Computational protein–ligand docking and virtual drug screening with the AutoDock suite
TLDR
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.Abstract:
Computational docking can be used to predict bound conformations and free energies of binding for small-molecule ligands to macromolecular targets. Docking is widely used for the study of biomolecular interactions and mechanisms, and it is applied to structure-based drug design. The methods are fast enough to allow virtual screening of ligand libraries containing tens of thousands of compounds. 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. The entire protocol will require ∼5 h.read more
Citations
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Journal ArticleDOI
AutoDock Vina 1.2.0: New Docking Methods, Expanded Force Field, and Python Bindings.
TL;DR: This work implemented Python bindings to facilitate scripting and the development of docking workflows in AutoDock Vina 1.2.0, an effort toward the unification of the features of the autoDock4 and AutoD Dock Vina docking engines.
Journal ArticleDOI
Natural product-derived phytochemicals as potential agents against coronaviruses: A review.
Janice S. Mani,Joel B. Johnson,Jason C. Steel,Daniel A. Broszczak,Paul M. Neilsen,Kerry B. Walsh,Mani Naiker +6 more
TL;DR: It was noted that the most promising small molecules identified as coronavirus inhibitors contained a conjugated fused ring structure with the majority being classified as being polyphenols.
Journal ArticleDOI
A Review on Applications of Computational Methods in Drug Screening and Design
Xiaoqian Lin,Xiu Li,Xubo Lin +2 more
TL;DR: Roles of multiscale biomolecular simulations in identifying drug binding sites on the target macromolecule and elucidating drug action mechanisms are discussed and virtual screening methods as well as structure- and ligand-based classical/de novo drug design are introduced and discussed.
Journal ArticleDOI
Autodock Vina Adopts More Accurate Binding Poses but Autodock4 Forms Better Binding Affinity.
Nguyen Thanh Nguyen,Trung Hai Nguyen,T. Ngoc Han Pham,Nguyen Truong Huy,Mai Van Bay,Minh Quan Pham,Pham Cam Nam,Van V. Vu,Son Tung Ngo +8 more
TL;DR: The binding pose and affinity between a ligand to an enzyme are very important pieces of information for computer-aided drug design and it is found that the Vina approach converges much faster than AD4 one, however, interestingly, AD4 shows a better performance than Vina over 21 considered targets, whereas Vina protocol is better thanAD4 package for 10 other targets.
Journal ArticleDOI
Key Topics in Molecular Docking for Drug Design.
Pedro Henrique Monteiro Torres,Ana Carolina Rennó Sodero,Paula Jofily,Floriano Paes Silva-Jr +3 more
TL;DR: This review presents an overview of the method and attempts to summarise recent developments regarding four main aspects of molecular docking approaches: (i) the available benchmarking sets, highlighting their advantages and caveats, (ii) the advances in consensus methods, (iii) recent algorithms and applications using fragment-based approaches, and (iv) the use of machine learning algorithms in molecular docking.
References
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Journal ArticleDOI
AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading
Oleg Trott,Arthur J. Olson +1 more
TL;DR: AutoDock Vina achieves an approximately two orders of magnitude speed‐up compared with the molecular docking software previously developed in the lab, while also significantly improving the accuracy of the binding mode predictions, judging by tests on the training set used in AutoDock 4 development.
Journal ArticleDOI
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.
Journal ArticleDOI
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.
Journal ArticleDOI
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.
Software News and Update A Semiempirical Free Energy Force Field with Charge-Based Desolvation
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.
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