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Published on: November 11, 2016
Computational analysis of CCN1 as a druggable target predicts interactions with bioactive compounds
Roudy Bou Francis1, Racha Kerek1, Mohamad Rima2
1Department of Biological Sciences, Lebanese American University, Byblos, Lebanon.
This study computationally assesses the druggability of the CCN1 protein, a key player in aging and disease. It identifies Metformin and other compounds as potential modulators, offering a new avenue for drug discovery.
Area of Science:
- Biochemistry and Molecular Biology
- Computational Drug Discovery
- Genomics
Background:
- CCN1 is a multifunctional protein implicated in aging, fibrosis, inflammation, and cancer.
- Its complex roles make it a significant target for therapeutic intervention.
- Assessing CCN1's druggability is crucial for developing targeted therapies.
Purpose of the Study:
- To computationally evaluate the druggability of the CCN1 protein.
- To identify potential small molecule modulators of CCN1 activity.
- To establish a scalable workflow for CCN1-targeted drug screening.
Main Methods:
- Predicted CCN1 3D structure using AlphaFold 3.
- Identified binding pockets using Fpocket.
- Assessed ligand affinity with SwissDock molecular docking.
Main Results:
- Identified multiple high-confidence druggable pockets in CCN1.
- Top pocket located between TSP-1 and CTCK domains.
- Metformin showed highest predicted affinity (-200.26 SwissDock AC score).
- Interactions remained stable across CCN1 variants and pocket deletions, confirming genetic robustness.
Conclusions:
- CCN1 is a druggable target with potential for therapeutic modulation.
- Metformin and other compounds show promise for targeting CCN1 in aging and disease.
- The developed in silico workflow enables rapid screening of CCN1-targeted therapeutics.
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