LibINVENT: Reaction-based Generative Scaffold Decoration for in Silico Library Design
Artikel i vetenskaplig tidskrift, 2022

Because of the strong relationship between the desired molecular activity and its structural core, the screening of focused, core-sharing chemical libraries is a key step in lead optimization. Despite the plethora of current research focused on in silico methods for molecule generation, to our knowledge, no tool capable of designing such libraries has been proposed. In this work, we present a novel tool for de novo drug design called LibINVENT. It is capable of rapidly proposing chemical libraries of compounds sharing the same core while maximizing a range of desirable properties. To further help the process of designing focused libraries, the user can list specific chemical reactions that can be used for the library creation. LibINVENT is therefore a flexible tool for generating virtual chemical libraries for lead optimization in a broad range of scenarios. Additionally, the shared core ensures that the compounds in the library are similar, possess desirable properties, and can also be synthesized under the same or similar conditions. The LibINVENT code is freely available in our public repository at https://github.com/MolecularAI/Lib-INVENT. The code necessary for data preprocessing is further available at: https://github.com/MolecularAI/Lib-INVENT-dataset.

Författare

Vendy Fialková

AstraZeneca AB

Jiaxi Zhao

AstraZeneca AB

Uppsala universitet

Kostas Papadopoulos

AstraZeneca AB

Ola Engkvist

AstraZeneca AB

Chalmers, Data- och informationsteknik

Esben Jannik Bjerrum

AstraZeneca AB

Thierry Kogej

AstraZeneca AB

Atanas Patronov

AstraZeneca AB

Journal of Chemical Information and Modeling

1549-9596 (ISSN) 1549960x (eISSN)

Vol. 62 9 2046-2063

Ämneskategorier

Rymd- och flygteknik

Organisk kemi

Datorsystem

DOI

10.1021/acs.jcim.1c00469

PubMed

34460269

Relaterade dataset

Lib Invent Dataset [dataset]

URI: https://github.com/MolecularAI/Lib-INVENT-dataset

Mer information

Senast uppdaterat

2024-07-27