Improved Protein–Ligand Binding Affinity Prediction with Structure-Based Deep Fusion Inference

Machine learning and ligand binding predictions: A review of data, methods, and obstacles

(2020) Sally R. Ellingson et al.   BIOCHIMICA ET BIOPHYSICA ACTA-GENERAL SUBJECTS

DeepBindRG: a deep learning based method for estimating effective protein–ligand affinity

(2019) Haiping Zhang et al.   PeerJ

Predicting Drug–Target Interaction Using a Novel Graph Neural Network with 3D Structure-Embedded Graph Representation

(2019) Jaechang Lim et al.   Journal of Chemical Information and Modeling

Development and evaluation of a deep learning model for protein–ligand binding affinity prediction

(2018) Marta M Stepniewska-Dziubinska et al.   BIOINFORMATICS

KDEEP: Protein–Ligand Absolute Binding Affinity Prediction via 3D-Convolutional Neural Networks

(2018) José Jiménez et al.   Journal of Chemical Information and Modeling

Visualizing convolutional neural network protein-ligand scoring

(2018) Joshua Hochuli et al.   JOURNAL OF MOLECULAR GRAPHICS & MODELLING

3D Molecular Representations Based on the Wave Transform for Convolutional Neural Networks

(2018) Denis Kuzminykh et al.   MOLECULAR PHARMACEUTICS

Comparative Assessment of Scoring Functions: The CASF-2016 Update

(2018) Minyi Su et al.   Journal of Chemical Information and Modeling

Protein Data Bank: the single global archive for 3D macromolecular structure data

(2018) et al.   NUCLEIC ACIDS RESEARCH

PotentialNet for Molecular Property Prediction

(2018) Evan N. Feinberg et al.   ACS Central Science

Protein–Ligand Scoring with Convolutional Neural Networks

(2017) Matthew Ragoza et al.   Journal of Chemical Information and Modeling

Molecular graph convolutions: moving beyond fingerprints

(2016) Steven Kearnes et al.   JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN

ff14SB: Improving the Accuracy of Protein Side Chain and Backbone Parameters from ff99SB

(2015) James A. Maier et al.   Journal of Chemical Theory and Computation

Machine-learning scoring functions to improve structure-based binding affinity prediction and virtual screening

(2015) Qurrat Ul Ain et al.   Wiley Interdisciplinary Reviews-Computational Molecular Science

Assessing the performance of MM/PBSA and MM/GBSA methods. 5. Improved docking performance using high solute dielectric constant MM/GBSA and MM/PBSA rescoring

(2014) Huiyong Sun et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

Toward Fully Automated High Performance Computing Drug Discovery: A Massively Parallel Virtual Screening Pipeline for Docking and Molecular Mechanics/Generalized Born Surface Area Rescoring to Improve Enrichment

(2013) Xiaohua Zhang et al.   Journal of Chemical Information and Modeling

Message passing interface and multithreading hybrid for parallel molecular docking of large databases on petascale high performance computing machines

(2013) Xiaohua Zhang et al.   JOURNAL OF COMPUTATIONAL CHEMISTRY

Open Babel: An open chemical toolbox

(2011) Noel M O'Boyle et al.   Journal of Cheminformatics

A machine learning approach to predicting protein–ligand binding affinity with applications to molecular docking

(2010) Pedro J. Ballester et al.   BIOINFORMATICS

AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading

(2009) Oleg Trott et al.   JOURNAL OF COMPUTATIONAL CHEMISTRY

The other 90% of the protein: Assessment beyond the Cαs for CASP8 template-based and high-accuracy models

(2009) Daniel A. Keedy et al.   PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS