Unleashing the power of generative AI in drug discovery

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Deep reinforcement learning for de novo drug design

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GuacaMol: Benchmarking Models for de Novo Molecular Design

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

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Machine-learning approaches in drug discovery: methods and applications

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Virtual Screening Strategies in Drug Discovery: A Critical Review

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Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation ModelsPreprint

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Applications of Deep Learning in Biomedicine

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Graph Convolutional Policy Network for Goal-Directed Molecular Graph GenerationPreprint

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Deep learning for molecular design—a review of the state of the art

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Optimization of Molecules via Deep Reinforcement Learning

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Self-referencing embedded strings (SELFIES): A 100% robust molecular string representation

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druGAN: An Advanced Generative Adversarial Autoencoder Model for de Novo Generation of New Molecules with Desired Molecular Properties in Silico

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Grammar Variational AutoencoderPreprint

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Reinvent 4: Modern AI–driven generative molecule design

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GraphAF: a Flow-based Autoregressive Model for Molecular Graph GenerationPreprint

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

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

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Reinforced Adversarial Neural Computer for de Novo Molecular Design

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AI in drug discovery and its clinical relevance

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Deep Reinforcement Learning for Multiparameter Optimization in de novo Drug Design

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Grammatical error correction using neural machine translation

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Adversarial Threshold Neural Computer for Molecular de Novo Design

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Generative molecular design in low data regimes

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Conditional Molecular Design with Deep Generative Models

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Exploring the GDB-13 chemical space using deep generative models

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Graph neural networks for automated de novo drug design

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Evaluation guidelines for machine learning tools in the chemical sciences

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MELLODDY: Cross-pharma Federated Learning at Unprecedented Scale Unlocks Benefits in QSAR without Compromising Proprietary Information

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

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AI in small-molecule drug discovery: a coming wave?

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De Novo Molecular Design by Combining Deep Autoencoder Recurrent Neural Networks with Generative Topographic Mapping

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The drug-maker's guide to the galaxy

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Discovery of Highly Potent, Selective, and Orally Efficacious p300/CBP Histone Acetyltransferases Inhibitors

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

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A Grammar-Based Structural CNN Decoder for Code Generation

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De Novo Design of New Chemical Entities for SARS-CoV-2 Using Artificial Intelligence

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Chemical Space Mimicry for Drug Discovery

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A new paradigm for drug development

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