[Dockdev] Docking and Scoring algorithms
DAVID M ROGERS
rogersdd at email.uc.edu
Wed Feb 23 11:02:12 PST 2005
It seems to me that there are a multitude of docking
algorithms out there, all of which have individual quirks
(Kitchen et. al.), and none of which work perfectly for every
type of interaction (since simplifying a thermodynamic binding
potential energy calculation must obviously make assumptions).
Dr. Kuntz recently wrote his own review of docking
methodoligies (Brooijmans & Kuntz).
It seems clear in these reviews that the most challenging
task of the docking function is to reproduce correct binding
energies. Even in the MD community, it has been difficult to
create force-fields that do this task, and P-Chemists are
working toward quantum corrections to these methods (what
seems like the opposite direction).
I have recently tried scoring several receptor-ligand
complexes (those that worked from the Gold validation set)
with different scoring functions, and found that the average
correlation (R^2) between different scoring functions is about
0.3, that is 30% similarity. Dock5, as it is installed here,
however, gave scores with a correlation of about 0.02, right
around the limit of statistical validity for our dataset (~73
I have also tried changing the random number generation
seed, and found that (with the parameters included in the
methotrexate example) Dock's energy scores vary by +/- 0.5,
which (I believe) is acceptable.
Anyway, I am highly skeptical of Dock5's scoring algorithm,
and uncertain about publishing any work based upon it until I
have been able to reproduce a successful screening. This is,
of course, difficult to do since assembling a list of relevant
compounds with known binding affinities in the same conditions
Brooijmans, N. & Kuntz, I. D. (2003) Annu. Rev. Biophys.
Biomol. Struct. 32, 335-373.
Kitchen, D. B., Helene, D., Furr, J. R., Bajorath, J. (2004)
Nature Reviews Drug Discovery. 3, 935
Gold Validation Set:
~ David Rogers
Department of Chemistry
University of Cincinnati
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