Unveiling molecular moieties through hierarchical Grad-CAM graph explainability

Our approach may represent a valid support to shorten both the screening and the hit discovery process. Detailed knowledge of the molecular substructures that play a role in the binding process can help the computational chemist to gain insights into the structure optimization, as well as in drug repurposing tasks.

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Publication Details

Journal
BMC Bioinformatics
Published
2025-10-23
DOI
https://doi.org/10.1186/s12859-025-06208-y
Citations
2
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
3.01
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article

Unveiling molecular moieties through hierarchical Grad-CAM graph explainability

Roberto Pirrone, Salvatore Contino, Maria Rita Gulotta, Ugo Perricone et al.
2 citations
BMC Bioinformatics
Computational Drug Discovery Methods
3.01
article

Unveiling molecular moieties through hierarchical Grad-CAM graph explainability

Roberto Pirrone, Salvatore Contino, Maria Rita Gulotta, Ugo Perricone, Paolo Sortino
article en
2 citations

Abstract

Our approach may represent a valid support to shorten both the screening and the hit discovery process. Detailed knowledge of the molecular substructures that play a role in the binding process can help the computational chemist to gain insights into the structure optimization, as well as in drug repurposing tasks.

BMC BioinformaticsVol. 26(1)
Ri.MED (IT), University of Palermo (IT)
Openalex Percentile: Top 7%
Computational Drug Discovery Methods
3.01
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