Protein Structure and Function. Application of Bioinformatics Methods - John Rigden 2014

Prediction of membrane protein structure
Introduction

Timothy Nugent, David T. Jones

Transmembrane (TM) Proteins perform a multitude of critical functions within The Cell and make up a significant portion of the proteome. Estimates suggest that up to 30% of all human genes may encode $\alpha$-helical TM proteins. However, high-resolution structures are known for only a small fraction of TM proteins. Consequently, There is a growing emphasis on Research Methods that extract maximum structural information from available Amino acid sequences. This chapter focuses on modern sequence- and Structure-based methods for predicting the topology and structure of Membrane Proteins. Special attention is given to the pitfalls in this field, as well as to challenges that remain to be solved.

Transmembrane (TM) proteins are involved in many vital biological processes, such as cellular signaling, the Transport of Molecules that cannot independently cross membranes, intercellular interactions, Cell Recognition, and Cell Adhesion. Furthermore, many transmembrane proteins serve as important drug targets. Estimates indicate that over half of all pharmaceutical drugs currently on the market target transmembrane proteins (Klabunde and Hesler 2002). However, because obtaining high-quality crystal structures involves significant technical hurdles, this Class of proteins is severely underrepresented in structural Databases, accounting for only 1% of known structures in the PDB (White 2004). Transmembrane proteins are of profound biological and pharmacological significance. Elucidating their structure and topology—including the total number of TM helices, their boundaries, and their orientation relative to the membrane—is essential for analyzing protein function and guiding future experimental work. In the absence of structural data, modern bioinformatics strategies rely primarily on sequence-based prediction methods.

Timothy Nugent and David T Jones**

Bioinformatics Group, Department of Computer Science,

University College, London, WC1E 6BT, UK

*e-mail:d.jones@cs.ucl.ac.uk