Chemical language models for de novo drug design: Challenges and opportunities

On the Frustration to Predict Binding Affinities from Protein–Ligand Structures with Deep Neural Networks

(2022) Mikhail Volkov et al.   JOURNAL OF MEDICINAL CHEMISTRY

Language models can learn complex molecular distributions

(2022) Daniel Flam-Shepherd et al.   Nature Communications

Implications of Additivity and Nonadditivity for Machine Learning and Deep Learning Models in Drug Design

(2022) Karolina Kwapien et al.   ACS Omega

Large-Scale Distributed Training of Transformers for Chemical Fingerprinting

(2022) Hisham Abdel-Aty et al.   Journal of Chemical Information and Modeling

Exposing the Limitations of Molecular Machine Learning with Activity Cliffs

(2022) Derek van Tilborg et al.   Journal of Chemical Information and Modeling

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

Combining generative artificial intelligence and on-chip synthesis for de novo drug design

(2021) Francesca Grisoni et al.   Science Advances

Exploring chemical space using natural language processing methodologies for drug discovery

(2020) Hakime Öztürk et al.   DRUG DISCOVERY TODAY

Bidirectional Molecule Generation with Recurrent Neural Networks

(2020) Francesca Grisoni et al.   Journal of Chemical Information and Modeling

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

Guidelines for Recurrent Neural Network Transfer Learning-Based Molecular Generation of Focused Libraries

(2020) Silvia Amabilino et al.   Journal of Chemical Information and Modeling

Critical Assessment of Artificial Intelligence Methods for Prediction of hERG Channel Inhibition in the “Big Data” Era

(2020) Vishal B. Siramshetty et al.   Journal of Chemical Information and Modeling

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

(2020) Daniil Polykovskiy et al.   Frontiers in Pharmacology

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

Optimization of Molecules via Deep Reinforcement Learning

(2019) Zhenpeng Zhou et al.   Scientific Reports

From Target to Drug: Generative Modeling for the Multimodal Structure-Based Ligand Design

(2019) Miha Skalic et al.   MOLECULAR PHARMACEUTICS

De Novo Design of Bioactive Small Molecules by Artificial Intelligence

(2018) Daniel Merk et al.   Molecular Informatics

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

Chemical Space Mimicry for Drug Discovery

(2017) William Yuan 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

Deep learning

(2015) Yann LeCun et al.   NATURE

Quantifying the chemical beauty of drugs

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