A semiempirical free energy force field with charge‐based desolvation

By Ruth Huey, Garrett M. Morris, Arthur J. Olson, David S. Goodsell. Journal of Computational Chemistry, 2007

2,152 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Materials Chemistry, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/96ea415081cb294d61bac31f4746a01a80a3516e

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Citations in the corpus

Accelerating AutoDock4 with GPUs and Gradient-Based Local Search (2019, methodology): “In AUTODOCK, molecular interactions are modeled by a scoring function f that quantifies the free energy of a given binding pose (21):”
Is It Reliable to Take the Molecular Docking Top Scoring Position as the Best Solution without Considering Available Structural Data? (2018, methodology): “AutoDock uses a semi-empirical free energy force field to predict binding energies or ligands to macromolecular targets and Lamarckian genetic algorithm (GA) to search for docking solutions [69].”
DARC 2.0: Improved Docking and Virtual Screening at Protein Interaction Sites (2015, methodology): “Broadly speaking, this is strategy utilized in both AutoDock4 (through AutoGrid) [33, 43] and the DOCK suite [34, 44].”
Application of the PM6 semi-empirical method to modeling proteins enhances docking accuracy of AutoDock (2009, methodology): “In AutoDock 4 energy scoring function the calculation of pair-wise atomic terms includes evaluations for different secondary interactions, dispersion/repulsion, hydrogen bonding, electrostatics, and desolvation [14].”
Evaluation of AlphaFold2 structures as docking targets (2022, result): “This is comparable to a previously published performance of AutoDock 4 of 45% (Huey et al., 2007).”
Key Topics in Molecular Docking for Drug Design (2019, methodology): “AutoDock4 Lamarckian Genetic Algorithm, Genetic Algorithm or Simulated Annealing Semiempirical Free (GNU License) Morris, 2009; Huey, 2007 [31,32]”
Protein-Ligand Interaction Graphs: Learning from Ligand-Shaped 3D Interaction Graphs to Improve Binding Affinity Prediction (2022, methodology): “They are used in popular docking software such as AutoDock4 ([2, 3]), AutoDock Vina ([4]) or GOLD ([5]) to score 3D ligand poses.”
AutoDock-GIST: Incorporating Thermodynamics of Active-Site Water into Scoring Function for Accurate Protein-Ligand Docking (2016, background): “Since the desolvation term Δ is based on the continuous solvation model and represents a penalty of binding free energy [49], we assumed that the displacing gain of unfavorable water ∆ does not conflict with Δ .”
GOMoDo: A GPCRs Online Modeling and Docking Webserver (2013, background): “(i) VINA [34] is a fast, multithreaded and accurate rewriting of AutoDock that often outperforms classical AutoDock both in speed and quality [37,38].”