Staff Profile:Dr Liam McGuffin

Name:

Dr Liam McGuffin

Job Title:

Academic, Harborne Bldg

Responsibilities:

Lecturer in Bioinformatics

Areas of Interest:

Research Interests:

One of the key areas of study in biomedical sciences is how proteins function within cells and how that function translates to health. To deliver on the promise of genome projects for health care, we must understand the information implicit in the genome, specifically, the functions of the proteins encoded by the genes.  Individual protein chains fold into specific three dimensional structures and bind with one another to form complexes that perform essential functions. The fold of a protein is therefore key to the cell functioning correctly and protein misfolding is a direct cause of disease - Alzheimer's, Parkinson's and Mad Cow disease being well known if extreme examples.

Protein structure prediction methods allow us to rapidly model the shapes of proteins in order to determine their likely functions. Predicting how proteins fold is not easy. In cases where the structure of a protein has been determined experimentally the fold can be directly visualised. However, solving structures experimentally is currently time consuming and expensive and so the vast majority of proteins with known sequences have unknown structures. My main interest is in the development of computational methods for rapidly and confidently predicting the structures for the majority of proteins from their primary sequences. When a catalogue of accurately predicted structures for the majority of proteins within a cell is available, the eventual aim is to predict their function and their ability to interact with others to form the protein complexes upon which life depends. This vital information should allow us to produce novel or more efficient products for use in medicine.

My innovative methods for predicting protein structures rank among the top few internationally. Notably, the DISOclust server for the prediction of intrinsic protein disorder and the ModFOLD model quality assessment server have recently been particularly successful - further details can be seen at http://www.reading.ac.uk/bioinf.

Research groups / Centres:

Cardiovascular biology

Development and endocrinology research group

Institute for Cardiovascular & Metabolic Research

Publications:

Y

Jump to: 2012 | 2011 | 2010 | 2009 | 2008 | 2007 | 2006

Number of items: 16.

2012

• Fuller, S., McGuffin, L., Marshall, A., Giraldo, A., Pikkarainen, S., Clerk, A. and Sugden, P. (2012) A novel, non-canonical mechanism of regulation of mammalian Ste20-related kinase 3 (MST3). Biochemical Journal. ISSN 0264-6021 (In Press)

2011

• Bindschedler, L. V., McGuffin, L. J., Burgis, T. A., Spanu, P. D. and Cramer, R. (2011) Proteogenomics and in silico structural and functional annotation of the barley powdery mildew Blumeria graminis f. sp. hordei. Methods, 54 (4). pp. 432-441. ISSN 1046-2023
• McGuffin, L. J. and Roche, D. B. (2011) Automated tertiary structure prediction with accurate local model quality assessment using the IntFOLD-TS method. Proteins: Structure, Function, and Bioinformatics. ISSN 1097-0134 (In Press)
• Roche, D. B., Buenavista, M. T., Tetchner, S. J. and McGuffin, L. J. (2011) The IntFOLD server: an integrated web resource for protein fold recognition, 3D model quality assessment, intrinsic disorder prediction, domain prediction and ligand binding site prediction. Nucleic Acids Research, 39 (Web Server issue). W171-W176. ISSN 1362-4962
• Roche, D. B., Tetchner, S. J. and McGuffin, L. J. (2011) FunFOLD: an improved automated method for the prediction of ligand binding residues using 3D models of proteins. BMC Bioinformatics, 12 (1). p. 160. ISSN 1471-2105

2010

• McGuffin, L. J. (2010) Model quality prediction. In: Rangwala, H. and Karypis, G. (eds.) Introduction to protein structure prediction: methods and algorithms. Wiley, pp. 323-342. ISBN 9780470470596
• Roche, D. B., Tetchner, S. J. and McGuffin, L. J. (2010) The binding site distance test score: a robust method for the assessment of predicted protein binding sites. Bioinformatics, 26 (22). pp. 2920-2921. ISSN 1460-2059
• McGuffin, L. J. and Roche, D. B. (2010) Rapid model quality assessment for protein structure predictions using the comparison of multiple models without structural alignments. Bioinformatics, 26 (2). pp. 182-188. ISSN 1460-2059

2009

• McGuffin, L. J. (2009) Insertions and deletions, their molecular mechanisms and their impact on sequence alignments. In: Rosenberg, M. S. (ed.) Sequence Alignment: Methods, Models, Concepts, and Strategies. University of California Press, pp. 23-38. ISBN 9780520256972
• McGuffin, L. J. (2009) Prediction of global and local model quality in CASP8 using the ModFOLD server. Proteins-Structure Function and Bioinformatics, 77. pp. 185-190. ISSN 0887-3585

2008

• McGuffin, L. J. (2008) Aligning sequences to structures. Methods in Molecular Biology, 413. pp. 61-90. ISSN 1064-3745
• McGuffin, L. J. (2008) Intrinsic disorder prediction from the analysis of multiple protein fold recognition models. Bioinformatics, 24 (16). pp. 1798-1804. ISSN 1367-4803
• McGuffin, L. J. (2008) The ModFOLD server for the quality assessment of protein structural models. Bioinformatics, 24 (4). pp. 586-587. ISSN 1367-4803
• McGuffin, L.J. (2008) Protein fold recognition and threading. In: Computational Structural Biology. World Scientific Publishing Ltd, pp. 37-60. ISBN 9789812778772

2007

• McGuffin, L. J. (2007) Benchmarking consensus model quality assessment for protein fold recognition. Bmc Bioinformatics, 8. p. 15. ISSN 1471-2105

2006

• McGuffin, L. J., Smith, R. T., Bryson, K., Sorensen, S. A. and Jones, D. T. (2006) High throughput profile-profile based fold recognition for the entire human proteome. BMC Bioinformatics, 7. p. 288. ISSN 1471-2105

This list was generated on Thu Feb 9 08:30:57 2012 GMT.