Molegro Virtual Docker - Technology
Docking Algorithm
Molegro Virtual Docker uses the MolDock docking engine to predict ligand - protein interactions. MolDock is based on a new hybrid search algorithm, called guided differential evolution.
The guided differential evolution algorithm combines the differential evolution (DE) optimization technique with a cavity prediction algorithm which is dynamically used during the docking process.
Differential evolution was introduced by Storn and Price [1] in 1995 and has previously been applied to various optimization problems with great succes. The use of predicted cavities during the search process allows for a fast and accurate identification of potential binding modes.
The MolDock docking engine has been benchmarked and is described in details in MolDock: A New Technique for High-Accuracy Molecular Docking (Journal of Medicinal Chemistry).
| Docking Product | Accuracy |
|---|---|
| Molegro Virtual Docker | 87.0% |
| Glide | 81.8% |
| Surflex | 75.3% |
| FlexX[*] | 57.9% |
Table 1: Accuracy of selected docking programs. A binding mode is regarded as correctly identified if the RMSD (to the native co-crystallized ligand) is less than 2.0Å. Before docking the ligands were energy minimized and randomized and all water molecules were removed from the complex. The dataset consists of the 77 complexes from the Surflex set as defined in Friesner et al. [2]. [*] Based on 76 out of the 77 complexes in the Surflex77 set.
Evaluation Function
The docking scoring function used by the MolDock engine during the docking simulation is based on a "piecewise linear potential" (PLP) [3]. In MolDock, the docking scoring function has been extended with new terms (e.g. hydrogen bond directionality). The docking scoring function makes it possible to quickly evaluate poses during the docking process.
After the docking process has terminated the poses found are reranked using a more complex force-field.
Molegro Virtual Docker is also able to provide a rough estimate of the binding affinity between the ligand and protein (using a combination of energy terms and molecular descriptors calibrated on more than 200 complexes with known binding energies).
More Information
For more information please refer to the included manual in Molegro Virtual Docker 2007, which contains detailed information on the MolDock scoring function and search algorithm.
[1] Storn, R.; Price, K.
Differential Evolution - A Simple And Efficient Adaptive Scheme for Global Optimization over Continuous Spaces.
Tech-report, International Computer Science Institute, Berkley, 1995.
[2] Friesner, R. A.; Banks, J. L.; Murphy, R. B.; Halgren, T. A.
Glide: A New Approach for Rapid Accurate Docking And Scoring. 1. Method And Assessment of Docking Accuracy.
J. Med. Chem. 2004, 47, 1739-1749.
[3] Gehlhaar, D. K.; Verkhivker, G.; Rejto, P. A.; Fogel, D. B.; Fogel, L. J.; Freer, S. T.
Docking Conformationally Flexible Small Molecules Into a Protein Binding Site Through Evolutionary Programming.
Proceedings of the Fourth International Conference on Evolutionary Programming 1995, 615-627.