DecoyFinderNetAna: Application of Graph Convolution Neural Networks for Accurate Classification of True Small Molecule Binders from their Decoys

DecoyFinderNetAna demonstrates strong potential as a reliable early-stage screening tool in the drug discovery pipeline. By accurately eliminating decoys prior to docking, it streamlines the workflow and enhances the precision of downstream in silico validation processes.

Authors

Avinash Mishra (ORCID: https://orcid.org/0000-0003-4125-6670)
Parveen Punia
Priyasha Maitra (ORCID: https://orcid.org/0009-0008-0179-5809)
Shreyansh Suyash
Manjusha Govindh
Akshat Jha

Institutions

Shree Guru Gobind Singh Tricentenary University (IN)
Maharshi Dayanand University (IN)

Publication Details

Journal: Current Computer - Aided Drug Design
Published: 2026-02-23
DOI: https://doi.org/10.2174/0115734099429333260113070143
Primary Topic: Computational Drug Discovery Methods
Type: article
Field-Weighted Citation Impact: 0.00

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article

DecoyFinderNetAna: Application of Graph Convolution Neural Networks for Accurate Classification of True Small Molecule Binders from their Decoys

Avinash Mishra, Parveen Punia, Priyasha Maitra, Shreyansh Suyash et al.

Feb 23, 2026

Current Computer - Aided Drug Design

Computational Drug Discovery Methods

article

DecoyFinderNetAna: Application of Graph Convolution Neural Networks for Accurate Classification of True Small Molecule Binders from their Decoys

Avinash Mishra, Parveen Punia, Priyasha Maitra, Shreyansh Suyash, Manjusha Govindh, Akshat Jha

February 23, 2026article en

Abstract

DecoyFinderNetAna demonstrates strong potential as a reliable early-stage screening tool in the drug discovery pipeline. By accurately eliminating decoys prior to docking, it streamlines the workflow and enhances the precision of downstream in silico validation processes.

Current Computer - Aided Drug DesignVol. 22

Shree Guru Gobind Singh Tricentenary University (IN), Maharshi Dayanand University (IN)

Openalex Percentile: Top 39%

Computational Drug Discovery Methods

DOI Source OpenAlex

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