Structure-Based Drug Design Conference Final Brochure.pdf

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WEDNESDAY, JUNE 8 12:00-1:20 pm Main Conference Registration STRUCTURE-BASED KINASE INHIBITOR DESIGN & KINASE SELECTIVITY (Shared session with Next-Gen Kinase Inhibitors Conference) 1:10 Chairperson’s Remarks Andrew C. Good, Ph.D., Distinguished Scientific Fellow, Medicinal Chemistry, Genzyme Corp. 1:15 Discovery of Crizotinib (PF-02341066)-A c-Met/ALK Dual Inhibitor for Oncology Applications Jean Cui, Ph.D., Associate Research Fellow, Oncology Medicinal Chemistry, Pfizer, Inc. Crizotinib (PF-02341066) has shown remarkable efficacy for lung cancer patients with EML4-ALK fusion gene and is currently in Phase III clinical trials. Crizotinib is created as a c-Met/ALk dual inhibitor using structurebased drug design in combination with medicinal chemistry principles. 1:45 A Role for Hydration in Interleukin-2 Inducible T Cell Kinase Selectivity Ronald Knegtel, Ph.D., Research Fellow I, Molecular Modeling, Vertex Pharmaceuticals (Europe) Ltd. A series of Itk inhibitors that achieve selectivity through the introduction of a single, solvent exposed aromatic nitrogen atom without direct interactions with the enzyme is reported. By analyzing active site hydration using WaterMap, the selectivity profile can be explained in terms of the replacement of a thermodynamically unfavorable water molecule by the inhibitor and improved hydration of the bound ligand. This hydration site was successfully used to enrich virtual screening results in their content of selective Itk inhibitors. 2:15 Overcoming Drug-Resistant Mutations in Kinase Drug Discovery: Applying Lessons from Ponatinib (AP24534) David C. Dalgarno, Ph.D.,Vice President, Research Technologies, ARIAD Pharmaceuticals, Inc. Ponatinib (AP24534) is a novel BCR-ABL inhibitor that inhibits both native and mutant BCR-ABL, including the T315I gatekeeper mutation, and hence acts as a pan-BCR- ABL inhibitor. We recently analyzed the structural basis for this pan-BCR-ABL activity. Here we discuss this analysis and how it can be applied to other kinase targets exhibiting mutation-based resistance, and how the lessons from ponatinib can be applied to the design of other mutant kinase inhibitors. 2:45 Structure-Based Kinase Sponsored by Inhibitor Design & Kinase Selectivity Stephen A. Parent, Ph.D., Director of Business Development, Reaction Biology Corporation RBC provides drug profiling and screening services using HotSpot technology, a high-throughput radioisotopic screening platform with more than 370 kinases. We will describe its application to kinase inhibitor development and kinase inhibitor selectivity. 3:00 Networking Refreshment Break in the Exhibit Hall with Poster Viewing 3:30 Structure-Guided Fragment-Based Drug Discovery for Protein Kinase Targets Stephen K. Burley, M.D., D.Phil., Distinguished Lilly Research Scholar, Lilly Biotechnology Center, Eli Lilly and Company 4:00 How Molecular Dynamics Simulation May be Applied in Structural Based Design of Kinase Drugs Yibing Shan, Ph.D., Senior Scientist, Chemistry and Biology, D. E. Shaw Research The understanding of the extensive conformational heterogeneity of protein kinases is crucial to the understanding of kinase drugs’ binding and specificity. To this end, long molecular dynamics (MD) simulations, which for the first time reached the relevant timescale of micro- to millisecond, may prove a powerful tool. Our MD study of Abl, Src, and EGFR kinases will be discussed as examples of such effort in its early stage. 4:30 Recent experience establishing a new lead ID capability to pursue oncology kinase targets. Hans-Peter Biemann, Ph.D., Associate Scientific Director, In vitro Biology, Genzyme Corporation Genzyme’s small molecule discovery unit has incorporated fragmentbased and x-ray structure-assisted technologies over the last three years. Ligands of 150-250 Daltons have undergone structure-assisted elaboration to identify novel potent and selective inhibitors of tyrosine and ser/thr kinases, including Pim-1. One program progressed a tyrosine kinase to late lead optimization in 2.5 years and newer projects have productively commenced outside of the kinase and oncology sectors. This evolution of our HTS-based drug discovery unit to a multiplatform format enables us to address a number of target classes more expediently than before. 5:00 Longstanding Kinase Contributor Panel: Structure-Based Kinase Inhibitor Design Topic: Insights correlating kinase selectivity and toxicity Andrew C. Good, Ph.D., Distinguished Scientific Fellow, Medicinal Chemistry, Genzyme Corp. Ravi G. Kurumbail, Ph.D., Research Fellow and Structural Biology Laboratory Head, Pfizer, Inc. Dirksen Bussiere, Ph.D., M.B.A., Director, Structural Chemistry, Novartis Institutes for BioMedical Research 5:00-6:00 Registration for Dinner Short Course Wednesday Evening, June 8, 2011 Dinner Short Course* 6:00-9:00 pm Identification of Druggable Sites for Protein- Protein Interaction Targets Despite the growing number of examples of small molecule inhibitors that disrupt protein-protein interactions (PPIs), the origin of druggability is poorly understood. This course is designed to demonstrate the use of computational methods to determine the most likely structure of the complex formed by interacting proteins, identify potentially druggable sites in the interface, determine whether the target is druggable, and provide information on potential ligands. Participants will study a number of targets using web-based software (including PIPER and ClusPro, currently the best protein docking tools available) on their laptops. Course Instructors: Dima Kozakov, Ph.D., Research Assistant Professor, Departments of Biomedical Engineering, Boston University Dmitry Beglov, Ph.D., Senior Research Scientist, Structural Bioinformatics Laboratory, Boston University Ryan Brenke, Ph.D., Postdoctoral Research Associate, Structural Bioinformatics Laboratory and Department of Chemistry, Boston University David R. Hall, Ph.D. student, Department of Biomedical Engineering, Boston University *Separate Registration Required THURSDAY, JUNE 9 8:00 am Morning Coffee PROTEIN FLEXIBILITY AND DRUGGABILITY 8:25 Chairperson’s Opening Remarks Woody Sherman, Ph.D., Vice President, Applications Science, Schrodinger, Inc. 8:30 FAST Prediction of Protein Stability and Flexibility Donald Jacobs, Ph.D., Associate Professor of Physics, Physics and Optical Science, University of North Carolina Funded by NIH R01-GM073082, a novel computational method based on free energy decomposition and an iterative self-consistent reconstitution involving network rigidity to account for non-additivity in conformational entropy due to correlated motions has been developed. The program, FAST, provides a Flexibility And Stability Test for proteins that quantifies stability/flexibility relationships for understanding function. Speed versus accuracy is optimized for high-throughput screening to test for structure/function 2 healthtech.com/SBD
elationships in mutation studies, substrate binding, pKa predictions, allostery, protein-protein interactions and protein formulation. 8:55 Predicting Selectivity and Druggability in Small Molecule Drug Discovery Alan Cheng, Ph.D., Senior Scientist, Chemistry Research & Development, Amgen, Inc. Structure-based druggability and selectivity analyses increasingly inform target assessment and setting of lead optimization strategies in drug discovery. Continuing work on druggability prediction will be presented in the context of applying druggability prediction approaches to large numbers of protein structures. Work on selectivity analysis will be presented in the context of kinase inhibitor discovery examples from Amgen, and we will show how a thermodynamics-based selectivity index can help in predicting biological selectivity. 9:20 Development of a Simple Metric for the Structure-Based Assessment of Protein Druggability Emanuele Perola, Ph.D., Research Fellow I, Vertex Pharmaceuticals Accurate assessments of target druggability could significantly reduce the attrition rate in drug discovery programs. We developed an algorithm to isolate and characterize the binding pockets of protein targets and used it to analyze a set of validated drug targets and a diverse set of proteins with known crystal structures. We identified five parameters that differentiate the two sets in a statistically significant manner and derived a set of simple rules that could be applied to estimate the druggability of prospective targets. 9:45 Improvements in Predicting Sponsored by Protein-Ligand Binding Energies: Waters, Protein Flexibility, and Empirical Scoring Woody Sherman, Ph.D., Vice President, Applications Science, Schrodinger, Inc. Recent years have seen significant advancements in structure-based drug design methods. The inclusion of explicit waters and protein flexibility have proven to be critical components of improved protein-ligand scoring. We will discuss these advances and how they have produced more robust scoring and have been integrated into the Glide XP empirical scoring function to significantly improve virtual screening enrichments. 10:15 Networking Coffee Break in the Exhibit Hall with Poster Viewing PROTEIN-PROTEIN INTERACTION 10:45 Identification of Druggable Sites for Protein-Protein Interaction Targets by Computational Fragment Mapping Dima Kozakov, Ph.D., Research Assistant Professor, Departments of Biomedical Engineering, Boston University We have developed computational fragment mapping to identify “hot spot” regions in protein-protein interfaces. The method accounts for protein plasticity, and finds energetically favorable sites for fragment sized probe molecules. Results are presented for protein-protein interaction targets, including interleukin-2, Bcl-xL, MDM2, HPV-11 E2, ZipA, TNF-a, NEMO, and eIF4E. We also discuss methods of finding druggable targets in cancer pathways. 11:10 Induced Fit Modeling with Monte Carlo Techniques: Protein Energy Landscape Exploration Victor Guallar, Ph.D., ICREA Research Professor, Life Science Department, Barcelona Supercomputing Protein energy landscape exploration (PELE) constitutes a remarkable advance over conventional techniques to map protein and protein-ligand dynamics. This method, which combines protein structure prediction techniques with a metropolis algorithm, is capable of describing the all-atom ligand migration pathway and induced fit in approximately 100 hours of CPU. A more recent developments in protein-ligand and protein-protein induced fit will be presented. 11:35 Antagonizing the IAP proteins to Induce Programmed Cell Death in Cancer: A New Therapeutic Approach Utilizing Protein-Protein Interaction Kurt Deshayes, Ph.D., Senior Scientist, Department of Early Discovery Biochemistry, Genentech, Inc. Inhibitor of apoptosis (IAP) proteins are expressed at elevated levels in human malignancies and block cell death in response to diverse stimuli. They are targets for small molecule cancer therapeutics under current clinical development. Results from biophysical, chemical, and molecular biological studies of the mechanism by which binding of small molecule IAP antagonists leads to cancer cell death will be reported. 12:00 pm Target based lead optimization: Sponsored by VLifeSCOPE and SATREA Sudhir A. Kulkarni, Ph.D., Vice President, Discovery Research, VLife Sciences Technologies Pvt. Ltd. VLifeSCOPE is a novel target based lead optimization method where target ligand interactions obtained from scoring function are partitioned into individual residues in the active site and correlated to the activity of molecules. VLifeSCOPE provides information on key residues to be targeted in lead optimization. SATREA is a visualization tool that provides information on regions of exploitation and avoidance for achieving specificity of target of interest with respect to other target in the same family. 12:30 Luncheon Presentations (Sponsorship Opportunities Available) or Lunch on Your Own FRAGMENT-BASED DRUG DESIGN 1:30 Chairperson’s Remarks Roderick Hubbard, Ph.D., Professor, University of York and Vernalis Ltd. 1:35 Practical Concepts in Fragment-to-Lead Optimization Marcel Verdonk, Ph.D., Director, Computational Chemistry and Informatics, Astex Therapeutics Ltd. Fragment-based screening methodologies have become widely used in drug discovery projects. We will present various practical concepts that are used at Astex during the process of fragment prioritization and optimizations. For example, we will discuss the use of Ligand Efficiency and Group Efficiency measures. In addition, a practical approach will be presented to significantly improve docking performance during fragment-to-lead optimization 2:00 Making Decisions in Fragment-Based Discovery Roderick Hubbard, Ph.D., Professor, University of York and Director, Stuctural Sciences, Vernalis Ltd. Fragment-based methods are now well established and generate hits for most targets. A continuing challenge is making the right decisions during the fragment to lead evolution stage – which fragment to evolve based on chemical and target opportunities and how to evolve fragments in the absence of structure. This presentation will discuss the contribution of both computational and experimental methods to address these challenges. 2:30 Applying Integral Equation Sponsored by Theory to Structure Based Design Jean-François Truchon, Ph.D., Research Scientist, Chemical Computing Group Integral equation theories seem attractive for their ability to generate water and solvated fragment density distributions in enzyme active sites. They are much less computationally demanding than Molecular Dynamics and unveil explicit solvent details missing in continuum models such as Poisson-Boltzmann. We compare a particular flavor, namely 3D-RISM/KH, to other methods and examine its usefulness in structure based design and fragment docking. 3:00 Networking Refreshment Break in the Exhibit Hall with Poster Viewing 3:45 A Computational Approach to Fragment-Based Drug Design Charles H. Reynolds, Ph.D., Senior Director, Discovery Technologies, Ansaris We have developed a free energy method for computing the interaction of small molecule fragments with their target proteins. This approach is fast relative to traditional free energy methods and more accurate than traditional modeling methods that only compute interaction energies based on one, or a small number, of configurations. The methodology is ideal for 3 healthtech.com/SBD
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