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Hierarchical Virtual Screening Based on Rocaglamide Derivatives to Discover New Potential Anti-Skin Cancer Agents.

Igor V F Dos Santos^1,2, Rosivaldo S Borges^1,3, Guilherme M Silva^4,5

¹Modeling and Computational Chemistry Laboratory, Federal University of Amapá, Macapá, Brazil.

Frontiers in Molecular Biosciences

|June 20, 2022

Summary

This study explored natural compounds for skin cancer (SC) treatment. Virtual screening identified 10 promising molecules, derived from Rocaglamide A, as potential new anti-SC agents for further research.

Keywords:

anticancer activity hierarchical virtual screening pharmacophore rocaglamide skin cancer

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Area of Science:

Medicinal Chemistry
Computational Drug Discovery
Oncology

Background:

Skin cancer (SC) is a prevalent global cancer.
Natural products, like Rocaglamide A (Roc-A), show potential as SC therapeutics.
Molecular modeling offers a promising strategy for discovering novel SC treatments.

Purpose of the Study:

To identify novel chemical entities with potential anti-skin cancer activity.
To virtually screen Roc-A derivatives against skin cancer targets.
To develop and validate pharmacophore models for drug discovery.

Main Methods:

Hierarchical virtual screening of Roc-A derivatives.
Molecular docking studies against Checkpoint kinase 1 (Chk1).
Pharmacophore model development and validation.
Prospective virtual screening against the Molport database.
Toxicity, pharmacokinetic, and consensus molecular docking analyses.

Main Results:

15 Roc-A molecules were used for initial docking and model building.
Pharmacophore models were validated using Pearson's correlation and HCA.
Prospective screening yielded 10 promising compounds similar to Roc-A.
Selected compounds demonstrated favorable predicted properties and structural features.

Conclusions:

The 10 identified compounds represent potential novel anti-skin cancer agents.
Further biological testing is warranted to confirm their therapeutic efficacy.
This study highlights the utility of virtual screening in natural product-based drug discovery for SC.