Abstract

BackgroundProtein 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.ResultsAn 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.ConclusionsThe 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.

Highlights

  • Protein structure comparison play important role in in silico functional prediction of a new protein

  • In earlier study for comparing two protein structures based on elastic shape analysis (ESA) using only backbone atoms resulted with classification accuracy of 80.73 and 92.10 % for the first and second dataset of proteins respectively [23]

  • The proposed algorithm is based on ESA using either centroid of backbone atoms (ESA-MC-BB) or Cα (ESA-CA) along with dihedral angles as geometric property of molecular structure

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Summary

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 squareroot velocity function. Singular value decomposition and dynamic programming have been employed for optimal rotation and optimal matching of the proteins, respectively. 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. User friendly web-based application called ProtSComp has been developed using above algorithm for comparing protein 3D structures and is accessible free

Conclusions
Background
Results and discussion
Method
41. R Core Team
Full Text
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