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Seminars, events & talks

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)

Thursday, 19th January, 2012, 11:00

Evolutionary Genomics

Evolutionary dynamics of short indels in mammalian genomes

Insertions and deletions (indels), together with nucleotide substitutions, are major drivers of sequence evolution. An excess of deletions over insertions in genomic sequences-the so-called deletional bias-has been reported in a wide range of species, including mammals. However, this bias has not been found in the coding sequences of some mammalian species, such as human and mouse. To determine the strength of the deletional bias in mammals, and the influence of mutation and selection, we have quantified indels in both neutrally evolving noncoding sequences and protein-coding sequences, in six mammalian branches: human, macaque, ancestral primate, mouse, rat, and ancestral rodent. The results  indicate that contrary to previous results, the only mammalian branch with a strong deletional bias is the rodent ancestral branch. We estimate that such a bias has resulted in an 2.5% sequence loss of mammalian syntenic region in the ancestor of the mouse and rat. Further, a comparison of coding and noncoding sequences shows that negative selection is acting more strongly against mutations generating amino acid insertions than against mutations resulting in amino acid deletions. The strength of selection against indels is found to be higher in the rodent branches than in the primate branches, consistent with the larger effective population sizes of the rodents.

Speaker: Steve Laurie, Biomedical Informatics, IMIM-UPF

Room Marie Curie

Wednesday, 18th January, 2012, 12:00h

Computational RNA Biology

Understanding RNA through massively parallel sequencing (RNA in the ENCODE project)

The unfolding of the instructions encoded in the genome is triggered by the transcription of DNA into RNA, and the subsequent processing of the resulting primary RNA transcripts into functional mature RNAs. RNA is thus the first phenotype of the genome, mediating all other phenotypic changes at the organism level caused by changes in the DNA sequence. While current technology is too primitive to provide accurate measurements of the RNA content of the cell, the recent development of Massively Parallel Sequencing Instruments has dramatically increased the resolution with which we can monitor cellular RNA. Using these instruments, the ENCODE project has surveyed the RNA content of multiple cell lines and subcellular compartments. The results of these surveys underscore pervasive transcription, as well as great RNA heterogeneity between and within cells. Comparison of RNA surveys with other genome wide epigenetic surveys—such as those of binding sites for Transcription Factors, or of Histone modifications—reveals a very tightly coupling between the different pathways involved in RNA processing, transcription and splicing in particular.

Speaker: Roderic Guigó, CRG

Room Auditorium PRBB

Wednesday, 11th January, 2012, 12:00

GPCR drug discovery

Cracking the cancer code, a bioinformatics journey

Nuria Lopez-Bigas obtained her PhD for work on the molecular causes of hereditary deafness at the group of Xavier Estivill. After a postdoc on computational genomics at the European Bioinformatics Institute (with Christos Ouzounis) and at the CRG (with Roderic Guigó), she established her laboratory at the University Pompeu Fabra in 2006. In 2011 she was appointed ICREA research professor.

Thanks to the advance of genomic technologies it is currently possible to obtain a comprehensive catalog of genomic alterations in cancer cells. However the identification of alterations directly involved in the development of the tumor is challenging. Nuria Lopez-Bigas current research focuses on the development of computational approaches to analyse cancer genomic data with the objective to identify genes and pathways driving tumorigenesis.

Speaker: Nuria López-Bigas, GRIB (IMIM - UPF)

Room Auditorium PRBB

Friday, 18th November, 2011, 11:00-12:00

Computational Biophysics

Protein flexibility in docking with discrete molecular dynamics simulations

The aim of protein-protein docking is to predict how two proteins associate to form a complex. This means determining where will be the interface. This is a complex problem with many degrees of freedom. To reduce the sampling space, in general both proteins are considered to be rigid bodies (rigid docking). This reduces the problem to 6 degrees of freedom (3 for translation and 3 for rotation). The rigid body docking is a rude approach, since the proteins have flexibility and may undergo relevant conformational changes upon binding to the other protein when forming the complex. We have used discrete molecular dynamics (DMD) simulations to include the protein flexibility in docking configurations, and we have improved the predictive power of the method. DMD is a simplified molecular dynamics method much faster than standard MD, specially for systems with less that 10^3 particles.

Speaker: Dr. Agustí Emperador-Institut for Research in Biomedicine (IRB, Barcelona)

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

Thursday, 17th November, 2011, 11:00-12:00

GPCR drug discovery

Co-Alterations in Human Cancer

Big efforts are being made to reveal the alterations that have occurred in the genomes of cancerous cells. Especially the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) will contribute by collecting data in a standardized way and make it publicly available.

With the already available data, an abundance of alterations of different types have been found – some so-called driver alterations that drive the cell towards its cancerous state and some passenger alterations that are a by-product of the cancer development.

It is an ongoing challenge to discriminate driver from the passenger mutations even though a variety of methods have been proposed up to this day. These include methods based on recurrence of alterations (RBM) across a cohort of samples and sequence based methods (SBM) that assess the impact of mutations on the functionality of the protein product.

We are working on how to detect the coaltered pairs that are candidates for having a synergistic effect. We hypothesize that some driver alterations may only have their driver effect when occurring with a certain other driver alteration – synergistic drivers. This could be reflected by either the strict co-occurrence of the driver alterations along the samples and/or similar expression patterns of reporter genes of the candidate drivers.

Speaker: Michael P. Schroeder

Room 473.10_Aula

Friday, 28th October, 2011, 11:00 - 12:00

Computational Biophysics

Understanding allosteric effects in receptor and non-receptor kinases

Protein kinases (PK) are one of the largest and most functionally diverse protein families and are involved in most cellular pathways. PK malfunction is related to an important number of human diseases, such as cancer, diabetes and cardiovascular diseases. Thus, PK represent major targets for drug development. Historically, drug discovery programs have been dominated by efforts to develop antagonists that compete for binding with endogenous ligands at orthosteric sites. However, allosteric drugs might offer several therapeutic advantages over traditional orthosteric ligands, including greater safety and/or selectivity. Here, by combining of state-of-the-art computer simulations as well as spectroscopy, chemical and molecular biology approaches we  study in great details complex allosteric effects in the pharmaceutically relevant Abl and FGFr kinases. In Abl a shift of the SH2 domain from the C- to the N-terminus of the catalytic domain has been found to be involved in activation [1]. The allosteric mechanism, by which the SH2 domain induces conformational changes at the active site, is still debated. We have used elastic network models, normal mode analysis, molecular dynamics simulation and mutagenesis to gain insight into the interplay between the SH2 domain and the relevant motifs at the catalytic site. We propose a mechanism, by which the SH2 domain influences the dynamics of the crucial residues directly involved in the catalytic process. In FgFr we use free energy calculations, crystallography and NMR approaches to shed light on the mode of action of a novel allosteric inhibitor. [2]
[1] Nagar B, Hantschel O, Seeliger M, Davies JM, Weis WI, Superti-Furga G, Kuriyan J Molecular Cell 2006, 21, 787-798.
[2] F. Bono et al., submitted.

Speaker: Dr. Francesco Gervasio - Computational Biophysics Groups. CNIO, Madrid

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

Friday, 14th October, 2011, 11:00-12:00

Computational Biophysics

Markov models of molecular conformation dynamics: Computing rare events in biomolecules

The simulation of conformational dynamics, inclucing protein folding, aggregation and conformational switching, is one of the main challenges of the molecular sciences. Unfortunately, these processes are rare events such that single long molecular dynamics simulations often fail to sample them. One way out is to distribute many short simulation trajectories onto independent processors, which are then combined into a single Markov model of the conformation dynamics. It can be shown that Markov models can successfully predict slow kinetics even when they are constructed from short trajectories, thus bridging the gap from short simulations to long timescales. Here, I will show how Markov models and related ideas are useful to understand the kinetics of protein folding and the conformational dynamics of the polymeric protein Dynamin. 

Speaker: Dr. Frank Noé -Computational Molecular Biology (CMB) - Freie Universität Berlin, Germany

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

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