homologous proteins. Ligand-binding sites were predicted by combining the interaction energy and the amino acid conservation score. The performance of our prediction method was evaluated using a non-redundant dataset of 348 ligand-bound and ligand-unbound protein structure pairs, constructed by filtering entries in a ligand-binding site structure database, LigASite. Ligand-bound structure prediction (bound prediction) indicated that 74.0 % of predicted ligand-binding sites overlapped with real ligand-binding sites by over 25 % of their volume. Ligand-unbound structure prediction (unbound prediction) indicated that 73.9 % of predicted ligand-binding residues overlapped with real ligand-binding residues. The amino acid conservation score improved the average prediction accuracy by 17.0 and 17.6 points for the bound and unbound predictions, respectively. These results demonstrate the effectiveness of the combined use of the interaction energy and amino acid conservation in the ligand-binding site prediction.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信