Thornton Group Member Details

Pedro Ballester, MRC Methodology Research Fellow

My work focuses on the development and application of new computational tools to analyse and predict protein-ligand binding. While at Oxford University, I developed and validated a particularly efficient, alignment-free molecular shape similarity method. In collaboration with colleagues at Oxford’s Pharmacology Department, I applied this tool prospectively to identify novel inhibitors of a breast cancer target. During my recent one-year postdoc at Cambridge University, I worked on non-parametric machine learning approaches to predicting protein-ligand binding affinity by exploiting structural and interaction data. These tools can be used as re-scoring functions as well as to investigate the impact of modelling assumptions on predictive performance. More recently, I have become interested in the application of evolutionary algorithms to improve in silico docking of molecules with high conformational flexibility. This reconnects with my PhD work at Imperial College London on nonlinear parameter estimation using real-coded genetic algorithms. I currently hold a four-year Methodology Research Fellowship from the UK's Medical Research Council.

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I am a post-doctoral research fellow in the Thornton group involved in the EMBL Interdisciplinary Postdocs (EIPOD) program. My current project is a systems biology approach to study protein kinase and phosphatase networks. I perform computational analysis of kinases and phosphatases to understand and predict the potential protein-ligand interactions in the Thornton Group (EMBL-EBI, Cambridge). I will also test the predictions using biochemical methods in the Köhn Group (EMBL, Heidelberg) and crystallographic approach in the Wilmanns Group (EMBL, Hamburg). Prior to joining EBI, I did my PhD under the supervision of Prof. Renxiao Wang at Shanghai Institute of Organic Chemistry (SIOC), China. The projects included: (i) discovery and development of small-molecule inhibitors of Bcl-2 family proteins, which are promising anticancer targets involving protein-protein interactions; (ii) evaluation of computational methods including molecular docking and scoring functions in structure-based drug design; (iii) systematic study on covalent interactions between protein and ligand with experimentally determined complex structures and binding affinity data.