Towards genome-scale structure prediction for transmembrane proteins

Author:

Hurwitz Naama1,Pellegrini-Calace Marialuisa2,Jones David T1

Affiliation:

1. Bioinformatics Unit, Department of Computer Science & Department of Biochemistry and Molecular BiologyDarwin Building, University College London, Gower Street, London WC1E 6BT, UK

2. Department of Biochemical Sciences, University of Rome ‘La Sapienza’P.le Aldo Moro, 5, 00185 Rome, Italy

Abstract

In this paper we briefly review some of the recent progress made by ourselves and others in developing methods for predicting the structures of transmembrane proteins from amino acid sequence. Transmembrane proteins are an important class of proteins involved in many diverse biological functions, many of which have great impact in terms of disease mechanism and drug discovery. Despite their biological importance, it has proven very difficult to solve the structures of these proteins by experimental techniques, and so there is a great deal of pressure to develop effective methods for predicting their structure. The methods we discuss range from methods for transmembrane topology prediction to new methods for low resolution folding simulations in a knowledge-based force field. This potential is designed to reproduce the properties of the lipid bilayer. Our eventual aim is to apply these methods in tandem so that useful three-dimensional models can be built for a large fraction of the transmembrane protein domains in whole proteomes.

Publisher

The Royal Society

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology

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1. Background on Biology of Ageing and Bioinformatics;Advanced Information and Knowledge Processing;2018-11-30

2. Modeling of Membrane Proteins;Springer Series on Bio- and Neurosystems;2018-11-29

3. Membrane Proteins;Textbook of Membrane Biology;2017

4. Advances in Computational Methods for Transmembrane Protein Structure Prediction;From Protein Structure to Function with Bioinformatics;2017

5. De Novo Membrane Protein Structure Prediction;Methods in Molecular Biology;2014-09-03

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