LibINVENT: Reaction-based Generative Scaffold Decoration for in Silico Library Design-Reference-Cited by-同舟云学术

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LibINVENT: Reaction-based Generative Scaffold Decoration for in Silico Library Design

Published:2021-08-30 Issue: Volume: Page:
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Fialková Vendy¹,Zhao Jiaxi¹²,Papadopoulos Kostas¹,Engkvist Ola¹³^ORCID,Bjerrum Esben Jannik¹^ORCID,Kogej Thierry¹,Patronov Atanas¹^ORCID

Affiliation:

1. Molecular AI, Discovery Sciences, R&D, AstraZeneca, Gothenburg 43183, Sweden

2. Department of Pharmaceutical Biosciences, Uppsala University, Uppsala 75237, Sweden

3. Department of Computer Science and Engineering, Chalmers University of Technology, Gothenburg 41756, Sweden

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.1c00469

Reference59 articles.

1. Drug discovery with explainable artificial intelligence

2. Artificial intelligence in drug discovery and development

3. A Turing Test for Molecular Generators

4. Application of Generative Autoencoder inDe NovoMolecular Design

5. Advances and challenges in deep generative models for de novo molecule generation

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1. Effect of Data Quality and Data Quantity on the Estimation of Intrinsic Solubility: Analysis Based on a Single-Source Data Set;Molecular Pharmaceutics;2024-09-13

2. Optimal Molecular Design: Generative Active Learning Combining REINVENT with Precise Binding Free Energy Ranking Simulations;Journal of Chemical Theory and Computation;2024-09-03

3. Accelerated Discovery of Carbamate Cbl-b Inhibitors Using Generative AI Models and Structure-Based Drug Design;Journal of Medicinal Chemistry;2024-08-12

4. Evaluation of reinforcement learning in transformer-based molecular design;Journal of Cheminformatics;2024-08-08

5. ACEGEN: Reinforcement Learning of Generative Chemical Agents for Drug Discovery;Journal of Chemical Information and Modeling;2024-08-02

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