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J Comput Aided Mol Des. 2012 May;26(5):497-503. doi: 10.1007/s10822-011-9521-2. Epub 2011 Dec 21.

The DINGO dataset: a comprehensive set of data for the SAMPL challenge.

Author information

1
CSIRO Division of Materials, Science and Engineering, 343 Royal Parade, Parkville, VIC 3052, Australia.

Abstract

Part of the latest SAMPL challenge was to predict how a small fragment library of 500 commercially available compounds would bind to a protein target. In order to assess the modellers' work, a reasonably comprehensive set of data was collected using a number of techniques. These included surface plasmon resonance, isothermal titration calorimetry, protein crystallization and protein crystallography. Using these techniques we could determine the kinetics of fragment binding, the energy of binding, how this affects the ability of the target to crystallize, and when the fragment did bind, the pose or orientation of binding. Both the final data set and all of the raw images have been made available to the community for scrutiny and further work. This overview sets out to give the parameters of the experiments done and what might be done differently for future studies.

PMID:
22187139
PMCID:
PMC3382646
DOI:
10.1007/s10822-011-9521-2
[Indexed for MEDLINE]
Free PMC Article

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