Rapid traversal of vast chemical space using machine learning-guided docking screens

Luttens, Andreas; Vaca, Israel Cabeza de; Sparring, Leonard; Brea, José; Martínez, Antón L.; Kahlous, Nour Aldin; Radchenko, Dmytro S.; Moroz, Yurii S.; Loza, Marı́a Isabel; Norinder, Ulf; Carlsson, Jens

doi:10.1038/s43588-025-00777-x

articleNature Computational ScienceMar 13, 2025HYBRID OA

Rapid traversal of vast chemical space using machine learning-guided docking screens

ALAndreas Luttens ICIsrael Cabeza de Vaca LSLeonard Sparring JBJosé Brea ALAntón L. Martínez

Broad Institute · Uppsala University · +7 more institutions

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Abstract

The accelerating growth of make-on-demand chemical libraries provides unprecedented opportunities to identify starting points for drug discovery with virtual screening. However, these multi-billion-scale libraries are challenging to screen, even for the fastest structure-based docking methods. Here we explore a strategy that combines machine learning and molecular docking to enable rapid virtual screening of databases containing billions of compounds. In our workflow, a classification algorithm is trained to identify top-scoring compounds based on molecular docking of 1 million compounds to the target protein. The conformal prediction framework is then used to make selections from the multi-billion-scale…

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51

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Percentile: 100%
References: 56

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Topics & keywords

Topics

Keywords

Virtual screening
Workflow
Computer science
Docking (animal)
Drug discovery
Chemical space
Tree traversal
Classifier (UML)

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