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GNINA 1.0: Molecular Docking with Deep Learning

Andrew McNutt, Paul Francoeur, Rishal Aggarwal, Tomohide Masuda, Rocco Meli, Matthew Ragoza, Jocelyn Sunseri, David Koes

Version 1 posted 18 January 2021

2,741

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Theoretical and Computational Chemistry

Working Paper

Learning RMSD to Improve Protein-Ligand Scoring and Pose Selection

Rishal Aggarwal, David R. Koes

Version 2 posted 03 March 2020

2,451

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5

Citations

Theoretical and Computational Chemistry

Working Paper

Hidden Bias in the DUD-E Dataset Leads to Misleading Performance of Deep Learning in Structure-Based Virtual Screening

Lieyang Chen, Anthony Cruz, Steven Ramsey, Callum J. Dickson, José S. Duca, Viktor Hornak, David R. Koes, Tom Kurtzman

Version 1 posted 25 March 2019

1,325

Downloads

2

Citations

Theoretical and Computational Chemistry

Working Paper

Evaluation of Thermochemical Machine Learning for Potential Energy Curves and Geometry Optimization

Dakota Folmsbee, David R. Koes, Geoffrey Hutchison

Version 2 posted 10 February 2021

762

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Biological and Medicinal Chemistry

Working Paper

3D Convolutional Neural Networks and a CrossDocked Dataset for Structure-Based Drug Design

Paul Francoeur, Tomohide Masuda, David R. Koes

Version 2 posted 04 March 2020

2,956

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Theoretical and Computational Chemistry

Working Paper

Active Learning for Small Molecule pKa Regression; a Long Way To Go

Paul Francoeur, Daniel Penaherrera, David Koes

Version 1 posted 20 May 2022

780

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Theoretical and Computational Chemistry

Working Paper

Systematic Comparison of Experimental Crystallographic Geometries and Gas-Phase Computed Conformers for Torsion Preferences

Dakota Folmsbee, David Koes, Geoffrey Hutchison

Version 3 posted 08 November 2023

278

Downloads

Theoretical and Computational Chemistry

Working Paper

BigBind: Learning from Nonstructural Data for Structure-Based Virtual Screening

Michael Brocidiacono, Paul Francoeur, Rishal Aggarwal, Konstantin Popov, David Koes, Alexander Tropsha

Version 3 posted 14 November 2023

1,450

Downloads

Theoretical and Computational Chemistry

Working Paper

Condensing Molecular Docking CNNs via Knowledge Distillation

Andrew McNutt, Yanjing Li, Paul Francoeur, David Koes

Version 1 posted 29 March 2024

176

Downloads

Theoretical and Computational Chemistry

Working Paper

Open-ComBind: Harnessing unlabeled data for improved binding pose prediction

Andrew McNutt, David Koes

Version 1 posted 06 September 2023

211

Downloads

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12 results in David Koes in Authors: David Koes

GNINA 1.0: Molecular Docking with Deep Learning

Learning RMSD to Improve Protein-Ligand Scoring and Pose Selection

Hidden Bias in the DUD-E Dataset Leads to Misleading Performance of Deep Learning in Structure-Based Virtual Screening

Evaluation of Thermochemical Machine Learning for Potential Energy Curves and Geometry Optimization

3D Convolutional Neural Networks and a CrossDocked Dataset for Structure-Based Drug Design

Active Learning for Small Molecule pKa Regression; a Long Way To Go

Systematic Comparison of Experimental Crystallographic Geometries and Gas-Phase Computed Conformers for Torsion Preferences

BigBind: Learning from Nonstructural Data for Structure-Based Virtual Screening

Condensing Molecular Docking CNNs via Knowledge Distillation

Open-ComBind: Harnessing unlabeled data for improved binding pose prediction

12 results in Authors: David Koes