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Co-Located with:

Next-Gen Kinase Inhibitors 

Corporate Sponsors:

Chemical Computing GroupNEW logo 





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Lead Sponsoring Publications:


Science AAAS 

The Scientist 


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Sponsoring Publications:

chemical biology 

Insight Pharma Reports 



Thursday, June 7



7:30 AM Morning Coffee

8:00 Chairperson’s Remarks

Woody Sherman, Ph.D., Vice President, Applications Science, Schrodinger, Inc.

8:10 Free Energy Driven Geometrical Simulation of Protein Dynamics

Donald JacobsDonald Jacobs, Ph.D., Associate Professor, Physics and Optical Science, UNC Charlotte

Graph-rigidity plays an important role in (i) quantifying protein flexibility, (ii) exploring conformational dynamics using geometrical simulation (GS) and (iii) calculating free energy using a Distance Constraint Model (DCM). While GS explores accessible geometries for a fixed constraint topology, the DCM generates an ensemble of constraint topologies for fixed geometry. Combining GS with the DCM yields a novel Monte Carlo method to efficiently explore conformational states along the free energy landscape of a protein, and this exploration can be directed.

8:40 Toward Antibody Drug Development Assisted by Molecular Dynamics Simulations

Takefumi YamashitaTakefumi Yamashita, Ph.D., Project Associate Professor, Laboratory for System Biology and Medicine, Research Center for Advanced Science and Technology, University of Tokyo

In order to develop an antibody drug, achieving high affinity through mutation is one of the most essential steps. I have been working on mutant antibodies specific for Roundabout homolog 1 (ROBO1), which is known as a hepatocellular carcinoma antigen, by utilizing molecular dynamics simulation techniques including a newly developed method to evaluate the absolute binding free energy. In my talk, I will discuss several key features of the single mutation of the antibody. In collaboration with experimentalists, we found that even the single mutation can affect the interface structure globally.

9:10 Making Docking/Scoring Calculations More Accurate via Error Analysis

Kenneth MerzKenneth Merz, Jr., Ph.D., Professor of Chemistry, Quantum Theory Project, University of Florida Gainesville

Docking calculations are a mainstay of structure-based drug design and this talk addresses the central question regarding how potential function errors affect the (un)successful outcome of a docking effort. We analyze and estimate the magnitude of potential function error and demonstrate how to use this knowledge to improve the outcome of a docking exercise.

Chemical Computing Group-DO NOT USE9:40 Rationalization and Visualization of Nonbonded Interactions

Chris Williams, Ph.D., Principal Scientist, Chemical Computing Group

The visualization and assessment of the quality of non-bonded interactions in molecular modeling application is an important tool in structure-based drug desgin. Often, purely geo-metric criteria are used to score non-bonded interactions (such as hydrogen bonds). Such methods poorly represent the underlying chemistry of the interacting species. In this work, we present techniques based on Extended Hueckel Theory for scoring hydrogen bonds and make some generalizations for halogen bonds and sulfur-oxygen interactions.

10:10 Coffee Break in the Exhibit Hall with Poster Viewing


10:40 Exploring the S1P1 Ligand Binding Pocket through Structural Analysis

Michael Hanson, Ph.D., Associate Director, Structural Biology, Receptos, Inc.

A structural view at 2.8 Å resolution of a lipid mediated GPCR reveals an access channel adjacent to the plasma membrane and provides supporting evidence for a volume triggered activation mechanism.  This structure, along with mutagenesis, agonist structure-activity relationship data and modeling, provides a detailed view of the molecular recognition and hydrophobic volume triggering that activates S1P1 resulting in the modulation of immune and stromal cell responses, which are therapeutically important for human diseases ranging from multiple sclerosis to influenza.

11:10 Binding Affinity Prediction for Drugs and Receptors Forming Multiple Species by Ionization and Tautomerism

Stefan BalazStefan Balaz, Albany College of Pharmacy and Health Sciences, Vermont Campus

Treatment of ionization and tautomerism of ligands and receptors is one of the unresolved issues in structure-based prediction of binding affinities.  Our solution utilizes the thermodynamic master equation, expressing the experimentally observed association constant as the sum of products, each valid for a specific ligand-receptor species pair, consisting of the association microconstant and the fractions of the involved ligand and receptor species.  The microconstants are characterized by structure-based simulations, which are run for individual species pairs.  The concept will be illustrated for ligand-based CoMFA approach and receptor-based QM/MM linear response approach.

OpenEye_Vertical11:40 POSIT - Pose Prediction with Confidence - Ligand and Structure based Flexible DockingBrian Kelley Brian Kelley, OpenEye Scientific SoftwareTraditional structure based pose-prediction has not been very accurate in reproducing crystallographic poses.  This can be rectified by using all of the information present in a crystal structure - both ligand and protein structure.  POSIT is a flexible docking technique that uses both the known protein and ligand structure to predict poses.  Furthermore, using this information generates a probability that the predicted pose is indeed correct.  This has far reaching implications for real world lead optimization scenarios including measuring confidence but also the ability to select the existing crystal structure that best predicts the docked pose for a given molecule.

12:10 PM Luncheon Presentation (Opportunity Available) or Lunch on Your Own 



1:30 Chairperson’s Remarks

Christopher W. Murray, Ph.D., Vice President of Discovery Technology, Astex Pharmaceuticals

1:40 The Use of Fragment-Based Drug Discovery to Exploit Alternative Binding Sites on Proteins

Christopher MurrayChristopher W. Murray, Ph.D., Vice President of Discovery Technology, Astex Pharmaceuticals

Fragment-based drug discovery (FBDD) allows for the collection of large numbers of crystal structures co-soaked with fragments. We will describe a computational approach that searches the protein surface to detect binding at alternative sites away from the known binding sites of the protein. Several examples will be given including the application of FBDD to the discovery of molecules that bind to a novel allosteric site on the full length NS3 protein from the Hepatitis C Virus.

2:10 Hot Spot Analysis for Driving the Development of Hits into Leads in Fragment Based Drug Discovery

Sandor Vajda, Ph.D., Professor, Biomedical Engineering and Chemistry, Boston University

Protein mapping, a computational method developed to find binding hot spots and implemented as the FTMap server, provides information that complements fragment screening results and can drive the evolution of core fragments into larger leads with a minimal loss or, in some cases, even a gain in ligand efficiency. We consider a variety of drug targets and show that the main hot spot identified by FTMap binds the core compound found by fragment screening. The most useful information is provided by the neighboring secondary hot spots, indicating the regions where the core can be extended to increase its affinity. To quantify this information, we calculate the density of probes from mapping, which describes the binding propensity at each point, and show that the change in the correlation between a ligand position and the probe density upon extending or repositioning the core moiety predicts the expected change in ligand efficiency.

CRESSET 2:40 A Fast Computational Method for Fragment Growing and Joining Using Molecular FieldsRae Lawrence, Technical Sales Manager, Cresset BioMolecular Discovery LtdThe use of fragments in medicinal chemistry is a powerful alternative technique for drug discovery.  Our field based modelling approach provides fine detail irrespective of the size of molecule.  We describe the use of sparkV10 in a rapid virtual fragment growth and joining exercise to facilitate the design of potential novel and selective P38 kinase inhibitors. 

2:55 Sponsored Presentation (Opportunity Available) 

3:10 Refreshment Break in the Exhibit Hall with Poster Viewing

3:40 Decisions in Fragment Progression – Can Thermodynamics or Kinetics Help?

Rod HubbardRod Hubbard, Ph.D., Director, Structural Sciences, Vernalis Ltd.

4:10 Drug Design and Repositioning Using Multiple Fragment Simultaneous Docking

Chenglong Li, Ph.D., Associate Professor, Medicinal Chemistry, The Ohio State University

We use multiple fragment simultaneous docking to find the optimal fragment combinations binding to the most important target “hot spots,” followed by tethering to generate virtual template compounds. The fragments can be linked to generate novel leads, and we designed two novel lead inhibitors based on one of the lead templates. Existing drugs can be repositioned for the new targets via the new lead templates. Case studies will be presented.

4:40 High-Throughput Synchrotron Crystallography for Fragment-Based, Structure-Guided Drug Discovery

Stephen R. Wasserman, Ph.D., Director, LRL Collaborative Access Team; Senior Research Fellow, Translational Science & Technologies, Eli Lilly and Company Advanced Photon Source Argonne National Laboratory

5:10-6:30  Welcome Reception in the Exhibit Hall with Poster Viewing  

PubChem Mining - From Small Molecule to Structures and Bioactivity *


Jun (Luke) Huan, Ph.D., Associate Professor, Electrical Engineering and Computer Science Department, University of Kansas

In this short course, the presenter will review the knowledge discovery and management needs in the drug discovery process. One part of the talk will focus on an introduction to PubChem, a public repository for small molecule structures and bioactivity data, where several components facilitating data mining of biological assays test results, including data organization, search of chemicals and analysis for assay development will be covered. On the second part, latest computing and modeling methodology development, primarily those from data mining and machine learning will be overviewed.

The primary targeted audience of the tutorial is cheminformatics researchers and practitioners who are interested in developing or applying advanced computing techniques to support knowledge discovery in drug discovery and drug development programs. It may also help drug development and drug post-market safety monitoring. General knowledge of cheminformatics and statistics is assumed.

*Separate registration is required to attend the dinner short course.