Natural product databases for drug discovery: Features and applications

Area of Science:

• Medicinal Chemistry
• Bioinformatics
• Computational Drug Discovery

Background:

• Natural products (NPs) are vital for drug discovery due to their diverse structures and bioactivities.
• Computational approaches are increasingly important in natural drug discovery, with NP databases being central.
• Advancements in technology highlight the need for robust NP databases.

Purpose of the Study:

• To review the key features of natural product databases.
• To explore the applications of NP databases in drug discovery.
• To discuss challenges and future directions in NP database development.

Main Methods:

• Summarization of NP database features (structural data, properties, sources, pathways, interfaces).
• Review of NP database applications (virtual screening, knowledge graphs, molecular generation).
• Discussion on database development challenges (data quality, updates) and future strategies (collaboration, toolkit innovation).

Main Results:

• NP databases offer comprehensive data crucial for various drug discovery tasks.
• Effective utilization of NP databases can significantly accelerate the identification and modification of bioactive compounds.
• Database quality, continuous updating, team collaboration, and innovative toolkits are essential for maximizing NP database potential.

Conclusions:

• High-quality NP databases are indispensable tools for modern drug discovery.
• Strategic development and collaborative efforts are key to unlocking the full potential of NP databases.
• This review provides a framework for researchers to develop and maintain effective NP databases for drug discovery.