4:00-5:00 Interactive Break-Out Discussion Groups
Concurrent break-out discussion groups are interactive, guided discussions hosted by a facilitator or set of co-facilitators to discuss some of the more poignant questions facing the industry. Delegates will join a table of interest to them and become an active part of the discussion at hand. It is an informal yet informative format that allows attendees to learn from each other and make some new contacts. To get the most out of this interactive format please come prepared to: share examples from your work, vet some ideas with your peers, be a part of group interrogation and problem solving, and, most importantly, participate in active idea sharing.
TABLE 1: Integration of 3-D and 2-D structural information, for instance the ones from the PDB with those from PubChem
Host: Talapady Bhat, Ph.D., Project Leader, Biochemical Science, NIST
• The need (if any) for the Integration of 2-D and 3-D small molecule structural data
• What are current approaches and break through technologies and what are their limitations
• Semantic Web Concepts and rule-based structural ontologies for the integration of 2-D and
3-D structural data
TABLE 2: Use of Structure-Based Drug Design to Address Drug Resistance
Hosts: Juswinder Singh, Ph.D., Founder and CSO, Avila Therapeutics, Inc.
David Dalgarno, Ph.D., Vice President, Research Technologies, ARIAD Pharmaceuticals, Inc.
• How useful is SBDD in addressing drug resistance mutations
• What are the strengths and weaknesses of the current computational approaches
• Do we see any breakthrough technologies emerging in the near-term
TABLE 3: Computational Directions for Structure-Based Lead Optimization
Host: W. Patrick Walters, Ph.D., Senior Research Fellow, Group Head, Computational Drug Discovery Technologies, Vertex Pharmaceuticals, Inc.
• What constitutes a reliable validation of structure-based lead optimization tools, do real validations exist in the literature?
• Is docking and scoring a viable solution for lead optimization, how well do empirical scoring functions predict binding affinity?
• Can we use intermediate computational techniques such as MMPBSA/MMGBSA to drive a lead optimization program?
• Are more rigorous techniques such as FEP “ready for prime time”, where do improvements need to be made?
TABLE 4: Do We Get the Most Out of the Structural information in the PDB? Tips and Lessons Learned
Host: José Duca, Ph.D., Senior Principal Scientist, 3D - Drug Design Department, Merck Research Laboratories
TABLE 5: Why Aren’t We Designing the Perfect Drug as Soon as We Have a Crystal Structure?
Hosts: Rama Kondru, Ph.D., Principal Research Scientist, Hoffmann-La Roche
Ms. Elizabeth Sourial, Director, Scientific Services, Chemical Computing Group Inc.
• What are the current limitations of structure based design?
• How do we handle protein flexibility?
• What are the key protein-ligand interactions that we do not understand – like long range electrostatics?
• What are the new methods that can change the landscape in the future, if any?
TABLE 6: The Role of Structural Waters in Drug Design
Host: Woody Sherman, Ph.D., Vice President, Applications Science, Schrodinger, Inc.
• When is it best to bridge versus displace a water molecule?
• Should certain structural water molecules be avoided?
• Can activity cliffs be explained by waters?
TABLE 7: Matching SBDD Approaches with Targets: Do We Know How to Optimize Our Protocols?
Host: Sid Topiol, Ph.D., Head of US Computational Chemistry and Structural Investigations, Lundbeck Research, USA
• With numerous computational options (e.g., protein and/or ligand flexibility, homology modeling, energetic approximations, solvation effects) and target considerations
(e.g., X-ray resolution, multiple states), are we equipped to identify the best protocols?
• What role, if any, should be played by ligand-based methods in conjunction with SBDD?
• Experimental insights from protein/ligand interactions; are ligand methods (MedChem) or protein methods (X-ray, mutation) more informative?
TABLE 8:The Issue of Protein Flexibility in the Structure-Based Drug Design
Host: Jie Zheng, Ph.D., Associate Member, Department of Structural Biology, St. Jude Children’s Research Hospital
TABLE 9: Getting Around Scoring
Hosts: Matthias Rarey, Ph.D., Professor & Managing Director, ZBH Center for Bioinformatics, University of Hamburg
Chris Williams, Ph.D., Principal Scientist, Chemical Computing Group (CCG)
The development of accurate protein-ligand scoring functions is the bottleneck for structure-based drug design over the past 20 years. In contrast of thinking how to improve
existing methods by another few percent, the focus of the discussion should be how to circumvent this difficult question:
• Are target-based scoring methods a solution?
• Can we develop classification schemes (binder - non binder), even if we are not able to make a good energy estimate?
• Is ranking simpler than scoring and if yes, can we make use of this?