Structure Alignment

TL;DR

This paper introduces Structural Bioinformatics, focusing on computational techniques for analyzing, predicting, and comparing protein structures, emphasizing the importance of structural alignment over sequence comparison for discovering protein similarities.

Contribution

It provides an overview of computational methods in Structural Bioinformatics and highlights the significance of structural alignment for protein comparison beyond sequence similarity.

Findings

Structural alignment offers more valuable insights than sequence comparison.

The book emphasizes practical knowledge for applying computational techniques.

Protein structure comparison is crucial for understanding protein function and relationships.

Abstract

While many good textbooks are available on Protein Structure, Molecular Simulations, Thermodynamics and Bioinformatics methods in general, there is no good introductory level book for the field of Structural Bioinformatics. This book aims to give an introduction into Structural Bioinformatics, which is where the previous topics meet to explore three dimensional protein structures through computational analysis. We provide an overview of existing computational techniques, to validate, simulate, predict and analyse protein structures. More importantly, it will aim to provide practical knowledge about how and when to use such techniques. We will consider proteins from three major vantage points: Protein structure quantification, Protein structure prediction, and Protein simulation & dynamics. The Protein DataBank (PDB) contains a wealth of structural information. In order to investigate the similarity between different proteins in this database, one can compare the primary sequence through pairwise alignment and calculate the sequence identity (or similarity) over the two sequences. This strategy will work particularly well if the proteins you want to compare are close homologs. However, in this chapter we will explain that a structural comparison through structural alignment will give you much more valuable information, that allows you to investigate similarities between proteins that cannot be discovered by comparing the sequences alone.