The Montreal Computer-Aided Drug Design (MCADD) organizing committee is annoucing the Fall 2011 seminar will feature Zsolt Zsoldos of SimBioSys Inc. (http://www.simbiosys.ca/) . He will be presenting his talk entitled “Automated tuning of eHiTS scoring weights specific to protein families”. The seminar will be October 5th at 3pm in room 501 of the Goodman Cancer Center of McGill University. This seminar will be followed by a wine and cheese reception afterwards. We look forward to seeing you there and please feel free to forward this email to anyone interested in attending the seminar and/or joining the MCADD Group (students and post-docs are welcome).
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Chair, 4th MCADD Organizing Committee
Organizing Committee members:
Pierre Bonneau, Boehringer Ingelheim (Canada) Ltd.
Araz Jakalian, Boehringer Ingelheim (Canada) Ltd.
Enrico O. Purisima, NRC-BRI
Constatin Yannopolous, Vertex Canada
Date: October 5th, 2011
Location: Room 501 (Karp Conference Room) Goodman Cancer Center, McGill University, 1160 Pine Ave. West, Montreal, Quebec
Time: 3:00pm - Seminar: /Automated tuning of eHiTS scoring weights specific to protein families/, Zsolt Zsoldos, SimBioSys Inc. Toronto, Canada
4:00pm - Cocktail/Wine
The molecular docking paradigm, has thus far failed to produce a generic approach that would deliver accurate pose prediction capabilities, and reliable rank-ordering of conformations and ligands consistently for any biological system of interest. This reality, which has been addressed by numerous methodology papers and comparative studies, has been largely attributed to the inability of scoring functions to capture different chemical interaction types at a uniform level of accuracy. Several studies attempted to develop guidelines for choosing the most suitable docking and scoring method for a specific problem based on protein family classification of the target, dominant interactions, and other properties of the studied system. Consensus techniques, on the other hand, try to synergistically integrate information from multiple sources assuming agreement between different methods is indicative of more accurate values. Both approaches, however, have shown only limited success in improving binding mode and activity prediction capabilities.
An alternative solution, and arguably a more rigorous one, would be to tailor the scoring function for the system of interest. eHiTS uses a novel scoring method consisting of a statistical knowledge base focused on interacting surface points and physical terms combined with an adaptive parameter scheme. This approach offers users the capability to fine-tune the scoring function using their data and thus incorporate their full body of knowledge in a systematic and automatic fashion. In many realistic drug discovery scenarios, structural and ligand-activity information is sufficient in a statistical sense to adjust a limited set of parameters representing the relative weights of the various terms in the eHiTS scoring function. During tuning, receptor targets are clustered according to the chemical and shape similarity of the active site, and weight sets are optimized for each family. Pharmacophore constraint descriptions are thus generated automatically from the recurring interaction patterns observed in a specific active set profile. These constraints can be used for constrained docking or pharmacophore-enhanced scoring schemes.
In this talk, an overview of the eHiTS’ tuning utility will be given, outlining the underlying methodology. Results will be presented showing the enhancements achieved by the tuning process on docking and scoring performance.