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[News]
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Can we trust docking results?
Sept 2010 IBM Systems and Technology Group releases a white paper with eHiTS and Cell
Oct 2008
EPA's ToxCastTM project will use SimBioSys'
eHiTS as docking engine
Nov,
2007
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[Events]
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| 243rd ACS
Mar 25-29, 2012
San Diego, CA
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>> more
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WEDNESDAY 14 OCTOBER 2009: Structure-Based Drug Design
Chaired
by Natasja Brooijmans (Wyeth)
Improving Molecular Docking Through a
Tunable Scoring Function
Zsolt Zsoldos , Orr Ravitz, Danni Harris
and Aniko
Simon
SimBioSys,
Inc., 135 Queen's Plate Dr., Unit 520, Toronto, ON, M9W 6V1,
Canada
Abstract:
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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. Acetylcholine binding protein,
beta secretase and other systems of pharmaceutical interest will be
used to demonstrate the improvement in docking performance in terms
of score discrimination between low and high RMSD poses, of
enrichment levels in screening runs, and of correlation between score
and binding affinity. Guidelines for choosing the optimal data set
for training will be discussed.
view: talk
view: poster
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