Targeting CAPON to modulate the CAPON–NOS Axis: a computational approach

The carboxy-terminal PDZ ligand of neuronal nitric oxide synthase (CAPON) serves as a critical regulatory protein controlling nitric oxide (NO) signaling across multiple physiological and pathological processes which encompass neurological, cardiac and metabolic functions. These diverse physiological roles of CAPON marks it as a key therapeutic target for conditions associated with its dysregulation. Despite this therapeutic potential there are no specific CAPON or nNOS/CAPON modulators which have been developed to date, highlighting a significant gap in targeted drug discovery. Herein, we report the first strategy specifically focused on disrupting the nNOS/CAPON protein-protein interface. Through screening of a chemical library composed of 4.6 million compounds and 13 molecular dynamics simulations, nine potential hit compounds were identified. This work represents a foundational step toward developing targeted therapies for CAPON-mediated disorders. Beyond identifying these promising hits, our approach introduces three python-based drug discovery tools: (i) a Python-based toolset for NMR structural analysis, clustering and visualization, (ii) accelerated ligand preparation toolkit, (iii) Automated hit prioritization pipeline based on multi-method consensus scoring approach that takes in account docking scores and MMGBSA. Collectively, these tools form an accelerated drug discovery pipeline that automates most of the virtual screening process and offers a scalable computational framework to support future drug discovery targeting protein-protein interactions.

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Publication Details

Journal
Computational and Structural Biotechnology Journal
Published
2025-01-01
DOI
https://doi.org/10.1016/j.csbj.2025.11.001
Citations
1
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
1.50
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article

Targeting CAPON to modulate the CAPON–NOS Axis: a computational approach

Hossam Nada, Moustafa T. Gabr, Gerhard Wolber
1 citations
Computational and Structural Biotechnology Journal
Computational Drug Discovery Methods
1.50
article

Targeting CAPON to modulate the CAPON–NOS Axis: a computational approach

Hossam Nada, Moustafa T. Gabr, Gerhard Wolber
article en
1 citations

Abstract

The carboxy-terminal PDZ ligand of neuronal nitric oxide synthase (CAPON) serves as a critical regulatory protein controlling nitric oxide (NO) signaling across multiple physiological and pathological processes which encompass neurological, cardiac and metabolic functions. These diverse physiological roles of CAPON marks it as a key therapeutic target for conditions associated with its dysregulation. Despite this therapeutic potential there are no specific CAPON or nNOS/CAPON modulators which have been developed to date, highlighting a significant gap in targeted drug discovery. Herein, we report the first strategy specifically focused on disrupting the nNOS/CAPON protein-protein interface. Through screening of a chemical library composed of 4.6 million compounds and 13 molecular dynamics simulations, nine potential hit compounds were identified. This work represents a foundational step toward developing targeted therapies for CAPON-mediated disorders. Beyond identifying these promising hits, our approach introduces three python-based drug discovery tools: (i) a Python-based toolset for NMR structural analysis, clustering and visualization, (ii) accelerated ligand preparation toolkit, (iii) Automated hit prioritization pipeline based on multi-method consensus scoring approach that takes in account docking scores and MMGBSA. Collectively, these tools form an accelerated drug discovery pipeline that automates most of the virtual screening process and offers a scalable computational framework to support future drug discovery targeting protein-protein interactions.

Computational and Structural Biotechnology JournalVol. 27
Cornell University (US), Molecular Innovations (United States) (US), Weill Cornell Medicine (US), Freie Universität Berlin (DE)
Openalex Percentile: Top 12%
Computational Drug Discovery Methods
1.50
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