Resource For Structure-Based Computational Drug Discovery And Design (RSCD3)

Building on several decades of work with the AutoDock Suite, the Resource for Structure-based Computational Drug Discovery and Design (RSCD3) aims to provide a user-facing infrastructure for novice and expert users to easily apply a diverse, modern toolset of methods to drug discovery and design applications.

RSCD3 is directed by Dr. Stefano Forli, PI of the Forli lab at Scripps Research.

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Getting Started

Beginners’ guides for molecular modeling, docking, and virtual screening.

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AutoDock

Ongoing projects and new updates on AutoDock from RSCD3, and legacy programs from MGL.

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Resources

Links to software, websites, databases and other useful resources for virtual screening.

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AutoDock-GPU

Current version

Why AutoDock-GPU?

AutoDock-GPU is the fastest full-service docking engine available at RSD3. It is a version of AutoDock4.2.6 accelerated by OpenCL and Cuda. It leverages the embarrassingly-parallelizable Lamarckian Genetic Algorithm of AutoDock by processing ligand-receptor poses in parallel over multiple compute units.

Cite AutoDock-GPU...

Santos-Martins, D., et al. (2021). “Accelerating AutoDock4 with GPUs and Gradient-Based Local Search.” Journal of Chemical Theory and Computation 17(2): 1060-1073. DOI: 10.1021/acs.jctc.0c01006

AutoDock-Vina

Current version

v1.1.2 (Obsolete)

Why AutoDock-Vina?

AutoDock-Vina is one of the fastest and most widely used open-source docking engines. It is a turnkey computational docking program that is based on a simple scoring function and rapid gradient-optimization conformational search.

Cite AutoDock-Vina...

Trott, O. and A. J. Olson (2010). “AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading.” J Comput Chem 31(2): 455-461. DOI: 10.1002/jcc.21334

Eberhardt, J., et al. (2021). “AutoDock Vina 1.2.0: New Docking Methods, Expanded Force Field, and Python Bindings.” Journal of Chemical Information and Modeling 61(8): 3891-3898. DOI: 10.1021/acs.jcim.1c00203

AutoDock FR &

AutoDock CrankPep

ADCP Latest

ADFR Current

Why AutoDock FR?

AutoDockFR (or ADFR in short) is a protein-ligand docking program designed specifically, to include selective receptor flexibility and also supports covalent docking.Its custom Genetic Algorithm enables docking ligands with more rotatable bonds than AutoDock4.

Cite AutoDock FR...

Ravindranath, P. A., et al. (2015). “AutoDockFR: Advances in Protein-Ligand Docking with Explicitly Specified Binding Site Flexibility.” PLOS Computational Biology 11(12): e1004586. DOI: 10.1371/journal.pcbi.1004586

Why AutoDock CrankPep?

AutoDock CrankPep or ADCP is an AutoDock docking engine specialized for docking peptides. It combines technology form the protein folding filed with an efficient representation of a rigid receptor as affinity grids to fold the peptide in the context of the energy landscape created by the receptor. It has been show to successfully re-dock peptides with up to 20 amino acids in length.

Cite AutoDock CrankPep...

Zhang, Y. and M. F. Sanner (2019). “AutoDock CrankPep: combining folding and docking to predict protein–peptide complexes.” Bioinformatics 35(24): 5121-5127. DOI: 10.1093/bioinformatics/btz459

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AutoDock Cookbook

Presented collaboratively by RSCD3, the AutoDock Cookbook provides practical examples of performing computational experiments and common tasks in drug discovery and design.

For Beginners

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News & Events

RSCD3 is extending its support for the community through documentation and self-taught tutorials as well as presenting workshops at national conferences, community discussion groups, and expert guidance for showcasing more recent and advanced protocols.

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This resource is funded by a National Institute of General Medical Sciences grant: R24GM145962.