Trivedi, Rakesh and Nagarajaram, H.A. (2020) Substitution Scoring Matrices for Proteins ‐ An Overview. Protein Science, 29 (11). pp. 2150-2163. ISSN 0961-8368

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Abstract

Sequence analysis is the primary and simplest approach to discover structural, functional and evolutionary details of related proteins. All the alignment based approaches of sequence analysis make use of amino acid substitution matrices, and the accuracy of the results largely depends on the type of scoring matrices used to perform alignment tasks. An amino acid substitution matrix is a 20x20 matrix in which the individual elements encapsulate the rates at which each of the 20 amino acid residues in proteins are substituted by other amino acid residues over time. In contrast to most globular/ordered proteins whose amino acids composition is considered as standard, there are several classes of proteins (e.g., transmembrane proteins) in which certain types of amino acid (e.g., hydrophobic residues) are enriched. These compositional differences among various classes of proteins are manifested in their underlying residue substitution frequencies. Therefore, each of the compositionally distinct class of proteins or protein segments should be studied using specific scoring matrices that reflect their distinct residue substitution pattern. In this review, we describe the development and application of various substitution scoring matrices peculiar to proteins with standard and biased compositions. Along with most commonly used standard matrices (PAM, BLOSUM, MD and VTML) that act as default parameters in various homologs search and alignment tools, different substitution scoring matrices specific to compositionally distinct class of proteins are discussed in detail. This article is protected by copyright. All rights reserved.

Item Type:	Article
Subjects:	Computational Biology
Depositing User:	Users 2 not found.
Date Deposited:	24 Sep 2020 19:42
Last Modified:	12 Nov 2020 18:53
URI:	http://cdfd.sciencecentral.in/id/eprint/972

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