Nicole C. Arrigo, P. Paci, L. Paola, D. Santoni, M. Ruvo, A. Giuliani, F. Castiglione
{"title":"Characterizing Protein Shape by a Volume Distribution Asymmetry Index","authors":"Nicole C. Arrigo, P. Paci, L. Paola, D. Santoni, M. Ruvo, A. Giuliani, F. Castiglione","doi":"10.2174/1875036201206010020","DOIUrl":null,"url":null,"abstract":"A fully quantitative shape index relying upon the asymmetry of mass distribution of protein molecules along the three space dimensions is proposed. Multidimensional statistical analysis, based on principal component extraction and subsequent linear discriminant analysis, showed the presence of three major 'attractor forms' roughly correspondent to rod-like, discoidal and spherical shapes. This classification of protein shapes was in turn demonstrated to be strictly connected with topological features of proteins, as emerging from complex network invariants of their contact maps.","PeriodicalId":38956,"journal":{"name":"Open Bioinformatics Journal","volume":"6 1","pages":"20-27"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Open Bioinformatics Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/1875036201206010020","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 3
Abstract
A fully quantitative shape index relying upon the asymmetry of mass distribution of protein molecules along the three space dimensions is proposed. Multidimensional statistical analysis, based on principal component extraction and subsequent linear discriminant analysis, showed the presence of three major 'attractor forms' roughly correspondent to rod-like, discoidal and spherical shapes. This classification of protein shapes was in turn demonstrated to be strictly connected with topological features of proteins, as emerging from complex network invariants of their contact maps.
期刊介绍：
The Open Bioinformatics Journal is an Open Access online journal, which publishes research articles, reviews/mini-reviews, letters, clinical trial studies and guest edited single topic issues in all areas of bioinformatics and computational biology. The coverage includes biomedicine, focusing on large data acquisition, analysis and curation, computational and statistical methods for the modeling and analysis of biological data, and descriptions of new algorithms and databases. The Open Bioinformatics Journal, a peer reviewed journal, is an important and reliable source of current information on the developments in the field. The emphasis will be on publishing quality articles rapidly and freely available worldwide.
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