Search Results - "Koes, David"
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Hidden bias in the DUD-E dataset leads to misleading performance of deep learning in structure-based virtual screening
Published in PloS one (20-08-2019)“…Recently much effort has been invested in using convolutional neural network (CNN) models trained on 3D structural images of protein-ligand complexes to…”
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libmolgrid: Graphics Processing Unit Accelerated Molecular Gridding for Deep Learning Applications
Published in Journal of chemical information and modeling (23-03-2020)“…We describe libmolgrid, a general-purpose library for representing three-dimensional molecules using multidimensional arrays of voxelized molecular data…”
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SolTranNet–A Machine Learning Tool for Fast Aqueous Solubility Prediction
Published in Journal of chemical information and modeling (28-06-2021)“…While accurate prediction of aqueous solubility remains a challenge in drug discovery, machine learning (ML) approaches have become increasingly popular for…”
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DeepFrag: a deep convolutional neural network for fragment-based lead optimization
Published in Chemical science (Cambridge) (08-05-2021)“…Machine learning has been increasingly applied to the field of computer-aided drug discovery in recent years, leading to notable advances in binding-affinity…”
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GNINA 1.0: molecular docking with deep learning
Published in Journal of cheminformatics (09-06-2021)“…Molecular docking computationally predicts the conformation of a small molecule when binding to a receptor. Scoring functions are a vital piece of any…”
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Improvements to the APBS biomolecular solvation software suite
Published in Protein science (01-01-2018)“…The Adaptive Poisson–Boltzmann Solver (APBS) software was developed to solve the equations of continuum electrostatics for large biomolecular assemblages that…”
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Three-Dimensional Convolutional Neural Networks and a Cross-Docked Data Set for Structure-Based Drug Design
Published in Journal of chemical information and modeling (28-09-2020)“…One of the main challenges in drug discovery is predicting protein–ligand binding affinity. Recently, machine learning approaches have made substantial…”
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Pharmit: interactive exploration of chemical space
Published in Nucleic acids research (08-07-2016)“…Pharmit (http://pharmit.csb.pitt.edu) provides an online, interactive environment for the virtual screening of large compound databases using pharmacophores,…”
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Generating 3D molecules conditional on receptor binding sites with deep generative models
Published in Chemical science (Cambridge) (02-03-2022)“…The goal of structure-based drug discovery is to find small molecules that bind to a given target protein. Deep learning has been used to generate drug-like…”
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Deciphering the Role of Fatty Acid-Metabolizing CYP4F11 in Lung Cancer and Its Potential As a Drug Target
Published in Drug metabolism and disposition (01-02-2024)“…Lung cancer is the leading cause of cancer deaths worldwide. We found that the cytochrome P450 isoform CYP4F11 is significantly overexpressed in patients with…”
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Systematic Comparison of Experimental Crystallographic Geometries and Gas-Phase Computed Conformers for Torsion Preferences
Published in Journal of chemical information and modeling (11-12-2023)“…We performed exhaustive torsion sampling on more than 3 million compounds using the GFN2-xTB method and performed a comparison of experimental crystallographic…”
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AnchorQuery: Rapid online virtual screening for small‐molecule protein–protein interaction inhibitors
Published in Protein science (01-01-2018)“…AnchorQuery (http://anchorquery.csb.pitt.edu) is a web application for rational structure‐based design of protein–protein interaction (PPI) inhibitors. A…”
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Evaluation of Thermochemical Machine Learning for Potential Energy Curves and Geometry Optimization
Published in The journal of physical chemistry. A, Molecules, spectroscopy, kinetics, environment, & general theory (11-03-2021)“…While many machine learning (ML) methods, particularly deep neural networks, have been trained for density functional and quantum chemical energies and…”
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Correction to “SolTranNetA Machine Learning Tool for Fast Aqueous Solubility Prediction”
Published in Journal of chemical information and modeling (23-08-2021)Get full text
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Virtual Screening with Gnina 1.0
Published in Molecules (Basel, Switzerland) (04-12-2021)“…Virtual screening-predicting which compounds within a specified compound library bind to a target molecule, typically a protein-is a fundamental task in the…”
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SidechainNet: An all‐atom protein structure dataset for machine learning
Published in Proteins, structure, function, and bioinformatics (01-11-2021)“…Despite recent advancements in deep learning methods for protein structure prediction and representation, little focus has been directed at the simultaneous…”
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Evaluating amber force fields using computed NMR chemical shifts
Published in Proteins, structure, function, and bioinformatics (01-10-2017)“…NMR chemical shifts can be computed from molecular dynamics (MD) simulations using a template matching approach and a library of conformers containing chemical…”
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Expanding Training Data for Structure-Based Receptor–Ligand Binding Affinity Regression through Imputation of Missing Labels
Published in ACS omega (07-11-2023)“…The success of machine learning is, in part, due to a large volume of data available to train models. However, the amount of training data for structure-based…”
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Threonine 89 Is an Important Residue of Profilin-1 That Is Phosphorylatable by Protein Kinase A
Published in PloS one (26-05-2016)“…Dynamic regulation of actin cytoskeleton is at the heart of all actin-based cellular events. In this study, we sought to identify novel post-translational…”
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Enabling large-scale design, synthesis and validation of small molecule protein-protein antagonists
Published in PloS one (12-03-2012)“…Although there is no shortage of potential drug targets, there are only a handful known low-molecular-weight inhibitors of protein-protein interactions (PPIs)…”
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