Mark Wass

Structural Bioinformatics Group
Division of Molecular Biosciences
Faculty of Natural Sciences

I have moved to the University of Kent

I can still be contacted at mark.wass04 AT imperial.ac.uk or new email address m.n.wass AT kent.ac.uk.

Prediction of Protein-Protein interactions using protein docking

Working with Alfonso Valencia at the CNIO in Madrid we have demonstrated the ability to use a protein docking method to predict protein interaction partners (pairs of proteins that interact). Protein docking programs are generally used to predict the shape of the complex formed between pairs of proteins that are known to interact. This is a difficult problem and docking methods often fail to generate accurate models of complexes. It had therefore been widely thought that it was beyond the scope of such program to predict IF two proteins interact.

For a set of known complexes we demonstrated that it is possible to distinguish the docking scores of the real complex from the individual proteins docked with a large set of decoy proteins. For more details see Wass et al., 2011, Mol Syst Biol 7:469.

Prediction of Ligand binding sites

My work on predicting ligand binding sites started when we participated in CASP8. We made manual predictions of ligand binding sites by identifying homologous structures and superimposing them on models of the predicted structure of the target protein. This effectively superimposed the ligands of the homologues onto the model of the target protein from which we predicted the binding site of the target protein. More details are available on our CASP results page and our paper in the CASP8 Special Issue of Proteins - Wass, M.N. and Sternberg, M.J. (2009) Prediction of ligand binding sites using homologous structures and conservation at CASP8.Proteins, 77 Suppl 9:147-51. PubMed. We have continued to perform well in the recent CASP9 assessment.

After CASP8 we automated our manual predictive approach in the 3DLigandSite server (http://www.sbg.bio.ic.ac.uk/3dligandsite).
3DLigandSite combines protein modelling and structural searches to predict ligand binding sites. The approach identifies structures homologous to a query protein that have bound ligands and superimposes their ligands onto a model of the query protein. The superimposed ligands aresued to predict a binding site on the qeury protein. Read about our performance in CASP8 (Wass and Sternberg 2009) and use the 3DLigandSite server at http://www.sbg.bio.ic.ac.uk/3dligandsite .

ConFunc - Protein Function Prediction
The thoushands of seqeucned genomes and millions of sequences identified by metagenomics projects make the prediction of protein function an important problem. While function prediction can be relatively simple when sequences share high levels of similarity, it is cases where sequences only have more remote homologues that current function prediction methods are ineffective. Therefore the aim of my PhD has been the development of function prediction methods that complement existing tools by performing well for these more difficult cases.

ConFunc is a sequence based protein function method. ConFunc identifies GO annotated sequences present in PSI-BLAST searches and uses these to identify conserved residues associated with each individual function, which in turn are used to infer the function of query sequences. ConFunc is available to the academic community via a webserver at http://www.sbg.bio.ic.ac.uk/confunc/. A paper describing ConFunc and the results that its has obtained is currently under review.

Convergent Evolution of Enzyme active sites
The phenomenon of Convergent evolution of enzyme active sites demonstrates the remarkable ability for unrelated enzymes to evolve identical catalytic machinery to perform the same reaction. There are a number of well known cases of convergent evolution, particularly the serine proteases. We have performed a systematic analysis to identify cases of convergent evolution of enzyme active sites using the pdb, catalytic site atlas and the E.C. classification. Our analysis demonstrates that convergent evoltion is not a rare phenomenon as it is present in approximately 15% of 3 digit E.C. numbers. Full details of this work are availble from Gheridini et a., JMB 2007 (see Publications below for details).

David, A., Razali, R., Wass, M.N.*, Sternberg, M.J.E.* (2011) Protein-protein interaction sites are hot spots for disease-associated non-synonymous SNPs. Human Mutation, In press.
*Joint senior author

Chambers JC, Zhang W, Sehmi J, Li X, Wass M.N.* et al., (2011) Genome-wide association study identifies loci influencing concentrations of liver enzymes in plasma. Nat Genet. doi: 10.1038/ng.970 Pubmed
*Co first author

Wass M.N., David A., Sternberg M.J. (2011) Challenges for the prediction of macromolecular interactions. Curr Op Struct Biol. 21:382-90 Pubmed

Wass M.N., Fuentes G., Pons, C., Pazos F., Valencia A. (2011) Towards the prediction of interaction partners using Physical docking. Mol Syst Biol 7:469 Pubmed

Sinden R.E., Talman A., Marques S.R., Wass M.N., Sternberg M.J. (2010) The flagellum in malarial parasites. Curr Opin Microbiol. 13:491-500 PubMed

Wass M.N, Kelley L.A. and Sternberg M.J. (2010) 3DLigandSite: predicting ligand-binding sites using similar structures.NAR 38, W469-73 PubMed

Chambers J.C. et al., (2010) Genetic loci influencing kidney function and chronic kidney disease. Nat Genet 42:373-5 PubMed

Chambers, J.C. et al., (2010) Genetic variation in SCN10A influences cardiac conduction. Nat Genet, 42:149-52 PubMed

Chambers, J.C., Zhang, W., Li, Y., Sehmi, J., Wass, M.N. et al., (2009) Genome-wide association study identifies variants in TMPRSS6 associated with hemoglobin levels. Nat Genet, 41, 1170-2. PubMed

Wass, M.N. and Sternberg, M.J. (2009) Prediction of ligand binding sites using homologous structures and conservation at CASP8. Proteins, 77 Suppl 9:147-51. PubMed

Wass, M.N. and Sternberg, M.J. (2008) ConFunc--functional annotation in the twilight zone, Bioinformatics, 24, 798-806. PubMed

Gherardini, P.F., Wass, M.N., Helmer-Citterich, M. and Sternberg, M.J. (2007) Convergent Evolution of Enzyme Active Sites Is not a Rare Phenomenon, J Mol Biol, 372, 817-845. PubMed

Brand, M. D., Boutilier, R. G., Wass, M., St-Pierre, J. & Bishop, T. (2001). Mitochondrial proton leak in metabolic depression. In Molecular Mechanisms of Metabolic Arrest: Life in Limbo, edited by K. B. Storey, 59-76

3DLigandSite: Predicting ligand binding sites using similar structures. AFP SIG 2011, Vienna, Austria. 

Towards the prediction of interaction partners using Physical docking. ISMB 2010, Boston, USA.

Towards the prediction of interaction partners using Physical docking. 3D-SIG 2010, Boston USA.

Protein Modelling - structure, function and interactions. Brains of Britain, UK Biotechnology Showcase at AusBiotech, Melbourne, Australia, October 2009

Using function, conservation and structure to predict ligand binding sites. CASP 8 Sardinia, December 2008

ConFunc – functional annotation in the twilight zone. CASP7.5, Madrid, Spain, April 2008

ConFunc: Feature derived profiles for functional annotation. AFP SIG, Vienna, Austria, July 2007.

Email: m.wass04 AT imperial.ac.uk OR m.n.wass AT kent.ac.uk

Morning slides
Afternoon slides

3dligandsite Example
CombFunc Example