Computer-aided molecular selection and design of natural bioactive molecules

Area of Science:

• Natural Product Chemistry
• Bioinformatics
• Drug Discovery

Background:

• Renewed interest in plant-derived compounds for novel therapeutics.
• Need for rational and efficient strategies to discover natural bioactive molecules.

Purpose of the Study:

• To describe a comprehensive strategy for the selection and design of natural bioactive compounds.
• To integrate ethnopharmacology with computational approaches for drug discovery.

Main Methods:

• Development of the Phytotech database integrating ethnopharmacological, chemical, and biological data.
• Application of bioinformatics for lead identification based on molecular and botanical diversity.
• Utilizing molecular modeling to understand protein/ligand interactions.
• Employing 2D- and 3D-QSAR for pharmacomodulation and activity optimization.

Main Results:

• Demonstration of a hybrid chemometric strategy for natural product discovery.
• Successful application in identifying and optimizing acetylcholinesterase inhibitors.

Conclusions:

• The proposed CAMSD strategy offers a coherent and global approach to natural bioactive molecule discovery.
• This integrated method enhances the efficiency of identifying and optimizing drug leads from natural sources.