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ProtPCV: A Fixed Dimensional Numerical Representation of Protein Sequence to Significantly Reduce Sequence Search Time

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Abstract

Protein sequence is a wealth of experimental information which is yet to be exploited to extract information on protein homologues. Consequently, it is observed from publications that dynamic programming, heuristics and HMM profile-based alignment techniques along with the alignment free techniques do not directly utilize ordered profile of physicochemical properties of a protein to identify its homologue. Also, it is found that these works lack crucial bench-marking or validation in absence of which their incorporation in search engines may appears to be questionable. In this direction this research approach offers fixed dimensional numerical representation of protein sequences extending the concept of periodicity count value of nucleotide types (2017) to accommodate Euclidean distance as direct similarity measure between two proteins. Instead of bench-marking with BLAST and PSI-BLAST only, this new similarity measure was also compared with Needleman–Wunsch and Smith–Waterman. For enhancing the strength of comparison, this work for the first time introduces two novel benchmarking methods based on correlation of “similarity scores” and “proximity of ranked outputs from a standard sequence alignment method” between all possible pairs of search techniques including the new one presented in this paper. It is found that the novel and unique numerical representation of a protein can reduce computational complexity of protein sequence search to the tune of O(log(n)). It may also help implementation of various other similarity-based operation possible, such as clustering, phylogenetic analysis and classification of proteins on the basis of the properties used to build this numerical representation of protein.

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Acknowledgements

The authors gratefully acknowledge the logistic support of Biomedical Informatics Lab-Department of Applied Science, Computer Centre II, Indian Institute of Information Technology Allahabad(IIITA), India for providing financial support to procure computer systems and coding software, Perl (V5.26.1) and MATLAB (R2019b) used in this work. Manoj Kumar Pal and Rajnish Kumar are also thankful to Ministry of Human Resource Development (MHRD), Government of India for providing regular monthly Research Scholarship.

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  1. Department of Applied Sciences, Indian Institute of Information Technology, Allahabad, UP, 211015, India

    Manoj Kumar Pal, Tapobrata Lahiri & Rajnish Kumar

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  1. Manoj Kumar Pal
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  2. Tapobrata Lahiri
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Correspondence to Tapobrata Lahiri.

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Pal, M.K., Lahiri, T. & Kumar, R. ProtPCV: A Fixed Dimensional Numerical Representation of Protein Sequence to Significantly Reduce Sequence Search Time. Interdiscip Sci Comput Life Sci 12, 276–287 (2020). https://doi.org/10.1007/s12539-020-00380-w

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  • DOI: https://doi.org/10.1007/s12539-020-00380-w

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