Original paper

Journal of Computer-Aided Molecular Design

, Volume 20, Issue 10, pp 601-619

First online:

Development and validation of a modular, extensible docking program: DOCK 5

  • Demetri T. MoustakasAffiliated withJoint Graduate Program in Bioengineering, University of California, San FranciscoJoint Graduate Program in Bioengineering, University of California, Berkeley
  • , P. Therese LangAffiliated withGraduate Program in Chemistry and Chemical Biology, University of California, San Francisco
  • , Scott PeggAffiliated withDepartment of Pharmaceutical Chemistry, University of California, San Francisco
  • , Eric PettersenAffiliated withDepartment of Pharmaceutical Chemistry, University of California, San Francisco
  • , Irwin D. KuntzAffiliated withDepartment of Pharmaceutical Chemistry, University of California, San Francisco Email author 
  • , Natasja BrooijmansAffiliated withGraduate Program in Chemistry and Chemical Biology, University of California, San Francisco
  • , Robert C. RizzoAffiliated withDepartment of Applied Mathematics and Statistics, Stony Brook University

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Abstract

We report on the development and validation of a new version of DOCK. The algorithm has been rewritten in a modular format, which allows for easy implementation of new scoring functions, sampling methods and analysis tools. We validated the sampling algorithm with a test set of 114 protein–ligand complexes. Using an optimized parameter set, we are able to reproduce the crystal ligand pose to within 2 Å of the crystal structure for 79% of the test cases using our rigid ligand docking algorithm with an average run time of 1 min per complex and for 72% of the test cases using our flexible ligand docking algorithm with an average run time of 5 min per complex. Finally, we perform an analysis of the docking failures in the test set and determine that the sampling algorithm is generally sufficient for the binding pose prediction problem for up to 7 rotatable bonds; i.e. 99% of the rigid ligand docking cases and 95% of the flexible ligand docking cases are sampled successfully. We point out that success rates could be improved through more advanced modeling of the receptor prior to docking and through improvement of the force field parameters, particularly for structures containing metal-based cofactors.

Keywords

Automated docking Scoring functions Structure-based drug design Flexible docking Binding mode prediction Incremental construction Validation