Galileo: Three-dimensional searching in large combinatorial fragment spaces on the example of pharmacophores

Author:

Meyenburg ChristianORCID,Dolfus UschiORCID,Briem HansORCID,Rarey MatthiasORCID

Abstract

AbstractFragment spaces are an efficient way to model large chemical spaces using a handful of small fragments and a few connection rules. The development of Enamine’s REAL Space has shown that large spaces of readily available compounds may be created this way. These are several orders of magnitude larger than previous libraries. So far, searching and navigating these spaces is mostly limited to topological approaches. A way to overcome this limitation is optimization via metaheuristics which can be combined with arbitrary scoring functions. Here we present Galileo, a novel Genetic Algorithm to sample fragment spaces. We showcase Galileo in combination with a novel pharmacophore mapping approach, called Phariety, enabling 3D searches in fragment spaces. We estimate the effectiveness of the approach with a small fragment space. Furthermore, we apply Galileo to two pharmacophore searches in the REAL Space, detecting hundreds of compounds fulfilling a HSP90 and a FXIa pharmacophore.

Funder

Universität Hamburg

Publisher

Springer Science and Business Media LLC

Subject

Physical and Theoretical Chemistry,Computer Science Applications,Drug Discovery

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. De novo drug design through artificial intelligence: an introduction;Frontiers in Hematology;2024-01-25

2. School of cheminformatics in Latin America;Journal of Cheminformatics;2023-09-19

3. Navigating large chemical spaces in early-phase drug discovery;Current Opinion in Structural Biology;2023-06

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