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Seminars, events & talks

Wednesday, 25th April, 2012, 11:00-12:00

Functional Genomics

De-Novo Discovery of Differentially Abundant DNA Binding Sites Including Their Positional Preference

The identification of DNA binding sites has been a challenge since the early days of computational biology, and its importance has been increasing with the development of new experimental techniques and the ensuing flood of large-scale genomics and epigenomics data yielding approximate regions of binding. Many binding sites have a pronounced positional preference in their target regions, which makes them hard to find as this preference is typically unknown, and many of them are weak and cannot be found from target regions alone but only by comparison with carefully selected control sets. Several de-novo motif discovery programs have been developed that can either learn positional preferences from target regions or differentially abundant motifs in target versus control regions, but the combination of both ideas has been neglected. Here, we introduce Dispom, a de-novo motif discovery program for learning differentially abundant motifs and their positional preferences simultaneously. Dispom outperforms existing programs based on benchmark data and succeeded in detecting a novel auxin-responsive element (ARE) substantially more auxin-specific than the canonical ARE.

Since its publication, we have endowed Dispom with more complex motif models and extended it to handle weighted input data such as ChIP-seq or BS-seq data. We have been applying Dispom to in-house and publicly available data of different transcription factors and insulators in yeasts, plants, and mammals as well as to protein-binding microarrays, where it turned out to be one of the top-scoring approaches in the corresponding DREAM challenge.

Speaker: Dr. Ivo Grosse, Institute of Computer Science, Martin Luther University, Halle, Germany

Room Xipre (seminar 173.06-183.01)

Wednesday, 28th March, 2012, 15:00

Evolutionary Genomics

The origin of new genes

Speaker: Diethard Tautz, Max-Planck Institut für Evolutionsbiologie, Plön, Germany

Room Xipre (seminar 173.06-183.01)

Friday, 23th March, 2012, 11:00

Computational Biophysics

How do antimicrobial peptides really work? Adventures in NMR of whole bacteria

The mechanisms that antimicrobial peptides (AMPs) use to disrupt membranes have been studied extensively using NMR and other
biophysical techniques. However, such studies have generally been limited to model lipid systems. In real life, antimicrobial peptides interact with a much more complex environment that includes membrane proteins, a peptidoglycan layer, lipopolysaccharide, lipid domains, etc. One way to illustrate the impact of this complexity is to consider the difference in peptide:lipid molar (P:L) ratios between the conditions under which the biological activity of AMPs is observed and the conditions under which NMR studies of mechanism are conducted. Solid-state NMR and other biophysical studies of model systems can typically show AMP-induced changes at peptide:lipid ratios close to 1:100. Strikingly, however, a ratio of 100 bacterially bound peptides per lipid is needed to see inhibition in an Escherichia coli sterilization assay, i.e., 10000 times more peptide per lipid. In order to bridge this enormous gap, we have designed a procedure to incorporate high levels of 2H NMR labels specifically into the cell membrane of Escherichia coli and used this approach to study the interactions between the AMP MSI-78 and the membranes of intact bacteria. I will present the highlights from these whole-cell studies along with results from solution NMR structural studies, as well as molecular dynamics simulations starting from unassembled bilayers.

Speaker: Valerie Booth- Department of Biochemistry and Department of Physics and Physical Oceanography, Memorial University of Newfoundland, Canada

Room Xipre (seminar 173.06-183.01)

Monday, 19th March, 2012

Integrative Biomedical Informatics

Integrative computational strategies addressing drug safety issues: the EU-ADR and eTOX projects

AMIA, San Francisco, 19-23 March 2012

Speaker: Sanz F

Friday, 9th March, 2012, Friday, March 9th 2012; 11:00-12:00,

Computational Biophysics

May the force be with you: Biomolecular Nanomachines and the Dynasome

Proteins are biological nanomachines. Virtually every function in the cell is carried out by proteins – ranging from protein synthesis, ATP synthesis, molecular binding and recognition, selective transport, sensor functions, mechanical stability, and many more. The combined interdisciplinary efforts of the past years have revealed how many of these functions are effected on the molecular level. Computer simulations of the atomistic dynamics play a pivotal role in this enterprise, as they offer both unparalleled temporal and special resolution. With state of the art examples, this talk will the type of questions that can (and cannot) be addressed, its (current) limitations, and how these can be overcome. The examples include aquaporin selectivity, mechanics of F-ATP synthase, flexible recognition by nuclear pore transporters, the mechanical properties of viral capsids, and tRNA translocation through the ribosome."

Speaker: Helmut Grübmuller, Max-Planck Institute, Goettingen, Germany

Room Xipre (seminar 173.06-183.01)

Thursday, 8th March, 2012, 11:00

GPCR drug discovery

Structure and age jointly influence rates of protein evolution

What factors determine a protein's rate of evolution are still under debate.  Especially unclear is the relative role of intrinsic factors of present-day proteins versus historical factors such as protein age. Here we study the interplay of structural properties and evolutionary age, as determinants of protein evolutionary rate.  We use a large set of one-to-one orthologs between human and mouse proteins, with mapped PDB structures. We report that previously observed structural correlations also hold within each age group – including relationships between solvent accessibility, designabililty, and evolutionary rates. However, age also plays a crucial role: age modulates the relationship between solvent accessibility and rate, and younger proteins, despite of being less designable, are evolving faster than older proteins. We show that previously reported relationships between age and rate cannot be explained by structural biases among age groups. Finally, we introduce a knowledge-based potential function to study the stability of proteins through large-scale computation. We find that older proteins are more stable for their native structure, and also more robust to mutations, than younger ones.  Our results underscore that several determinants, both intrinsic and historical, can interact to determine rates of protein evolution.

Speaker: Macarena Toll - Biomedical Informatics, GRIB (IMIM - UPF)

Room Aula

Friday, 2nd March, 2012, 11:00 - 12:00

Computational Biophysics

Structure-based drug design: Towards accurate predictions of thermodynamic and kinetic parameters

"The combination of increased availability of structural information, major boosts in computational power and methodological developments is taking structure-based drug discovery to a higher level. I will present the main research lines of the group, focussing on the development of a new type of docking scoring functions and the elucidation of structure-kinetics relationships. Together with new experimental methods, these type of tools will enable the discovery of drugs with more diverse and effective mechanisms of action."

Speaker: XAVIER BARRIL - Universitat Barcelona

Room Seminar Room “Xipre” 173.06 (PRBB 1st floor)

Thursday, 1st March, 2012, 11:00

GPCR drug discovery

Troublemakers in cancer: a tale of usual suspects and novel villains

The expansion of the catalogs of somatic alterations in cancer accelerate as new laboratories release the sequences of cohorts of samples of different tumor types. One of the key challenges posed by this growth is the identification of driver alterations, genes and pathways among all the alterations found in several patients with the same disease. Traditionally, likely driver mutations for instance are identified either by their recurrence or by their impact on protein function. On the other hand, genes and pathways are prioritized according to the recurrence of alterations that they bear in such groups of samples, however this approach have some known limitations. We have developed an approach to improve the capability of known tools to assess the functional impact of somatic mutations, based on  correcting their scores by the baseline tolerance of their bearing proteins. Also, we have developed a method to uncover cancer drivers based on the detection of the bias towards the accumulation of variants with high functional impact across several tumor samples. We present the results of applying this method to several cancer datasets and show that very different pathways to tumorigenesis prevail in each of them.

Speaker: Abel Gonzalez-Perez - Biomedical Informatics, UPF

Room Aula

Thursday, 9th February, 2012, 11:00

Computational RNA Biology

Development and analysis of a chordate and plant orthologous promoter database

Speaker: Endre Sebestyen. Regulatory Genomics Group- GRIB

Room Aula

Friday, 20th January, 2012, 11:00-12:00,

Computational Biophysics

Template Based Protein-Protein Interaction Prediction and Towards Structural Interactomes

Protein–protein interaction networks provide valuable information in understanding of cellular functions and biological processes. Recent advances in high-throughput techniques have resulted in large amount of data on protein-protein interactions and lead to construction of large protein-protein interaction networks. However, these networks lack structural (3D) details of most interactions, and these structural details are the key components usually for understanding the function of proteins. Therefore, integrating structural information into protein networks on the proteome scale is important because it allows prediction of protein function, helps drug discovery and takes steps toward genome-wide structural systems   biology. In this talk, a fast method for structural modeling of protein-protein interactions that combines template-interface-based docking with flexible refinement will be presented. Its application towards building structural protein-interaction networks will be discussed with the examples on p53 interactions and E2-E3  interactions. In addition, how the structural networks can help drug discovery along the line of emerging polypharmacology paradigm will be discussed.

Speaker: Prof. ATTILA GURSOY, College of Engineering, Koc University, Istanbul, Turkey

Room Seminar Room “Xipre” 173.06 (PRBB – 1st floor)

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