Current trends in virtual high throughput screening using ligand-based and structure-based methods.

Area of Science:

• Computational Biology and Medicinal Chemistry
• Drug Discovery and Development

Background:

• High throughput in silico methods aim to accelerate the lengthy and costly drug discovery process.
• Despite decades of effort, many computational methods have not fully realized their potential.
• Structure-based modeling is crucial, leveraging target structure and protein-ligand interactions.

Purpose of the Study:

• To review recent advancements in structure-based and ligand-based drug design methodologies.
• To highlight applications and case studies of Virtual High Throughput Screening (VHTS).
• To discuss current research and limitations of these computational approaches.

Main Methods:

• Structure-based drug design (SBDD) utilizes target 3D structure (crystallography, spectroscopy, bioinformatics).
• Ligand-based drug design (LBDD) uses known active molecule chemistry.
• Target-based chemogenomics integrated into VHTS.

Main Results:

• Review of recent methodological developments in SBDD and LBDD.
• Presentation of case studies demonstrating VHTS applications.
• Discussion of ongoing research for further method development.

Conclusions:

• Structure-based and ligand-based methods are integral to modern drug discovery.
• VHTS offers a powerful platform for screening potential drug candidates.
• Understanding limitations is key for future advancements in computational drug design.