![]() ![]() It also incorporates a new charge-based desolvation method that uses a typical set of atom types and charges. This is performed by evaluating energies for both the bound and unbound states. ![]() The force field is based on a comprehensive thermodynamic model that allows incorporation of intramolecular energies into the predicted free energy of binding. Development and testing of the force field has been described elsewhere 11. A simulated annealing search method and a traditional genetic algorithm search are also available in AutoDock4.ĪutoDock4 uses a semiempirical free energy force field to predict binding free energies of small molecules to macromolecular targets. The “Lamarckian” aspect is an added feature that allows individual conformations to search their local conformational space, finding local minima, and then pass this information to later generations. A population of trial conformations is created, and then in successive generations these individuals mutate, exchange conformational parameters, and compete in a manner analogous to biological evolution, ultimately selecting individuals with lowest binding energy. The primary method for conformational searching is a Lamarckian genetic algorithm, described fully in Morris et al. This grid of energies may then be used as a lookup table during the docking simulation. Then, a probe atom is sequentially placed at each grid point, the interaction energy between the probe and the target is computed, and the value is stored in the grid. In this method, the target protein is embedded in a grid. In order to allow searching of the large conformational space available to a ligand around a protein, AutoDock uses a grid-based method to allow rapid evaluation of the binding energy of trial conformations. Since its release in 1990 10, AutoDock has proven to be an effective tool capable of quickly and accurately predicting bound conformations and binding energies of ligands with macromolecular targets 9, 11 – 14. This capability also provides an effective method for analysis of covalently-attached ligands. The new version of AutoDock described here-AutoDock4-incorporates explicit conformational modeling of specified sidechains in the receptor to address this problem. The remaining half show significant motion of the receptor upon binding, and thus have required a more sophisticated model of motion in the receptor, typically performed outside of AutoDock3. In our hands, AutoDock3 has proven to be effective in roughly half of complexes that we have studied. AutoDock combines an empirical free energy force field with a Lamarckian Genetic Algorithm, providing fast prediction of bound conformations with predicted free energies of association 9. Dozens of effective methods are available, incorporating different trade-offs in molecular representation, energy evaluation, and conformational sampling to provide predictions with a reasonable computational effort 1 – 8. Automated docking is widely used for prediction of biomolecular complexes in structure/function analysis and in molecular design. ![]()
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