David S. Goodsell
Rutgers University
310 Papers
2.3K Citations
David S. Goodsell is an academic researcher from Rutgers University. The author has contributed to research in topics: Computer science & Protein Data Bank. The author has an hindex of 58, co-authored 265 publications. Previous affiliations of David S. Goodsell include United States Naval Research Laboratory & Scripps Research Institute.
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Papers
AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility
Garrett M. Morris,Ruth Huey,William Lindstrom,Michel F. Sanner,Richard K. Belew,David S. Goodsell,Arthur J. Olson +6 more
TL;DR: AutoDock4 incorporates limited flexibility in the receptor and its utility in analysis of covalently bound ligands is reported, using both a grid‐based docking method and a modification of the flexible sidechain technique.
21.1K
Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function
Garrett M. Morris,David S. Goodsell,Robert Scott Halliday,Ruth Huey,William E. Hart,Richard K. Belew,Arthur J. Olson +6 more
TL;DR: It is shown that both the traditional and Lamarckian genetic algorithms can handle ligands with more degrees of freedom than the simulated annealing method used in earlier versions of AUTODOCK, and that the Lamarckia genetic algorithm is the most efficient, reliable, and successful of the three.
A semiempirical free energy force field with charge-based desolvation.
TL;DR: The authors describe the development and testing of a semiempirical free energy force field for use in AutoDock4 and similar grid‐based docking methods based on a comprehensive thermodynamic model that allows incorporation of intramolecular energies into the predicted free energy of binding.
2K
Computational protein–ligand docking and virtual drug screening with the AutoDock suite
TL;DR: This protocol covers the docking and virtual screening methods provided by the AutoDock suite of programs, including a basic docking of a drug molecule with an anticancer target, a virtual screen of this target with a small ligand library, docking with selective receptor flexibility, active site prediction and docking with explicit hydration.
Software News and Update A Semiempirical Free Energy Force Field with Charge-Based Desolvation
Ruth Huey,Garrett M. Morris,Arthur J. Olson,David S. Goodsell +3 more
- 01 Jan 2007
TL;DR: In this article, a semi-empirical free energy force field for use in AutoDock4 and similar grid-based docking methods is presented, based on a comprehensive thermodynamic model that allows incorporation of intramolecular energies into the predicted free energy of binding.