{"title":"一种寻找蛋白质配体结合袋的简单方法","authors":"Seyed Majid Saberi Fathi, Jack A Tuszynski","doi":"10.1186/1472-6807-14-18","DOIUrl":null,"url":null,"abstract":"<p>This paper provides a simple and rapid method for a protein-clustering strategy. The basic idea implemented here is to use computational geometry methods to predict and characterize ligand-binding pockets of a given protein structure. In addition to geometrical characteristics of the protein structure, we consider some simple biochemical properties that help recognize the best candidates for pockets in a protein’s active site.</p><p>Our results are shown to produce good agreement with known empirical results.</p><p>The method presented in this paper is a low-cost rapid computational method that could be used to classify proteins and other biomolecules, and furthermore could be useful in reducing the cost and time of drug discovery.</p>","PeriodicalId":51240,"journal":{"name":"BMC Structural Biology","volume":"14 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2014-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/1472-6807-14-18","citationCount":"21","resultStr":"{\"title\":\"A simple method for finding a protein’s ligand-binding pockets\",\"authors\":\"Seyed Majid Saberi Fathi, Jack A Tuszynski\",\"doi\":\"10.1186/1472-6807-14-18\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>This paper provides a simple and rapid method for a protein-clustering strategy. The basic idea implemented here is to use computational geometry methods to predict and characterize ligand-binding pockets of a given protein structure. In addition to geometrical characteristics of the protein structure, we consider some simple biochemical properties that help recognize the best candidates for pockets in a protein’s active site.</p><p>Our results are shown to produce good agreement with known empirical results.</p><p>The method presented in this paper is a low-cost rapid computational method that could be used to classify proteins and other biomolecules, and furthermore could be useful in reducing the cost and time of drug discovery.</p>\",\"PeriodicalId\":51240,\"journal\":{\"name\":\"BMC Structural Biology\",\"volume\":\"14 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-07-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1186/1472-6807-14-18\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BMC Structural Biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1186/1472-6807-14-18\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Biochemistry, Genetics and Molecular Biology\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Structural Biology","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1186/1472-6807-14-18","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Biochemistry, Genetics and Molecular Biology","Score":null,"Total":0}
A simple method for finding a protein’s ligand-binding pockets
This paper provides a simple and rapid method for a protein-clustering strategy. The basic idea implemented here is to use computational geometry methods to predict and characterize ligand-binding pockets of a given protein structure. In addition to geometrical characteristics of the protein structure, we consider some simple biochemical properties that help recognize the best candidates for pockets in a protein’s active site.
Our results are shown to produce good agreement with known empirical results.
The method presented in this paper is a low-cost rapid computational method that could be used to classify proteins and other biomolecules, and furthermore could be useful in reducing the cost and time of drug discovery.
期刊介绍:
BMC Structural Biology is an open access, peer-reviewed journal that considers articles on investigations into the structure of biological macromolecules, including solving structures, structural and functional analyses, and computational modeling.