An efficient algorithm for protein structure comparison using elastic shape analysis. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Srivastava, S.; Lal, S.; Mishra, D.; Angadi, U.; Chaturvedi, K.; Rai, S.; Rai, A.
• Is Part Of: Algorithms for molecular biology. Volume 11:Issue 1(2016)
• Page Start: 1
• Page End: 11
• Publication Date: 2016-12
• Subjects: Protein structure comparison -- Backbone atoms -- Geodesic distance -- Side chain properties; Molecular biology -- Mathematical models -- Periodicals; Algorithms -- Periodicals; Bioinformatics -- Periodicals; 572.8015118
• DOI: 10.1186/s13015-016-0089-1
• Languages: English
• ISSNs: 1748-7188

Abstract

Abstract Background Protein structure comparison play important role in in silico functional prediction of a new protein. It is also used for understanding the evolutionary relationships among proteins. A variety of methods have been proposed in literature for comparing protein structures but they have their own limitations in terms of accuracy and complexity with respect to computational time and space. There is a need to improve the computational complexity in comparison/alignment of proteins through incorporation of important biological and structural properties in the existing techniques. Results An efficient algorithm has been developed for comparing protein structures using elastic shape analysis in which the sequence of 3D coordinates atoms of protein structures supplemented by additional auxiliary information from side-chain properties are incorporated. The protein structure is represented by a special function called square-root velocity function. Furthermore, singular value decomposition and dynamic programming have been employed for optimal rotation and optimal matching of the proteins, respectively. Also, geodesic distance has been calculated and used as the dissimilarity score between two protein structures. The performance of the developed algorithm is tested and found to be more efficient, i.e., running time reduced by 80–90 % without compromising accuracy of comparison when compared with the existing methods. Source codes for different functions have been developed in R. Also, user friendly web-based application called ProtSComp has been developed using above algorithm for comparing protein 3D structures and is accessible free. Conclusions The methodology and algorithm developed in this study is taking considerably less computational time without loss of accuracy (Table 2). The proposed algorithm is considering different criteria of representing protein structures using 3D coordinates of atoms and inclusion of residue wise molecular properties as auxiliary information.