Recent progress on the prospective application of machine learning to structure-based virtual screening

Property-Unmatched Decoys in Docking Benchmarks

(2021) Reed M. Stein et al.   Journal of Chemical Information and Modeling

Generating property-matched decoy molecules using deep learning

(2021) Fergus Imrie et al.   BIOINFORMATICS

Machine‐learning scoring functions for structure‐based drug lead optimization

(2020) Hongjian Li et al.   Wiley Interdisciplinary Reviews-Computational Molecular Science

Machine learning models for drug–target interactions: current knowledge and future directions

(2020) Sofia D’Souza et al.   DRUG DISCOVERY TODAY

Similarity-Based Methods and Machine Learning Approaches for Target Prediction in Early Drug Discovery: Performance and Scope

(2020) Neann Mathai et al.   INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES

An open-source drug discovery platform enables ultra-large virtual screens

(2020) Christoph Gorgulla et al.   NATURE

Bayer’s in silico ADMET platform: a journey of machine learning over the past two decades

(2020) Andreas H. Göller et al.   DRUG DISCOVERY TODAY

Discovery of Novel Inhibitors of a Critical Brain Enzyme Using a Homology Model and a Deep Convolutional Neural Network

(2020) Adrian Stecula et al.   JOURNAL OF MEDICINAL CHEMISTRY

Machine learning classification can reduce false positives in structure-based virtual screening

(2020) Yusuf O. Adeshina et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Small molecules block the interaction between porcine reproductive and respiratory syndrome virus and CD163 receptor and the infection of pig cells

(2020) Chang Huang et al.   Virology Journal

Ensemble transfer learning for the prediction of anti-cancer drug response

(2020) Yitan Zhu et al.   Scientific Reports

Leveraging Uncertainty in Machine Learning Accelerates Biological Discovery and Design

(2020) Brian Hie et al.   Cell Systems

Handling the Hurdles on the Way to Anti-tuberculosis Drug Development

(2020) Pedro F. Dalberto et al.   Frontiers in Chemistry

Application of In Silico and HTS Approaches to Identify Nuclear Import Inhibitors for Venezuelan Equine Encephalitis Virus Capsid Protein: A Case Study

(2020) Sharon Shechter et al.   Frontiers in Chemistry

Structure-Based Scaffold Repurposing toward the Discovery of Novel Cholinesterase Inhibitors

(2020) Satish N. Dighe et al.   ACS Omega

Improved Method of Structure-Based Virtual Screening via Interaction-Energy-Based Learning

(2019) Nobuaki Yasuo et al.   Journal of Chemical Information and Modeling

MolTarPred: a web tool for comprehensive target prediction with reliability estimation

(2019) Antonio Peón et al.   Chemical Biology & Drug Design

Classical scoring functions for docking are unable to exploit large volumes of structural and interaction data

(2019) Hongjian Li et al.   BIOINFORMATICS

A Structure-Based Drug Discovery Paradigm

(2019) Maria Batool et al.   INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES

Miro1 Marks Parkinson’s Disease Subset and Miro1 Reducer Rescues Neuron Loss in Parkinson’s Models

(2019) Chung-Han Hsieh et al.   Cell Metabolism

A Stochastic Spiking Neural Network for Virtual Screening

(2018) A. Morro et al.   IEEE Transactions on Neural Networks and Learning Systems

Decoys Selection in Benchmarking Datasets: Overview and Perspectives

(2018) Manon Réau et al.   Frontiers in Pharmacology

Mathematical deep learning for pose and binding affinity prediction and ranking in D3R Grand Challenges

(2018) Duc Duy Nguyen et al.   JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN

Advances in the Development of Shape Similarity Methods and Their Application in Drug Discovery

(2018) Ashutosh Kumar et al.   Frontiers in Chemistry

Protein Family-Specific Models Using Deep Neural Networks and Transfer Learning Improve Virtual Screening and Highlight the Need for More Data

(2018) Fergus Imrie et al.   Journal of Chemical Information and Modeling

Practical Model Selection for Prospective Virtual Screening

(2018) Shengchao Liu 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

Correcting the impact of docking pose generation error on binding affinity prediction

(2016) Hongjian Li et al.   BMC BIOINFORMATICS

Docking Screens for Novel Ligands Conferring New Biology

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

Constructing and Validating High-Performance MIEC-SVM Models in Virtual Screening for Kinases: A Better Way for Actives Discovery

(2016) Huiyong Sun et al.   Scientific Reports

Advancing Biological Understanding and Therapeutics Discovery with Small-Molecule Probes

(2015) Stuart L. Schreiber et al.   CELL

A Comparative Assessment of Predictive Accuracies of Conventional and Machine Learning Scoring Functions for Protein-Ligand Binding Affinity Prediction

(2015) Hossam M. Ashtawy et al.   IEEE-ACM Transactions on Computational Biology and Bioinformatics

Neural-Network Scoring Functions Identify Structurally Novel Estrogen-Receptor Ligands

(2015) Jacob D. Durrant et al.   Journal of Chemical Information and Modeling

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

Integrating docking scores, interaction profiles and molecular descriptors to improve the accuracy of molecular docking: Toward the discovery of novel Akt1 inhibitors

(2014) Wenhu Zhan et al.   EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY

Does a More Precise Chemical Description of Protein–Ligand Complexes Lead to More Accurate Prediction of Binding Affinity?

(2014) Pedro J. Ballester et al.   Journal of Chemical Information and Modeling

Discovery of ZAP70 inhibitors by high-throughput docking into a conformation of its kinase domain generated by molecular dynamics

(2013) Hongtao Zhao et al.   BIOORGANIC & MEDICINAL CHEMISTRY LETTERS

Structure-Based Virtual Screening for Drug Discovery: a Problem-Centric Review

(2012) Tiejun Cheng et al.   AAPS Journal

Hierarchical virtual screening for the discovery of new molecular scaffolds in antibacterial hit identification

(2012) P. J. Ballester et al.   Journal of the Royal Society Interface

Target-Specific Support Vector Machine Scoring in Structure-Based Virtual Screening: Computational Validation, In Vitro Testing in Kinases, and Effects on Lung Cancer Cell Proliferation

(2011) Liwei Li 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

Structure-based discovery of antibacterial drugs

(2010) Katie J. Simmons et al.   NATURE REVIEWS MICROBIOLOGY