Generative machine learning for de novo drug discovery: A systematic review

Transformer neural network for protein-specific de novo drug generation as a machine translation problem

(2021) Daria Grechishnikova   Scientific Reports

Advances in De Novo Drug Design: From Conventional to Machine Learning Methods

(2021) Varnavas D. Mouchlis et al.   INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES

PaccMannRL: De novo Generation of Hit-like Anticancer Molecules from Transcriptomic Data via Reinforcement Learning

(2021) Jannis Born et al.   iScience

De novo design and bioactivity prediction of SARS-CoV-2 main protease inhibitors using recurrent neural network-based transfer learning

(2021) Marcos V. S. Santana et al.   BMC Chemistry

Comparison of structure- and ligand-based scoring functions for deep generative models: a GPCR case study

(2021) Morgan Thomas et al.   Journal of Cheminformatics

Beam Search for Automated Design and Scoring of Novel ROR Ligands with Machine Intelligence**

(2021) Michael Moret et al.   ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

De novo molecular design and generative models

(2021) Joshua Meyers et al.   DRUG DISCOVERY TODAY

AI in drug development: a multidisciplinary perspective

(2021) Víctor Gallego et al.   MOLECULAR DIVERSITY

Predicting novel drug candidates against Covid-19 using generative deep neural networks

(2021) Santhosh Amilpur et al.   JOURNAL OF MOLECULAR GRAPHICS & MODELLING

VARIDT 2.0: structural variability of drug transporter

(2021) Tingting Fu et al.   NUCLEIC ACIDS RESEARCH

Exploration and augmentation of pharmacological space via adversarial auto-encoder model for facilitating kinase-centric drug development

(2021) Xinyu Bai et al.   Journal of Cheminformatics

DrugEx v2: de novo design of drug molecules by Pareto-based multi-objective reinforcement learning in polypharmacology

(2021) Xuhan Liu et al.   Journal of Cheminformatics

Enhancing reaction-based de novo design using a multi-label reaction class recommender

(2020) Gian Marco Ghiandoni et al.   JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN

De novo generation of hit-like molecules from gene expression signatures using artificial intelligence

(2020) Oscar Méndez-Lucio et al.   Nature Communications

Mol-CycleGAN: a generative model for molecular optimization

(2020) Łukasz Maziarka et al.   Journal of Cheminformatics

Multiobjective de novo drug design with recurrent neural networks and nondominated sorting

(2020) Jacob Yasonik   Journal of Cheminformatics

Machine-Learning-Assisted De Novo Design of Organic Molecules and Polymers: Opportunities and Challenges

(2020) Guang Chen et al.   Polymers

In silico Strategies to Support Fragment-to-Lead Optimization in Drug Discovery

(2020) Lauro Ribeiro de Souza Neto et al.   Frontiers in Chemistry

The Synthesizability of Molecules Proposed by Generative Models

(2020) Wenhao Gao et al.   Journal of Chemical Information and Modeling

GEN: highly efficient SMILES explorer using autodidactic generative examination networks

(2020) Ruud van Deursen et al.   Journal of Cheminformatics

Generative Network Complex for the Automated Generation of Drug-like Molecules

(2020) Kaifu Gao et al.   Journal of Chemical Information and Modeling

Machine learning and AI-based approaches for bioactive ligand discovery and GPCR-ligand recognition

(2020) Sebastian Raschka et al.   METHODS

Virtual Screening and Design with Machine Intelligence Applied to Pim‐1 Kinase Inhibitors

(2020) Petra Schneider et al.   Molecular Informatics

Cheminformatics in Natural Product‐Based Drug Discovery

(2020) Ya Chen et al.   Molecular Informatics

Relevant Applications of Generative Adversarial Networks in Drug Design and Discovery: Molecular De Novo Design, Dimensionality Reduction, and De Novo Peptide and Protein Design

(2020) Eugene Lin et al.   MOLECULES

Chemical space exploration based on recurrent neural networks: applications in discovering kinase inhibitors

(2020) Xuanyi Li et al.   Journal of Cheminformatics

Artificial intelligence in drug discovery and development

(2020) Debleena Paul et al.   DRUG DISCOVERY TODAY

DeepCOMO: from structure-activity relationship diagnostics to generative molecular design using the compound optimization monitor methodology

(2020) Dimitar Yonchev et al.   JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN

Enhancing scientific discoveries in molecular biology with deep generative models

(2020) Romain Lopez et al.   Molecular Systems Biology

EvoMol: a flexible and interpretable evolutionary algorithm for unbiased de novo molecular generation

(2020) Jules Leguy et al.   Journal of Cheminformatics

Molecular representations in AI-driven drug discovery: a review and practical guide

(2020) Laurianne David et al.   Journal of Cheminformatics

Advanced machine-learning techniques in drug discovery

(2020) Moe Elbadawi et al.   DRUG DISCOVERY TODAY

Artificial intelligence in drug discovery: what is realistic, what are illusions? Part 1: Ways to make an impact, and why we are not there yet

(2020) Andreas Bender et al.   DRUG DISCOVERY TODAY

Artificial intelligence and machine learning‐aided drug discovery in central nervous system diseases: State‐of‐the‐arts and future directions

(2020) Sezen Vatansever et al.   MEDICINAL RESEARCH REVIEWS

Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models

(2020) Daniil Polykovskiy et al.   Frontiers in Pharmacology

Multimodal Deep Generative Models for Trajectory Prediction: A Conditional Variational Autoencoder Approach

(2020) Boris Ivanovic et al.   IEEE Robotics and Automation Letters

QBMG: quasi-biogenic molecule generator with deep recurrent neural network

(2019) Shuangjia Zheng et al.   Journal of Cheminformatics

GuacaMol: Benchmarking Models for de Novo Molecular Design

(2019) Nathan Brown et al.   Journal of Chemical Information and Modeling

An exploration strategy improves the diversity of de novo ligands using deep reinforcement learning: a case for the adenosine A2A receptor

(2019) Xuhan Liu et al.   Journal of Cheminformatics

A Structure-Based Drug Discovery Paradigm

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

Deep learning enables rapid identification of potent DDR1 kinase inhibitors

(2019) Alex Zhavoronkov et al.   NATURE BIOTECHNOLOGY

Looking beyond the hype: Applied AI and machine learning in translational medicine

(2019) Tzen S. Toh et al.   EBioMedicine

Automatic generation of sentimental texts via mixture adversarial networks

(2019) K. Wang et al.   ARTIFICIAL INTELLIGENCE

Randomized SMILES strings improve the quality of molecular generative models

(2019) Josep Arús-Pous et al.   Journal of Cheminformatics

Synthetic Activators of Cell Migration Designed by Constructive Machine Learning

(2019) Dominique Bruns et al.   ChemistryOpen

Applications of Deep-Learning in Exploiting Large-Scale and Heterogeneous Compound Data in Industrial Pharmaceutical Research

(2019) Laurianne David et al.   Frontiers in Pharmacology

DeepScaffold: A Comprehensive Tool for Scaffold-Based De Novo Drug Discovery Using Deep Learning

(2019) Yibo Li et al.   Journal of Chemical Information and Modeling

A de novo molecular generation method using latent vector based generative adversarial network

(2019) Oleksii Prykhodko et al.   Journal of Cheminformatics

What Contributes to Serotonin–Norepinephrine Reuptake Inhibitors’ Dual-Targeting Mechanism? The Key Role of Transmembrane Domain 6 in Human Serotonin and Norepinephrine Transporters Revealed by Molecular Dynamics Simulation

(2018) Weiwei Xue et al.   ACS Chemical Neuroscience

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

Reinforced Adversarial Neural Computer for de Novo Molecular Design

(2018) Evgeny Putin et al.   Journal of Chemical Information and Modeling

De Novo Design of Bioactive Small Molecules by Artificial Intelligence

(2018) Daniel Merk et al.   Molecular Informatics

Adversarial Threshold Neural Computer for Molecular de Novo Design

(2018) Evgeny Putin et al.   MOLECULAR PHARMACEUTICS

Computational identification of the binding mechanism of a triple reuptake inhibitor amitifadine for the treatment of major depressive disorder

(2018) Weiwei Xue et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

Clinical Success of Drug Targets Prospectively Predicted by In Silico Study

(2018) Feng Zhu et al.   TRENDS IN PHARMACOLOGICAL SCIENCES

Molecular generative model based on conditional variational autoencoder for de novo molecular design

(2018) Jaechang Lim et al.   Journal of Cheminformatics

Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules

(2018) Rafael Gómez-Bombarelli et al.   ACS Central Science

Fréchet ChemNet Distance: A Metric for Generative Models for Molecules in Drug Discovery

(2018) Kristina Preuer et al.   Journal of Chemical Information and Modeling

Entangled Conditional Adversarial Autoencoder for de Novo Drug Discovery

(2018) Daniil Polykovskiy et al.   MOLECULAR PHARMACEUTICS

Multi-objective de novo drug design with conditional graph generative model

(2018) Yibo Li et al.   Journal of Cheminformatics

Deep reinforcement learning for de novo drug design

(2018) Mariya Popova et al.   Science Advances

Population-based De Novo Molecule Generation, Using Grammatical Evolution

(2018) Naruki Yoshikawa et al.   CHEMISTRY LETTERS

Molecular Docking: Challenges, Advances and Its Use in Drug Discovery Perspective

(2018) Surovi Saikia et al.   CURRENT DRUG TARGETS

Generative Recurrent Networks for De Novo Drug Design

(2017) Anvita Gupta et al.   Molecular Informatics

Application of Generative Autoencoder in De Novo Molecular Design

(2017) Thomas Blaschke et al.   Molecular Informatics

DrugBank 5.0: a major update to the DrugBank database for 2018

(2017) David S Wishart et al.   NUCLEIC ACIDS RESEARCH

ChemTS: an efficient python library for de novo molecular generation

(2017) Xiufeng Yang et al.   SCIENCE AND TECHNOLOGY OF ADVANCED MATERIALS

Molecular de-novo design through deep reinforcement learning

(2017) Marcus Olivecrona et al.   Journal of Cheminformatics

Generating Focused Molecule Libraries for Drug Discovery with Recurrent Neural Networks

(2017) Marwin H. S. Segler et al.   ACS Central Science

Use of machine learning approaches for novel drug discovery

(2016) Angélica Nakagawa Lima et al.   Expert Opinion on Drug Discovery

Design of efficient molecular organic light-emitting diodes by a high-throughput virtual screening and experimental approach

(2016) Rafael Gómez-Bombarelli et al.   NATURE MATERIALS

The ChEMBL database in 2017

(2016) Anna Gaulton et al.   NUCLEIC ACIDS RESEARCH

Molecular fingerprint similarity search in virtual screening

(2015) Adrià Cereto-Massagué et al.   METHODS

What does the aromatic ring number mean for drug design?

(2014) Simon E Ward et al.   Expert Opinion on Drug Discovery

Recognizing Pitfalls in Virtual Screening: A Critical Review

(2012) Thomas Scior et al.   Journal of Chemical Information and Modeling

DOGS: Reaction-Driven de novo Design of Bioactive Compounds

(2012) Markus Hartenfeller et al.   PLoS Computational Biology

Extended-Connectivity Fingerprints

(2010) David Rogers et al.   Journal of Chemical Information and Modeling