OnionNet-2: A Convolutional Neural Network Model for Predicting Protein-Ligand Binding Affinity Based on Residue-Atom Contacting Shells

Combining Docking Pose Rank and Structure with Deep Learning Improves Protein–Ligand Binding Mode Prediction over a Baseline Docking Approach

(2020) Joseph A. Morrone et al.   Journal of Chemical Information and Modeling

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

spyrmsd: symmetry-corrected RMSD calculations in Python

(2020) Rocco Meli et al.   Journal of Cheminformatics

Applications of machine learning in drug discovery and development

(2019) Jessica Vamathevan et al.   NATURE REVIEWS DRUG DISCOVERY

Analyzing Learned Molecular Representations for Property Prediction

(2019) Kevin Yang et al.   Journal of Chemical Information and Modeling

AGL-Score: Algebraic Graph Learning Score for Protein–Ligand Binding Scoring, Ranking, Docking, and Screening

(2019) Duc Duy Nguyen et al.   Journal of Chemical Information and Modeling

Deep learning in bioinformatics

(2019) Wei Wang et al.   METHODS

From machine learning to deep learning: Advances in scoring functions for protein-ligand docking

(2019) Chao Shen et al.   Wiley Interdisciplinary Reviews-Computational Molecular Science

Deep learning in drug discovery: opportunities, challenges and future prospects

(2019) Antonio Lavecchia   DRUG DISCOVERY TODAY

OnionNet: a Multiple-Layer Intermolecular-Contact-Based Convolutional Neural Network for Protein–Ligand Binding Affinity Prediction

(2019) Liangzhen Zheng et al.   ACS Omega

Graph Convolutional Neural Networks for Predicting Drug-Target Interactions

(2019) Wen Torng 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

OUP accepted manuscript

(2018)   BIOINFORMATICS

Machine learning in chemoinformatics and drug discovery

(2018) Yu-Chen Lo et al.   DRUG DISCOVERY TODAY

The rise of deep learning in drug discovery

(2018) Hongming Chen et al.   DRUG DISCOVERY TODAY

Neural network and deep-learning algorithms used in QSAR studies: merits and drawbacks

(2018) Fahimeh Ghasemi et al.   DRUG DISCOVERY TODAY

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

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

Assessing protein–ligand interaction scoring functions with the CASF-2013 benchmark

(2018) Yan Li et al.   Nature Protocols

High Precision Protein Functional Site Detection Using 3D Convolutional Neural Networks

(2018) Wen Torng et al.   BIOINFORMATICS

Empirical Scoring Functions for Structure-Based Virtual Screening: Applications, Critical Aspects, and Challenges

(2018) Isabella A. Guedes et al.   Frontiers in Pharmacology

Comparative Assessment of Scoring Functions: The CASF-2016 Update

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

The Roles of Water in the Protein Matrix: A Largely Untapped Resource for Drug Discovery

(2017) Francesca Spyrakis et al.   JOURNAL OF MEDICINAL CHEMISTRY

Protein Binding Pocket Dynamics

(2016) Antonia Stank et al.   ACCOUNTS OF CHEMICAL RESEARCH

The Halogen Bond

(2016) Gabriella Cavallo et al.   CHEMICAL REVIEWS

Insights into Protein–Ligand Interactions: Mechanisms, Models, and Methods

(2016) Xing Du et al.   INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES

Deep learning for computational biology

(2016) Christof Angermueller et al.   Molecular Systems Biology

Computational protein–ligand docking and virtual drug screening with the AutoDock suite

(2016) Stefano Forli et al.   Nature Protocols

Machine-learning approaches in drug discovery: methods and applications

(2015) Antonio Lavecchia   DRUG DISCOVERY TODAY

Classification of Current Scoring Functions

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

Deep Learning in Drug Discovery

(2015) Erik Gawehn et al.   Molecular Informatics

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

Implementation of the Hungarian Algorithm to Account for Ligand Symmetry and Similarity in Structure-Based Design

(2014) William J. Allen et al.   Journal of Chemical Information and Modeling

Comparative Assessment of Scoring Functions on an Updated Benchmark: 2. Evaluation Methods and General Results

(2014) Yan Li et al.   Journal of Chemical Information and Modeling

Comparative Assessment of Scoring Functions on an Updated Benchmark: 1. Compilation of the Test Set

(2014) Yan Li et al.   Journal of Chemical Information and Modeling

Practical Aspects of Free-Energy Calculations: A Review

(2014) Niels Hansen et al.   Journal of Chemical Theory and Computation

Challenges, Applications, and Recent Advances of Protein-Ligand Docking in Structure-Based Drug Design

(2014) Sam Grinter et al.   MOLECULES

Hydration Properties of Ligands and Drugs in Protein Binding Sites: Tightly-Bound, Bridging Water Molecules and Their Effects and Consequences on Molecular Design Strategies

(2013) Alfonso T. García-Sosa   Journal of Chemical Information and Modeling

CSAR Benchmark Exercise of 2010: Selection of the Protein–Ligand Complexes

(2011) James B. Dunbar et al.   Journal of Chemical Information and Modeling

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

Prediction of protein–ligand binding affinity by free energy simulations: assumptions, pitfalls and expectations

(2010) Julien Michel et al.   JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN

Scoring functions and their evaluation methods for protein–ligand docking: recent advances and future directions

(2010) Sheng-You Huang et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

Computational evaluation of protein–small molecule binding

(2009) Olgun Guvench et al.   CURRENT OPINION IN STRUCTURAL BIOLOGY

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

An Improved PMF Scoring Function for Universally Predicting the Interactions of a Ligand with Protein, DNA, and RNA

(2008) Xiaoyu Zhao et al.   Journal of Chemical Information and Modeling