<i>De novo</i> generated combinatorial library design-Reference-Cited by-同舟云学术

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De novo generated combinatorial library design

Published:2024 Issue:1 Volume:3 Page:122-135
ISSN:2635-098X
Container-title:Digital Discovery
language:en
Short-container-title:Digital Discovery

Author:

Johansson Simon Viet¹²^ORCID,Haghir Chehreghani Morteza²^ORCID,Engkvist Ola¹²^ORCID,Schliep Alexander²³^ORCID

Affiliation:

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

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

3. Faculty of Health Sciences, Brandenburg University of Technology Cottbus-Senftenberg, Cottbus, Germany

Abstract

We introduce a framework for library design for de novo generated molecules, with consideration for availability of building blocks.

Funder

Knut och Alice Wallenbergs Stiftelse

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/DD/D3DD00095H

Reference124 articles.

1. QSAR without borders

2. Exploring QSAR models for activity-cliff prediction

3. Molecular de-novo design through deep reinforcement learning

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

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