Data Resources for Structural Bioinformatics

TL;DR

This paper introduces foundational computational techniques and key data resources in Structural Bioinformatics, emphasizing practical applications in protein structure analysis, prediction, and simulation for newcomers to the field.

Contribution

It provides an introductory overview of computational methods and key data resources specifically tailored for structural bioinformatics, filling a gap in educational materials.

Findings

Overview of computational techniques for protein analysis

Introduction to key data resources and tools

Guidance on practical application of methods

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. Structural bioinformatics involves a variety of computational methods, all of which require input data. Typical inputs include protein structures and sequences, which are usually retrieved from a public or private database. This chapter introduces several key resources that make such data available, as well as a handful of tools that derive additional information from experimentally determined or computationally predicted protein structures and sequences.