{"title":"Correlating Combined Features of Amino Acid and Protein with Crystallization Propensity of Proteins from Mycobacterium tuberculosis","authors":"Shaomin Yan, Guang Wu","doi":"10.4236/jbise.2019.129034","DOIUrl":null,"url":null,"abstract":"Since a decade ago, both protein and amino acid features have been correlated with crystallization propensity of proteins in order to develop methods to predict whether a protein can be crystallized. In this continuing study, each of three features combining features of amino acid and protein, was correlated with the crystallization propensity of proteins from Mycobacterium tuberculosis using logistic and neural network models. The results showed that two combined features, amino acid distribution probability and future composition, had good predictions on whether a protein would be crystallized in comparison with the predictions obtained from each of 531 amino acid features. The results obtained from the third combined feature, amino acid pair predictability, demonstrated the trend of crystallization propensity in proteins from Mycobacterium tuberculosis.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"生物医学工程(英文)","FirstCategoryId":"1087","ListUrlMain":"https://doi.org/10.4236/jbise.2019.129034","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Since a decade ago, both protein and amino acid features have been correlated with crystallization propensity of proteins in order to develop methods to predict whether a protein can be crystallized. In this continuing study, each of three features combining features of amino acid and protein, was correlated with the crystallization propensity of proteins from Mycobacterium tuberculosis using logistic and neural network models. The results showed that two combined features, amino acid distribution probability and future composition, had good predictions on whether a protein would be crystallized in comparison with the predictions obtained from each of 531 amino acid features. The results obtained from the third combined feature, amino acid pair predictability, demonstrated the trend of crystallization propensity in proteins from Mycobacterium tuberculosis.