Staff Profile:Dr Liam McGuffin

Name:
Dr Liam McGuffin
Job Title:
Academic, Harborne Bldg
Responsibilities:

Lecturer in Bioinformatics; Admissions Tutor for Biological Sciences

Areas of Interest:

Research Interests:

One of the fundamental areas of study in biomedical sciences is determining how proteins function within cells and how that function translates to health. To deliver on the promise of next generation sequencing for health care and personalised medicine, we must understand the information implicit in the genome, specifically, the functions of the proteins that are 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 3D 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 CJD being well known, if extreme, examples.

Determining the 3D fold of a protein is not always straight forward. In cases where the structure of a protein has been determined experimentally, the fold can then be directly visualised. However, solving structures experimentally is time consuming and expensive and so the vast majority of proteins with known sequences have unknown structures. Fortunately, in the majority of cases we can use predictive tools that allow us to rapidly and accurately model the shapes of proteins in silico, which helps us to determine their likely functions and interactions.

My main interest is in the development of computational methods for rapidly and confidently predicting the structures, functions and interactions of proteins using only amino acid sequence information. Once a catalogue of accurately predicted structures for the majority of proteins within a cell is available, the aim is to predict their ability to interact with small molecules and each other, to form the complex cellular machinery upon which life depends. This vital information will allow us to produce novel or more efficient products for use in medicine and will help us to better understand the mechanisms of the leading causes of death, such as heart disease and stroke.

My novel bioinformatics tools for predicting protein structures and functions rank among the top few internationally. The DISOclust, ModFOLD and FunFOLD methods and the IntFOLD integrated server for the prediction of structures and ligand interactions, have been particularly successful at the recent CASP competitions - further details can be seen on my group homepages: http://www.reading.ac.uk/bioinf/

Complete List of Publications

Google Scholar Profile with Citation Indices

Research groups / Centres:

Molecular and Cellular Medicine group

Institute for Cardiovascular & Metabolic Research (ICMR) 

Publications:
Y
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This list was generated on Wed Jun 19 14:33:09 2013 BST.

 

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Contact Details

Email:
l.j.mcguffin@reading.ac.uk
Telephone:
+44 (0) 118 378 6332
Fax:
+44 (0)118 378 8106
Building:
127 Harborne

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