You are cordially invited to a talk in the Edmond J. Safra Center for
Bioinformatics Distinguished Speaker Series.
The speaker is Prof. Michael Sternberg, Director of the Centre for Integrative
Systems Biology and Bioinformatics of the Imperial College, London.
Title:
"Computational studies on the analysis of biological networks,
nsSNP phenotypic effects, and the discovery of novel pharmaceutical
compounds"
Time:
Wednesday, 28 August 2013, at 12:15 (sharp).
Place:
Schreiber building, room 309
Abstract: The talk will cover a series of computational studies in bioinformatics, systems biology and chemoinformatics.
The talk will begin introducing bioinformatics tools from our laboratory to predict protein structure from sequence (Phyre), protein
function from sequence (Combfunc and 3D-Ligand site), and to compare protein-protein interaction networks.
A major challenge in systems biology is to interpret incomplete data from transcriptomic and metabolomics studies across the genome
scale. We have developed a novel logic-based approach using abductive learning to identify the regulating reactions which has been
applied to study the xenobiotic response in rats exposed to phenobarbital. About 500 transcriptomic and 50 metabolomic data
measurements were integrated across the rat metabolic network of over 2,000 reactions. Regulating reactions were identified for the
different phases of the xenobiotic response.
With the advent of fast and cheap genome sequencing, we are rapidly obtaining information about non-synonymous single nucleotide
polymorphisms (nsSNPs) and their association with both Mendelian and complex diseases. A bioinformatics analysis has shown that
nsSNPS located at interfaces of protein-protein interactions are hot spots for disease compared to other surface positions. A further
analysis showed that certain protein domains are preferentially associated with disease. Following on from these studies, we have
developed a novel algorithm (SuSPect) to predict the phenotypic effect of an nsSNP which outperforms current methods including SIFT,
PolyPhen2 and MutationAssessor
The final topic is to describe a logic-based approach (INDDEx) to identify in silico novel pharmaceutical hits. We learn rules describing
sub-pharmacophores from a set of ligands of known activity. These rules are then used to screen computational databases of available
small molecules to find novel hits. The approach has been benchmarked and shown to identify novel scaffolds with the potential for
novel patents. In an in-house trial we identified a novel inhibitor of a histone deacetylase (SIRT2) with an IC50 of 0.6 microM.
Prof. Haim Wolfson, wolfson@tau.ac.il, School of Computer
Science, Tel Aviv University.
Host: