Graph‐based methods for protein structure comparison

Abstract

While sequence‐based methods are widely used as reliable tools for protein function prediction in general, these methods are likely to fail in cases of low sequence similarity. This is due to the fact that proteins with low sequence similarity may nevertheless have similar functions and exhibit similar structures. In such cases, structure‐based comparison methods can help to provide further insights owing to the widely accepted paradigm that structure mirrors function. Moreover, thanks to the steady increase in structural information with the advent of structural genomic projects and the steady improvements in structure prediction, these methods are becoming more and more applicable. Many structure‐based approaches to the comparative analysis of proteins and the inference of protein function rely on graph formalisms for modeling protein structures and, correspondingly, employ graph‐theoretic algorithms for analyzing and comparing such structures. This review is devoted to approaches of that kind and presents an overview of the most important graph‐based algorithms.This article is categorized under: Algorithmic Development > Biological Data Mining Algorithmic Development > Structure Discovery