What is this meeting about?
Barcelona School of Informatics
Speakers and schedule
Welcome to Barcelona and to this workshop on In Silico tools in drug design and target discovery. This is a one-day workshop organized from the Spanish Network of Supercomputation (RES) with the aims to illustrate the use of high performance computing in the development of new therapies, and to approach the field of computational science to the drug discovery world. I am sure is going to be an exciting meeting, and I am convinced we will learn on the latest advances in chemoinformatics, genomics approaches to target finding, network medicine and structure based drug design. We hope to see you in Barcelona.
Modesto Orozco. Organizing Commitee
How to arrive?See a map of all the public transport available and get some indications below:
The nearest stations are "Palau Reial" and "Zona Unversitaria" (L3 or Green Line). You will have a 7-minutes walking distance to arrive to the meeting. Check maps, timetables and fares in Transports Metropolitans de Barcelona.
Different bus lines arrive near the meeting place, see the map linked above. Check maps, timetables and fares in Transports Metropolitans de Barcelona.
The tram station more near is "Palau Reial". Obtain more information on times and fares, we recommend visiting the website www.tram.cat.
The train station more near is Barcelona Sants and from this station you will have to take the L3 or Green Line in direction to “Zona Universitaria” and drop in the “Palau Reial” or "Zona Unversitaria" stations.To get more information on times and fares, we recommend visiting the website Renfe Cercanías Barcelona.
8:45 - 9:15 Registration
9:00 - 9:15 Modesto Orozco, David Vicente & Francesc Subirada
Welcome presentation of the symposium and the Spanish Network of Supercomputation (RES)
9:15 - 9:55 Emilio Diez-Monedero. GSK
9:55 - 10:20 Coffee Break
10:20 - 11:00 Federico Gago (U. de Alcalà)
The single worldwide archive of structural data of biological macromolecules is the Protein Data Bank (PDB; http://www.rcsb.org/pdb/) together with its partners in both Europe (PDB-e) and Japan (PDB-j). Within a PDB entry, individual monomers making up a protein (ATOM records) and solvent molecules and/or other ligands (HETATM records) form the principal building blocks or chemical components. These molecular definitions, currently numbering almost 20 000, are assembled in a reference data resource called the PDB Chemical Component Dictionary (CCD), which is not widely known and may be too cumbersome to understand in full detail. Most typical end users will download coordinate files from the PDB to view the structure in an interactive molecular graphics program and believe that everything that appears on the screen is equally sound. Over the years many expert scientists have also used different collections of ligand-receptor complexes from the PDB (and corporate databases) to fine-tune, test and compare a variety of computational methods for docking, virtual screening (VS) and structure-based drug design (SBDD). It has been revealed in several published studies, however, that a significant number of these three-dimensional models, which are built to approximate electron density maps derived from crystallographic data, can contain misleading inaccuracies, a fact that has been repeatedly appreciated by many savvy individuals in their daily work. It is then crucial to know the underlying error in these models if they are going to be profitably used for the accurate computation of ligand–protein interactions and to develop better VS and SBDD methods. As a result of the mandatory deposition of primary diffraction data, stringent validation of protein–ligand models has become possible in the last few years and some tailor-made computational tools are available nowadays to aid in this process. Furthermore, a series of alternative structural data banks offer re-refined and expanded data sets that can be downloaded directly using popular programs such as PyMOL and Coot. Finally, ensemble models have been shown to fit the X-ray data better than single structures but this practice is still in its infancy. An overview of these caveats and solutions will be briefly presented.
11:00 - 11:30 Victor Guallar (BSC)
Understanding the protein-ligand interaction mechanism requires the description of ligand migration and binding site induced fit. Such study involves dynamic time scales on the range of micro- to mili- seconds, a non-trivial task for current computational methods. Despite these difficulties, it has centered a great deal of effort from the molecular dynamics community, with its highest point, probably, in the recent design and development of the ANTON machine.
Here we will present an alternative to MD techniques. Using technological advances in protein structure prediction, we have recently introduced PELE (protein energy landscape explorations). PELE combines a Monte Carlo stochastic approach with protein structure prediction algorithms and is capable of accurately reproducing long time scale processes in only few hours of CPU (typically no more than an overnight computing period). For example, we can map de free (non biased) ligand diffusion and binding, such as the one performed with ANTON at a fraction of the cost, ~16 processors for 24 hours. Recently, by combining PELE with markov state models (MSM), we obtained absolute binding free energies at an affordable computational cost. This talk will summarize the technique, our latest studies of protein and protein-ligand dynamics, and the web server where the software is available for remote run.
11:30 - 12:00 Nuria Lopez Bigas (UPF)
Distinguishing the mutations directly involved in cancer, driver mutations, from the myriad of somatic mutations in a tumor genome is one of the major challenges of cancer research. This challenge is accentuated for mutations in non-coding regions. Given the evolutionary principles of cancer, one effective way to identify genomic elements involved in cancer is by tracing the signals left by the positive selection of driver mutations across tumours. We have applied this approach to identify 459 protein-coding cancer genes with driver mutations by analyzing close to 7000 tumor exomes from 28 different cancer types, and we have searched for their targeted therapeutic opportunities. Currently we are analyzing more than 2700 tumor whole-genomes, as part of the International Cancer Genome Consortium Pancancer Analysis of Whole Genomes Project, to identify non-coding elements with somatic cancer driver mutations, including promoters, enhancers, 5' and 3' untranslated regions, microRNAs and lncRNAs.
12:00 - 12:30 Patrick Aloy (IRB)
Network and systems biology offer a novel way of approaching therapeutics by developing models that consider the global physiological environment of protein targets, and the effects of modifying them, without losing the key molecular details. In this talk, I will discuss two recent projects developed in the lab that exploit global properties of complex systems. In particular, I will present a computational network biology strategy, based on the quantification of pathway crosstalk inhibition in therapeutic networks, to discover synergistic drug combinations for breast cancer treatment. In addition, I will show how taking a chemo-centric view of human health, which does not require detailed mechanistic information, we can build networks of human conditions able to predict disease comorbidities, as well as identifying potential drug side effects and opportunities for drug repositioning.
12:30 - 13:00 Xavier Deupi (Paul Scherrer Institute)
G protein-coupled receptors (GPCRs) are a large family of transmembrane proteins that trigger cellular signaling responses upon binding of extracellular ligands. Thus, GPCRs act as transmission devices between the environment and the cell interior and, due to this key physiological role, they constitute one of the most important pharmaceutical targets. However, despite recent breakthroughs in GPCR crystallography, the structural and mechanistic aspects of GPCR activation by drugs are not yet well understood. This is partly due to missing dynamical information, which can, in principle, be provided by NMR. However, only limited information of functional relevance on few side chain sites of eukaryotic GPCRs has been obtained to date.
Together with the group of Prof. Grzesiek (Biozentrum, University of Basel), we have recently shown that receptor motions can be followed in stabilized mutants of the β1-adrenergic receptor. We observe that the response to various ligands is heterogeneous in the vicinity of the extracellular binding pocket, but gets transformed into a homogeneous readout at the intracellular side of the receptor. By analyzing the effect of several mutations, we conclude that even a fully stabilized receptor is able to undergo certain activating motions, but the fully active state is only reached in presence of (a) two specific key residues (Y5.58 and Y7.53), and (b) a stabilizing partner in the cytoplasmic side (e.g. an antibody that mimics the cognate G protein).
Our analysis allows us to identify crucial connections in the allosteric signal transmission pathway of ligand-induced GPCR activation, and represents a general method to delineate signal transmission networks at high-resolution in GPCRs.
13:00 - 13:30 A.Oubrie (LeadPharma)
Nuclear receptors constitute one of the main protein target families for small molecule drug discovery. In the past, drug hunting activities against these targets were focused on steroid receptors such as the glucocorticoid receptor. At the moment, other members of the nuclear receptor family are also being actively pursued. Some case examples will be given.
13:30 - 15:00 Lunch
15:00 - 15:30 Manuel Pastor (UPF)
Drug safety assessment is living a change of paradigm. Diverse forces are pushing to replace classical toxicology using in vivo testing of apical endpoints by alternative methods. Recent advances in the definition of Adverse Outcome Pathways for diverse toxicity endpoints are also providing the necessary theoretical framework for a more detailed mechanistic understanding of drug toxicity. This scenario offers a unique opportunity to in silico approaches to become a key component of future drug safety assessment. At the same time, the complexity of the physiological phenomena involved in toxicity and the characteristics of the practical problems that must be addressed in drug development make their application challenging. Here we will present an overview of the current situation and some examples of in silico methods application, based in our experience in several European projects in this field (eTOX, iPiE and EU-ToxRisk).
15:30 - 16:00 Rebecca C. Wade (Heidelberg ITS)
The dynamic nature of protein structures provides challenges and opportunities for ligand design. I will discuss computational approaches that we are developing to compare protein binding sites, to identify transient pockets for ligand design, and to investigate protein motions that affect ligand binding and unbinding processes.
16:00 - 16:30 J.M. Jimenez (Vertex Pharmaceuticals)
This presentation outlines the design and optimization of novel classes of potent and selective kinase inhibitors using a SBDD approach. Examples will be used to illustrate the use of structural information derived from homology models. These models were built based on crystal structures of closely related kinases. Dramatic improvements in potency and selectivity from HTS hits were achieved. Deep understanding of key interactions within the ATP binding site drove potency improvements. In addition, subtle differences with closely related kinases were exploited to achieve good selectivity against family members that have almost identical binding sites.
16:30 - 16:50 Cofee Break
16:50 - 17:20 Xavier Barril (UB)
Structure-based methods for drug design aim to predict the thermodynamic stability of protein-ligand complexes, but we show that structural stability is equally important. This property can be assessed with inexpensive dynamic undocking calculations, which are an excellent complement to existing methods (e.g. molecular docking). The efficacy of the approach is demonstrated on a virtual fragment screening application.
17:20 - 17:50 Andrea Cavalli (U. Bologna)
Drug-target recognition and binding is a complex physicochemical process that represents the first event at the basis of the therapeutic action of drugs. Indeed, drugs navigating into the cell recognize their biological counterparts, loosely interact with them, and finally establish tight binding interactions with targets. This complex process is regulated by thermodynamic and kinetic parameters, which can eventually account for drug potency and in vivo drug efficacy.
Molecular simulation is emerging as a powerful tool for investigating protein-ligand binding. In particular, molecular dynamics (MD) simulation is getting increasing consensus from the drug discovery community, and MD-related approaches, including enhanced sampling methods, are playing a pivotal role in computational drug design. While extensive MD simulations in the microsecond to the millisecond timescale are nowadays able to simulate protein-ligand binding “spontaneously”, enhanced sampling methods, including metadynamics, steered-MD, umbrella sampling, etc., can improve the sampling of that part of free energy that can be relevant for the biological process under investigation.
In this talk, I will be presenting the use of extensive MD simulations to investigate spontaneous protein-ligand binding. In addition, I will show how free energy calculations allow the identification of the minimum free energy path from the bulk of the solvent into the protein-binding pocket, as well as the determination of thermodynamic and kinetic parameters associated to drug-target recognition and binding. The presentation will then be focused on applications of enhanced sampling methods to accelerate ligand binding and unbinding and to estimate kinetics and thermodynamics, in simulation timescale more compatible with the requirements of speed and accuracy of the pharmaceutical research. All these simulations will be discussed in the framework of drug design and discovery, highlighting the role of these approaches in real-life drug discovery endeavors.
17:50 - 18:00 Robert Soliva (BSC)
Wrapping up & conclusions