Staff Profile:Dr Liam McGuffin
- Name:
- Dr Liam McGuffin
- Job Title:
- RCUK Fellow, Harborne Building
- Responsibilities:
- Areas of Interest:
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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:
- Publications:
Recent Publications:
McGuffin, L. J. & Roche, D. B. (2010) Rapid model quality assessment for protein structure predictions using the comparison of multiple models without structural alignments. Bioinformatics, 26,182-188. Pubmed
McGuffin, L.J. (2009) Prediction of global and local model quality in CASP8 using the ModFOLD server. Proteins: Structure Function and Bioinformatics,77, 185-190. Pubmed
McGuffin, L. J. (2008) Intrinsic disorder prediction from the analysis of multiple protein fold recognition models. Bioinformatics, 24, 1798-1804. Pubmed
McGuffin, L. J. (2008) The ModFOLD Server for the Quality Assessment of Protein Structural Models. Bioinformatics, 24, 586-587. Pubmed
McGuffin, L. J. (2007) Benchmarking consensus model quality assessment for protein fold recognition, BMC Bioinformatics, 8, 345. Pubmed
