The freedom space – a new set of commercially available molecules for hit discovery

The advent of high-performance virtual screening techniques nowadays allows drug designers to explore ultra-large sets of candidate compounds in search of molecules predicted to have desired properties. However, the success of such an endeavor heavily relies on the pertinence (drug-likeness and, foremost, chemical feasibility) of these candidates, or otherwise, virtual screening will return valueless "hits", by the garbage in/garbage out principle. The huge popularity of the judiciously enumerated Enamine REAL Space is clear proof of the strength of this Big Data trend in drug discovery. Here we describe a new dataset of make-on-demand compounds called the Freedom space. It follows the principles of Enamine REAL Space and contains highly feasible molecules (synthesis success rate over 75 percent). However, the scaffold and chemography analysis revealed significant differences to both the REAL and biologically annotated compounds from the ChEMBL database. The Freedom Space is a significant extension of the REAL Space and can be utilized for a more comprehensive exploration of the synthetically feasible chemical space in hit finding and hit-to-lead campaigns.

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Publication Details

Journal
Molecular Informatics
Published
2024-08-22
DOI
https://doi.org/10.1002/minf.202400114
Citations
6
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
2.17
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article

The freedom space – a new set of commercially available molecules for hit discovery

Mykola Protopopov, Yurii S. Moroz, Gilles Marcou, Dragos Horvath et al.
6 citations
Molecular Informatics
Computational Drug Discovery Methods
2.17
article

The freedom space – a new set of commercially available molecules for hit discovery

Mykola Protopopov, Yurii S. Moroz, Gilles Marcou, Dragos Horvath, Fanny Bonachéra, Olga O. Tarkhanova, Olena Savych, Alexandre Varnek, Valentyna Tararina, Anna Kapeliukha, Erik Yeghyan, Igor M. Dzyuba, Oleksii Chuk, Serhii Hlotov, Olga Klimchuk
article en
6 citations

Abstract

The advent of high-performance virtual screening techniques nowadays allows drug designers to explore ultra-large sets of candidate compounds in search of molecules predicted to have desired properties. However, the success of such an endeavor heavily relies on the pertinence (drug-likeness and, foremost, chemical feasibility) of these candidates, or otherwise, virtual screening will return valueless "hits", by the garbage in/garbage out principle. The huge popularity of the judiciously enumerated Enamine REAL Space is clear proof of the strength of this Big Data trend in drug discovery. Here we describe a new dataset of make-on-demand compounds called the Freedom space. It follows the principles of Enamine REAL Space and contains highly feasible molecules (synthesis success rate over 75 percent). However, the scaffold and chemography analysis revealed significant differences to both the REAL and biologically annotated compounds from the ChEMBL database. The Freedom Space is a significant extension of the REAL Space and can be utilized for a more comprehensive exploration of the synthetically feasible chemical space in hit finding and hit-to-lead campaigns.

Molecular InformaticsVol. 43(12)
Taras Shevchenko National University of Kyiv (UA), Kyiv Academic University (UA), DigitalSpace (United States) (US), Enamine (Ukraine) (UA), Université de Strasbourg (FR)
Peace, Justice and strong institutions
Openalex Percentile: Top 11%
Computational Drug Discovery Methods
2.17
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