Zhiyu Zhao, Bin Fu, Francisco J Alanis, Christopher M Summa
{"title":"Feedback algorithm and web-server for protein structure alignment.","authors":"Zhiyu Zhao, Bin Fu, Francisco J Alanis, Christopher M Summa","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>We have developed a feedback algorithm for protein structure alignment between two protein backbones. A web portal implementing this method has been constructed and is freely available for use at http://fpsa.cs.uno.edu/ with a mirror site at http://fpsa.cs.panam.edu/FPSA/. We compare our algorithm with three other, commonly used methods: CE, DaliLite and SSM. The results show that in most cases our algorithm outputs a larger number of aligned positions when the (Calpha) RMSD is comparable. Also, in many cases where the number of aligned positions is larger or comparable, our learning method is able to achieve a smaller (Calpha) RMSD than the other methods tested. This trend of larger number of aligned positions and smaller (Calpha) RMSD is observed more frequently in cases where the similarity between protein structures is weak.</p>","PeriodicalId":72665,"journal":{"name":"Computational systems bioinformatics. Computational Systems Bioinformatics Conference","volume":"7 ","pages":"109-20"},"PeriodicalIF":0.0000,"publicationDate":"2008-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational systems bioinformatics. Computational Systems Bioinformatics Conference","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We have developed a feedback algorithm for protein structure alignment between two protein backbones. A web portal implementing this method has been constructed and is freely available for use at http://fpsa.cs.uno.edu/ with a mirror site at http://fpsa.cs.panam.edu/FPSA/. We compare our algorithm with three other, commonly used methods: CE, DaliLite and SSM. The results show that in most cases our algorithm outputs a larger number of aligned positions when the (Calpha) RMSD is comparable. Also, in many cases where the number of aligned positions is larger or comparable, our learning method is able to achieve a smaller (Calpha) RMSD than the other methods tested. This trend of larger number of aligned positions and smaller (Calpha) RMSD is observed more frequently in cases where the similarity between protein structures is weak.