MonBUG Seminar
December 10, 2009
6 to 9 pm

"The role of evolutionarily conserved ligand-interacting binding-site residues"

Rafael Najmanovich
Assistant Professor, Biochemistry Dept, Université de Sherbrooke

Leacock Building, Room 232, McGill University, 855 Sherbrooke St.W,Montreal


Evolutionarily conserved ligand-interacting binding-site residues are thought to be important to satisfy physico-chemical binding constraints. Recently we demonstrated that non-homologous proteins that evolved to bind similar ligands contain highly dissimilar patterns of conserved ligand-interacting binding-site residues. While the importance of conserved residues is unquestionable, these results suggest that conserved residues may play extra roles. We suggest that conserved residues may play the additional role of preventing the promiscuous binding of similar molecules present in the cellular milieu. Different patterns of conservation would reflect distinct cellular contexts. In support of this hypothesis, we created a dataset (and associated web-interface) of proteins with known structures containing binding site mutations in which both the wild type and mutant were crystallized with the ligand (as well as sometimes in the Apo form) demonstrating that the mutation does not prevent ligand binding. The dataset includes over 5000 entries containing between one and four mutations on residues with varying degrees of conservation in contact with ligands with varying levels of cognate similarity. Due to the experimental bias towards mutations on highly conserved residues, there are numerous cases of often-drastic changes on highly conserved residues bound to cognate ligands. If such drastic mutations do not prevent binding, the conserved residues in question must have a different essential function, including that of preventing promiscuity among other possibilities.

December 9th, 2009
2:30 - 3:30 pm

"Functional genomics in cancer and in stem cells"

Guillaume Bourque
Genome Institute of Singapore

Room 903, McIntyre Building, 3655 Promenade Sir-William-Osler, Montreal, Quebec


Next-Generation Sequencing has enabled a wealth of new applications. In this talk, I will show how new paired-end-tag sequencing strategies can efficiently provide the map of all structural changes in a given genome. Applying this technique to normal samples, cancer tumors and cancer cell lines and performing a comparative analysis can reveal different patterns of mutations and help identify important aberrations. Next, I will also look at some of the sequenced-based approaches that are used to explore transcriptional regulatory networks. Specifically, I will describe a study where we generated occupancy maps for three key regulatory proteins (OCT4, NANOG and CTCF) together with knockdown expression experiments (OCT4) in human and mouse Embryonic Stem cells. In this study we found that the binding profiles of OCT4 and NANOG were drastically different with only ~5% of the regions homologously occupied. We also showed that species-specific transposable elements have contributed up to 25% of the regulatory sites in both lineages and have wired new genes into the core regulatory network of human ES cells.

November 26th, 2009
1:00 - 2:30 pm

"Extracting information from biological networks"

Leonid Chindelevitch
Massachusetts Institute of Technology

Room 2120, Trottier Building, 3630 University Street, Montreal, Quebec H3A 2B2 1


In this talk, I will describe different types of biological networks and the information they can provide. I will first present a novel algorithm, PISwap, for computing global pairwise alignments of protein interaction networks, based on a local optimization heuristic that has previously demonstrated its effectiveness for a variety of other NP-hard problems, such as the Traveling Salesman Problem. Some interesting insights into the evolutionary history of the compared species will also be discussed. If time allows, I will briefly mention ongoing work on metabolic and signaling networks.

MonBUG Seminar
November 12, 2009
6 to 9 pm

"How perfect can protein interactomes be?"

Christian Landry
Faculté de Médecine Université de Montréal

Leacock Building, Room 232, McGill University, 855 Sherbrooke St. West, Montreal


Evolutionary theory tells us that biological systems need not be optimized and may very well accumulate nonfunctional elements. Mutational and demographic processes contribute to the cluttering of eukaryotic genomes and transcriptional networks with “junk” DNA and spurious DNA binding sites. Here, I question whether such a notion should be applied to protein interactomes- that is, whether these protein interactomes are expected to contain a fraction of nonselected, nonfunctional protein-protein interactions. I discuss evidence for the existence of these non-functional interactions in kinase-substrate networks from the analysis of the evolution of phosphoproteomes of mammals and fungi.

October 21st, 2009
2:30 to 3:30 pm

"Dominant Pathways in Protein Folding"

Dr. Henri Orland
Institut de Physique Théorique, France

McIntyre Medical Building, Room 903, 3655 Promenade Sir-William-Osler, Montreal, H3G 1Y6 1


Protein folding can be described by the Langevin dynamics. This dynamics can in turn be represented by a “path integral”, which is a weighted sum over all paths joining the denatured state with the native state of the protein. We show how one can compute the dominant paths (paths with largest weight) and how one can calculate dynamical quantities such as rates or transition path times from these paths. The method is illustrated on various simple examples.

October 14, 2009
2:30 to 3:30 pm

"Deriving Executable Models of Biochemical Network Dynamics from Qualitative and Semi-Quantitative Data"

Derek Ruths
McGill University,School of Computer Science

McIntyre Medical Building, Room 903, 3655 Promenade Sir-William-Osler, Montreal, H3G 1Y6 1


Progress in advancing our understanding of biological systems is limited by their sheer complexity, the cost of laboratory materials and equipment, and limitations of current laboratory technology. Computational and mathematical modeling provides ways to address these limitations through hypothesis generation and testing without experimentation - allowing researchers to analyze system structure and dynamics in silico and, then, design lab experiments that yield desired information about phenomena of interest. These models, however, are only as accurate and complete as the data used to build them. Currently most models are constructed from quantitative experimental data. However, since accurate quantitative measurements are hard to obtain and difficult to adapt from literature and online databases, new sources of data for building models need to be explored. In my research, I design methods for building and executing computational models of cellular networks based on qualitative experimental data, which is more abundant, easier to obtain, and reliably reproducible. Such executable models allow for in silico perturbation, simulation, and exploration of biological systems. In this talk, I will present two general strategies for building and executing Petri net-based models of biochemical networks. Both have been successfully used to model and predict the dynamics of signaling networks in normal and cancer cell lines, rivaling the accuracy of existing methods trained on quantitative data.

October 7, 2009
2:30 to 4:00 pm

"Ensemble predictions of RNA and Protein Structures"

Jerome Waldispuhl
McGill University,School of Computer Science

McIntyre Medical Building, Room 903, 3655 Promenade Sir-William-Osler, Montreal, H3G 1Y6 1


In this talk, I will describe my work in the area of computational structural biology. I will describe new ensemble modeling techniques which can analyze and predict an entire landscape of structural and evolutionary solutions, rather than simple single answer optimizations. This philosophy has a broad impact on our understanding of protein and RNA molecules -- Both of which I have applied this approach to and which I will address in this talk. First, I will introduce a new family of algorithms for investigating the folding landscape of transmembrane beta-barrel proteins based only on sequence information, broad investigator knowledge, and a statistical-mechanical approach using the Boltzmann partition function. This provides predictions of all possible structural conformations that might arise in-vivo, along with their relative likelihood of occurrence. Using a parameterizable grammatical model, these algorithms incorporate high-level information, such as membrane thickness, with an energy function based on stacked amino-acid pair statistical potentials to predict ensemble properties, such as the likelihood of two residues pairing in a beta-sheet, or the per-residue X-ray crystal structure B-value. Then, I will present recent algorithmic advances we have made in the techniques of exploration and analysis of RNA sequence/structure maps, an abstract framework which allows us to bridge different aspects of the sequence/structure relationship. In particular, we have successfully applied these techniques to discover deleterious mutations that radically modify the structure in the Hepatitis C virus cis-acting replication element. At a higher level, we provided evidence that the complete sequence of the 3'UTR of the GB RNA virus C has been optimized to preserve the secondary structure of the evolutionarily conserved stem regions from the destabilizing effect of pointwise mutations.