Journal of Computer-Aided Molecular Design

, Volume 26, Issue 6, pp 687–699

Surflex-Dock: Docking benchmarks and real-world application


DOI: 10.1007/s10822-011-9533-y

Cite this article as:
Spitzer, R. & Jain, A.N. J Comput Aided Mol Des (2012) 26: 687. doi:10.1007/s10822-011-9533-y


Benchmarks for molecular docking have historically focused on re-docking the cognate ligand of a well-determined protein–ligand complex to measure geometric pose prediction accuracy, and measurement of virtual screening performance has been focused on increasingly large and diverse sets of target protein structures, cognate ligands, and various types of decoy sets. Here, pose prediction is reported on the Astex Diverse set of 85 protein ligand complexes, and virtual screening performance is reported on the DUD set of 40 protein targets. In both cases, prepared structures of targets and ligands were provided by symposium organizers. The re-prepared data sets yielded results not significantly different than previous reports of Surflex-Dock on the two benchmarks. Minor changes to protein coordinates resulting from complex pre-optimization had large effects on observed performance, highlighting the limitations of cognate ligand re-docking for pose prediction assessment. Docking protocols developed for cross-docking, which address protein flexibility and produce discrete families of predicted poses, produced substantially better performance for pose prediction. Performance on virtual screening performance was shown to benefit by employing and combining multiple screening methods: docking, 2D molecular similarity, and 3D molecular similarity. In addition, use of multiple protein conformations significantly improved screening enrichment.


Docking Benchmarking Virtual screening Pose prediction Surflex-Dock Surflex-Sim Protein flexibility Cross-docking Cognate-docking Pocket adaptation 

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.Deparment of Bioengineering and Therapeutic Sciences, Helen Diller Family Comprehensive Cancer CenterUniversity of California, San FranciscoSan FranciscoUSA
  2. 2.University of California, San FranciscoSan FranciscoUSA