Virtual Screening of Peptide Libraries: The Search for Peptide-Based Therapeutics Using Computational Tools

Area of Science:

• Biochemistry
• Pharmacology
• Computational Biology

Background:

• Growing interest in peptides as therapeutics due to specificity and safety.
• Peptides are effective modulators of protein-protein interactions, targeting previously undruggable proteins.
• Peptide therapeutics offer advantages over small molecules for complex biological targets.

Purpose of the Study:

• To review challenges in peptide therapeutic development.
• To describe computational approaches, particularly structure-based virtual screening (SBVS), for identifying therapeutic peptides.
• To highlight applications of SBVS in discovering diverse bioactive peptides.

Main Methods:

• Review of existing literature on peptide therapeutics and computational screening.
• Focus on structure-based virtual screening (SBVS) strategies.
• Analysis of SBVS applications for various peptide classes.

Main Results:

• Identification of challenges in peptide therapeutic development.
• Demonstration of SBVS as an efficient and cost-effective in silico approach.
• Examples of successful SBVS applications for anticancer, antimicrobial, and anti-amyloid peptides.

Conclusions:

• Peptides are promising therapeutic agents, particularly for targeting protein-protein interactions.
• Structure-based virtual screening (SBVS) is a key computational tool for accelerating the discovery of novel therapeutic peptides.
• SBVS strategies are applicable across a range of therapeutic peptide classes, including anticancer and antimicrobial agents.