GNINA 1.0: molecular docking with deep learning

Three-Dimensional Convolutional Neural Networks and a Cross-Docked Data Set for Structure-Based Drug Design

(2020) Paul G. Francoeur et al.   Journal of Chemical Information and Modeling

Guiding Conventional Protein–Ligand Docking Software with Convolutional Neural Networks

(2020) Huaipan Jiang et al.   Journal of Chemical Information and Modeling

Ultra-large library docking for discovering new chemotypes

(2019) Jiankun Lyu et al.   NATURE

MathDL: mathematical deep learning for D3R Grand Challenge 4

(2019) Duc Duy Nguyen et al.   JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN

Cross‐docking benchmark for automated pose and ranking prediction of ligand binding

(2019) Shayne D. Wierbowski et al.   PROTEIN SCIENCE

Autodock Vina Adopts More Accurate Binding Poses but Autodock4 Forms Better Binding Affinity

(2019) Nguyen Thanh Nguyen 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

Machine Learning for Integrating Data in Biology and Medicine: Principles, Practice, and Opportunities

(2018) Marinka Zitnik et al.   Information Fusion

Comparative Assessment of Scoring Functions: The CASF-2016 Update

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

PotentialNet for Molecular Property Prediction

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

Integration of element specific persistent homology and machine learning for protein-ligand binding affinity prediction

(2017) Zixuan Cang et al.   International Journal for Numerical Methods in Biomedical Engineering

Task-Specific Scoring Functions for Predicting Ligand Binding Poses and Affinity and for Screening Enrichment

(2017) Hossam M. Ashtawy et al.   Journal of Chemical Information and Modeling

Protein–Ligand Scoring with Convolutional Neural Networks

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

Boosting Docking-Based Virtual Screening with Deep Learning

(2016) Janaina Cruz Pereira et al.   Journal of Chemical Information and Modeling

Vinardo: A Scoring Function Based on Autodock Vina Improves Scoring, Docking, and Virtual Screening

(2016) Rodrigo Quiroga et al.   PLoS One

BgN-Score and BsN-Score: Bagging and boosting based ensemble neural networks scoring functions for accurate binding affinity prediction of protein-ligand complexes

(2015) Hossam M Ashtawy et al.   BMC BIOINFORMATICS

Classification of Current Scoring Functions

(2015) Jie Liu et al.   Journal of Chemical Information and Modeling

Deep learning

(2015) Yann LeCun et al.   NATURE

BindingDB in 2015: A public database for medicinal chemistry, computational chemistry and systems pharmacology

(2015) Michael K. Gilson et al.   NUCLEIC ACIDS RESEARCH

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

ID-Score: A New Empirical Scoring Function Based on a Comprehensive Set of Descriptors Related to Protein–Ligand Interactions

(2013) Guo-Bo Li et al.   Journal of Chemical Information and Modeling

SFCscoreRF: A Random Forest-Based Scoring Function for Improved Affinity Prediction of Protein–Ligand Complexes

(2013) David Zilian et al.   Journal of Chemical Information and Modeling

Lessons Learned in Empirical Scoring with smina from the CSAR 2011 Benchmarking Exercise

(2013) David Ryan Koes et al.   Journal of Chemical Information and Modeling

ProDy: Protein Dynamics Inferred from Theory and Experiments

(2011) A. Bakan et al.   BIOINFORMATICS

Support Vector Regression Scoring of Receptor–Ligand Complexes for Rank-Ordering and Virtual Screening of Chemical Libraries

(2011) Liwei Li et al.   Journal of Chemical Information and Modeling

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

NNScore: A Neural-Network-Based Scoring Function for the Characterization of Protein−Ligand Complexes

(2010) Jacob D. Durrant et al.   Journal of Chemical Information and Modeling