On the rise of AI technologies for virtual screening

Here we provide raw data to reproduce results presented in our recent manuscript "On the rise of AI technologies for virtual screening" submitted to JCIM. The data allow to: reproduce the ROC curves based on Boltz-2 predictions for all targets of the ULVSH dataset (ZIP) analyse the Boltz-2 classifications based on different sets of runtime parameters (XLS) explore the structural models predicted by Boltz-2 for all protein-ligand complexes of the ULVSH dataset (pymol sessions, PSE)

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-12-03
DOI
https://doi.org/10.5281/zenodo.17804167
Primary Topic
Machine Learning in Bioinformatics
Type
article
Field-Weighted Citation Impact
0.00
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article

On the rise of AI technologies for virtual screening

Zenodo (CERN European Organization for Nuclear Research)
Machine Learning in Bioinformatics
article

On the rise of AI technologies for virtual screening

article en

Abstract

Here we provide raw data to reproduce results presented in our recent manuscript "On the rise of AI technologies for virtual screening" submitted to JCIM. The data allow to: reproduce the ROC curves based on Boltz-2 predictions for all targets of the ULVSH dataset (ZIP) analyse the Boltz-2 classifications based on different sets of runtime parameters (XLS) explore the structural models predicted by Boltz-2 for all protein-ligand complexes of the ULVSH dataset (pymol sessions, PSE)

Zenodo (CERN European Organization for Nuclear Research)
Université de Strasbourg (FR)
Openalex Percentile: Top 38%
Machine Learning in Bioinformatics
DOIOpen Access PDFOpenAlex
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On the rise of AI technologies for virtual screening · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS