Research Interests

The human genome sequence gives us a set of predicted protein sequences. Many of these proteins represent useful drug targets. However, simply knocking out or over-activating the primary enzymatic or signal transduction activity of such targets may not yield the most appropriate clinical response. For this reason, the pharmaceutical industry is increasingly focusing on targeting protein-protein interactions involved in more subtly modifying signalling in cells. There is strong evidence (www.elm.eu.org) that some short regions of proteins (<10 amino acids) have independent function, often involved in mediating transient protein interactions. These are attractive starting points for modulating protein interactions, since the interface between proteins is often relatively small, making it easier to modulate. We develop bioinformatic methods to systematically survey and identify short peptides and motifs of most interest from human andpathogen  proteins. With collaborators, we experimentally validate which of these are likely to be bioactive peptides. Such peptides/peptidomimetics may then be used to tease apart signalling pathways important in health and disease, and ultimately may themselves be lead therapeutics to target aspects of pathways.

 

 

Book Chapters

Mooney, C. and Wang, Y. and Pollastri, G.; (2011) 'De Novo Protein Subcellular Localization Prediction by N-to-1 Neural Networks' In: Rizzo, R. and Lisboa, P (eds). Computational Intelligence Methods for Bioinformatics and Biostatistics. Berlin / Heidelberg: Springer. [DOI] [Details]

Mooney, C. and Davey, N. and Martin, AJ and Walsh, I. and Shields, D.C. and Pollastri, G.; (2011) 'In Silico Protein Motif Discovery and Structural Analysis' In: Bing Yu and Marcus Hinchcliffe (eds). In Silico Tools in Gene Discovery. Humana Press. [DOI] [Details]

Martin, A.J.M. and Mooney, C. and Walsh, I. and Pollastri, G.; (2010) 'Contact Map Prediction by Machine Learning' In: H.Rangwala and G.Karypis (eds). Introduction to Protein Structure Prediction: Methods and Algorithms. Hoboken, NJ, USA: John Wiley & Sons, Inc. [DOI] [Details]

 

Peer Reviewed Journals

Norris, R; Casey, F; FitzGerald, RJ; Shields, D; Mooney C; (2012) 'Predictive modelling of angiotensin converting enzyme inhibitory dipeptides'. Food Chemistry, 133 (4):1349-1354. [DOI] [Details]

Mooney C, Pollastri G, Shields DC, Haslam NJ; (2011) 'Prediction of short linear protein binding regions'. Journal of molecular biology, . [DOI] [Details]

Mooney C, Wang YH, Pollastri G; (2011) 'SCLpred: protein subcellular localization prediction by N-to-1 neural networks'. Bioinformatics (Oxford, England), 27 (20):2812-2819. [DOI] [Details]

Walsh I, Bau D, Martin AJM, Mooney C, Vullo A, Pollastri, G; (2009) 'Ab initio and template-based prediction of multi-class distance maps by two-dimensional recursive neural networks'. BMC Structural Biology, 9 . [DOI] [Details]

Walsh I, Martin AJM, Mooney C, Rubagotti E, Vullo A, Pollastri G; (2009) 'Ab initio and homology based prediction of protein domains by recursive neural networks'. BMC Bioinformatics, 10 . [DOI] [Details]

                                   

Reports

Mooney C, Vullo A, Pollastri G; (2006) Protein Backbone Angle Prediction in Multidimensional phi-psi Space UCD CSI Technical Report 2006-1. Reports [Details]

                                                                         

Teaching Interests

Recent Postgraduates