tinyIFD: A High-Throughput Binding Pose Refinement Workflow Through Induced-Fit Ligand Docking

Hsu, Darren J.; Davidson, Russell B.; Sedova, Ada; Glaser, Jens

doi:10.1021/acs.jcim.2c01530

tinyIFD: A High-Throughput Binding Pose Refinement Workflow Through Induced-Fit Ligand Docking

Journal Article · Fri May 19 00:00:00 EDT 2023 · Journal of Chemical Information and Modeling

DOI:https://doi.org/10.1021/acs.jcim.2c01530· OSTI ID:1989574

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Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). National Center for Computational Sciences
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Biosciences Division

A critical step in structure-based drug discovery is predicting whether and how a candidate molecule binds to a model of a therapeutic target. However, substantial protein side chain movements prevent current screening methods, such as docking, from accurately predicting the ligand conformations and require expensive refinements to produce viable candidates. Here, we present the development of a high-throughput and flexible ligand pose refinement workflow, called “tinyIFD”. The main features of the workflow include the use of specialized high-throughput, small-system MD simulation code mdgx.cuda and an actively learning model zoo approach. We show the application of this workflow on a large test set of diverse protein targets, achieving 66% and 76% success rates for finding a crystal-like pose within the top-2 and top-5 poses, respectively. We also applied this workflow to the SARS-CoV-2 main protease (M^pro) inhibitors, where we demonstrate the benefit of the active learning aspect in this workflow.

View Accepted Manuscript (DOE)

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1989574

Journal Information:: Journal of Chemical Information and Modeling, Journal Name: Journal of Chemical Information and Modeling Journal Issue: 11 Vol. 63; ISSN 1549-9596

Publisher:: American Chemical SocietyCopyright Statement

Country of Publication:: United States

Language:: English

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