Improving protein–ligand docking and screening accuracies by incorporating a scoring function correction term

DeepBSP—a Machine Learning Method for Accurate Prediction of Protein–Ligand Docking Structures

(2021) Jingxiao Bao et al.   Journal of Chemical Information and Modeling

Machine Learning-Enabled Pipeline for Large-Scale Virtual Drug Screening

(2021) Aayush Gupta et al.   Journal of Chemical Information and Modeling

Highly accurate protein structure prediction with AlphaFold

(2021) John Jumper et al.   NATURE

Highly accurate protein structure prediction for the human proteome

(2021) Kathryn Tunyasuvunakool et al.   NATURE

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

(2021) Zechen Wang et al.   Frontiers in Chemistry

Tapping on the Black Box: How Is the Scoring Power of a Machine-Learning Scoring Function Dependent on the Training Set?

(2020) Minyi Su et al.   Journal of Chemical Information and Modeling

RosENet: Improving Binding Affinity Prediction by Leveraging Molecular Mechanics Energies with an Ensemble of 3D Convolutional Neural Networks

(2020) Hussein Hassan-Harrirou et al.   Journal of Chemical Information and Modeling

Improving structure-based virtual screening performance via learning from scoring function components

(2020) Guo-Li Xiong et al.   BRIEFINGS IN BIOINFORMATICS

KORP-PL: a coarse-grained knowledge-based scoring function for protein-ligand interactions

(2020) Maria Kadukova et al.   BIOINFORMATICS

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

Application of docking and active site analysis for enzyme linked biodegradation of textile dyes

(2019) Shantkriti Srinivasan et al.   ENVIRONMENTAL POLLUTION

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

Large-Scale Target Identification of Herbal Medicine Using a Reverse Docking Approach

(2019) Haiping Zhang et al.   ACS Omega

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

(2019) Liangzhen Zheng et al.   ACS Omega

Incorporating Explicit Water Molecules and Ligand Conformation Stability in Machine-Learning Scoring Functions

(2019) Jianing Lu et al.   Journal of Chemical Information and Modeling

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

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

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

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

(2018) Yan Li et al.   Nature Protocols

Comparative Assessment of Scoring Functions: The CASF-2016 Update

(2018) Minyi Su 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

Performance of machine-learning scoring functions in structure-based virtual screening

(2017) Maciej Wójcikowski et al.   Scientific Reports

Using reverse docking for target identification and its applications for drug discovery

(2016) Aeri Lee et al.   Expert Opinion on Drug Discovery

Improving scoring-docking-screening powers of protein-ligand scoring functions using random forest

(2016) Cheng Wang et al.   JOURNAL OF COMPUTATIONAL CHEMISTRY

Docking Screens for Novel Ligands Conferring New Biology

(2016) John J. Irwin et al.   JOURNAL OF MEDICINAL CHEMISTRY

Inhibitor design against JNK1 through e-pharmacophore modeling docking and molecular dynamics simulations

(2016) Sudheer Kumar Katari et al.   JOURNAL OF RECEPTORS AND SIGNAL TRANSDUCTION

A random forest guided tour

(2016) Gérard Biau et al.   TEST

A random forest guided tour

(2016) Gérard Biau et al.   TEST

PDB-wide collection of binding data: current status of the PDBbind database

(2014) Zhihai Liu et al.   BIOINFORMATICS

Reverse docking: a powerful tool for drug repositioning and drug rescue

(2014) Prashant S Kharkar et al.   Future Medicinal Chemistry

lDDT: a local superposition-free score for comparing protein structures and models using distance difference tests

(2013) Valerio Mariani et al.   BIOINFORMATICS

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

Directory of Useful Decoys, Enhanced (DUD-E): Better Ligands and Decoys for Better Benchmarking

(2012) Michael M. Mysinger et al.   JOURNAL OF MEDICINAL CHEMISTRY

NNScore 2.0: A Neural-Network Receptor–Ligand Scoring Function

(2011) Jacob D. Durrant 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

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