De novo molecular design and generative models

Derivatization Design of Synthetically Accessible Space for Optimization: In Silico Synthesis vs Deep Generative Design

(2021) Gergely M. Makara et al.   ACS Medicinal Chemistry Letters

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

(2021) Jannis Born et al.   iScience

MolFinder: an evolutionary algorithm for the global optimization of molecular properties and the extensive exploration of chemical space using SMILES

(2021) Yongbeom Kwon et al.   Journal of Cheminformatics

DeeplyTough: Learning Structural Comparison of Protein Binding Sites

(2020) Martin Simonovsky et al.   Journal of Chemical Information and Modeling

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

Automated De-Novo Design in Medicinal Chemistry: Which Types of Chemistry Does a Generative Neural Network Learn?

(2020) Christoph Grebner et al.   JOURNAL OF MEDICINAL CHEMISTRY

Reply to ‘Assessing the impact of generative AI on medicinal chemistry’

(2020) Alex Zhavoronkov et al.   NATURE BIOTECHNOLOGY

Assessing the impact of generative AI on medicinal chemistry

(2020) W. Patrick Walters et al.   NATURE BIOTECHNOLOGY

The unreasonable effectiveness of deep learning in artificial intelligence

(2020) Terrence J. Sejnowski   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

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

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

The Synthesizability of Molecules Proposed by Generative Models

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

Deep Generative Models for 3D Linker Design

(2020) Fergus Imrie et al.   Journal of Chemical Information and Modeling

AutoGrow4: an open-source genetic algorithm for de novo drug design and lead optimization

(2020) Jacob O. Spiegel et al.   Journal of Cheminformatics

CReM: chemically reasonable mutations framework for structure generation

(2020) Pavel Polishchuk   Journal of Cheminformatics

SMILES-based deep generative scaffold decorator for de-novo drug design

(2020) Josep Arús-Pous et al.   Journal of Cheminformatics

Combining Cloud-Based Free-Energy Calculations, Synthetically Aware Enumerations, and Goal-Directed Generative Machine Learning for Rapid Large-Scale Chemical Exploration and Optimization

(2020) Phani Ghanakota et al.   Journal of Chemical Information and Modeling

Automated extraction of chemical synthesis actions from experimental procedures

(2020) Alain C. Vaucher et al.   Nature Communications

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

(2020) Xuanyi Li et al.   Journal of Cheminformatics

Exploring chemical compound space with quantum-based machine learning

(2020) O. Anatole von Lilienfeld et al.   Nature Reviews Chemistry

OptiMol: Optimization of Binding Affinities in Chemical Space for Drug Discovery

(2020) Jacques Boitreaud et al.   Journal of Chemical Information and Modeling

A Turing Test for Molecular Generators

(2020) Jacob T. Bush et al.   JOURNAL OF MEDICINAL CHEMISTRY

GuacaMol: Benchmarking Models for de Novo Molecular Design

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

Shape-Based Generative Modeling for de Novo Drug Design

(2019) Miha Skalic et al.   Journal of Chemical Information and Modeling

Deep learning for molecular generation

(2019) Youjun Xu et al.   Future Medicinal Chemistry

Automated De Novo Drug Design - “Are we nearly there yet?”

(2019) Gisbert Schneider et al.   ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

Deep Reinforcement Learning for Multiparameter Optimization in de novo Drug Design

(2019) Niclas Ståhl et al.   Journal of Chemical Information and Modeling

Optimization of Molecules via Deep Reinforcement Learning

(2019) Zhenpeng Zhou et al.   Scientific Reports

Deep learning enables rapid identification of potent DDR1 kinase inhibitors

(2019) Alex Zhavoronkov et al.   NATURE BIOTECHNOLOGY

Autonomous discovery in the chemical sciences part II: Outlook

(2019) Connor W Coley et al.   ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

Has Drug Design Augmented by Artificial Intelligence Become a Reality?

(2019) Hongming Chen et al.   TRENDS IN PHARMACOLOGICAL SCIENCES

Randomized SMILES strings improve the quality of molecular generative models

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

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

(2019) Oleksii Prykhodko et al.   Journal of Cheminformatics

Planning chemical syntheses with deep neural networks and symbolic AI

(2018) Marwin H. S. Segler et al.   NATURE

Inverse molecular design using machine learning: Generative models for matter engineering

(2018) Benjamin Sanchez-Lengeling et al.   SCIENCE

Population-based De Novo Molecule Generation, Using Grammatical Evolution

(2018) Naruki Yoshikawa et al.   CHEMISTRY LETTERS

De Novo Molecule Design by Translating from Reduced Graphs to SMILES

(2018) Peter Pogány et al.   Journal of Chemical Information and Modeling

Generating Focused Molecule Libraries for Drug Discovery with Recurrent Neural Networks

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

When Quality Beats Quantity: Decision Theory, Drug Discovery, and the Reproducibility Crisis

(2016) Jack W. Scannell et al.   PLoS One

MOARF, an Integrated Workflow for Multiobjective Optimization: Implementation, Synthesis, and Biological Evaluation

(2015) Nicholas C. Firth et al.   Journal of Chemical Information and Modeling

Get Your Atoms in Order—An Open-Source Implementation of a Novel and Robust Molecular Canonicalization Algorithm

(2015) Nadine Schneider et al.   Journal of Chemical Information and Modeling

Multi-Objective Molecular De Novo Design by Adaptive Fragment Prioritization

(2014) Michael Reutlinger et al.   ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

Quantifying the chemical beauty of drugs

(2012) G. Richard Bickerton et al.   Nature Chemistry

A Collection of Robust Organic Synthesis Reactions forIn SilicoMolecule Design

(2011) Markus Hartenfeller et al.   Journal of Chemical Information and Modeling

A Drug Candidate Design Environment Using Evolutionary Computation

(2008) M.I. Ecemis et al.   IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION