Computational Docking and Solid Lipid Nanoparticle Formulation of Novel Isoquinoline Derivatives for Anticancer Therapy

This study investigates the anticancer potential of novel isoquinoline derivatives through computational docking and solid lipid nanoparticle (SLN) formulation. Computational docking was performed to predict the binding affinity of these derivatives against key cancer-related protein targets, providing insights into their molecular interactions and therapeutic potential. Following docking, SLNs were formulated to enhance solubility, stability, and targeted delivery of the derivatives. Results indicate promising binding interactions and efficient encapsulation within SLNs, suggesting potential for improved anticancer efficacy. This integrative approach combines in silico predictions with nanotechnology to advance novel drug candidates.

Publication Details

Journal
Journal of Carcinogenesis
Published
2025-01-01
DOI
https://doi.org/10.64149/j.carcinog.24.7s.163-171
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00
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article

Computational Docking and Solid Lipid Nanoparticle Formulation of Novel Isoquinoline Derivatives for Anticancer Therapy

Journal of Carcinogenesis
Computational Drug Discovery Methods
article

Computational Docking and Solid Lipid Nanoparticle Formulation of Novel Isoquinoline Derivatives for Anticancer Therapy

article en

Abstract

This study investigates the anticancer potential of novel isoquinoline derivatives through computational docking and solid lipid nanoparticle (SLN) formulation. Computational docking was performed to predict the binding affinity of these derivatives against key cancer-related protein targets, providing insights into their molecular interactions and therapeutic potential. Following docking, SLNs were formulated to enhance solubility, stability, and targeted delivery of the derivatives. Results indicate promising binding interactions and efficient encapsulation within SLNs, suggesting potential for improved anticancer efficacy. This integrative approach combines in silico predictions with nanotechnology to advance novel drug candidates.

Journal of Carcinogenesis
Openalex Percentile: Top 72%
Computational Drug Discovery Methods
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