Chemical Structure Similarity Search for Ligand-based Virtual Screening: Methods and Computational Resources

Area of Science:

• Computational Chemistry
• Cheminformatics
• Drug Discovery

Background:

• The principle of "similar structures, similar activities" is fundamental to lead identification.
• Chemical similarity can be assessed using topological, steric, electronic, or physical properties.
• Traditional substructure searches can be accelerated by fragment-based pre-screening, unlike similarity searches.

Purpose of the Study:

• To review recent progress in high-performance computing (HPC)-supported 2D and 3D chemical structure similarity search algorithms.
• To highlight the applications of these algorithms in ligand-based virtual screening.

Main Methods:

• Discussion of computational techniques for 2D chemical structure similarity assessment.
• Overview of algorithms for 3D similarity search, including conformational analysis.
• Emphasis on the role of High-Performance Computing (HPC) in accelerating these searches.

Main Results:

• HPC significantly enhances the speed and feasibility of complex 2D and 3D similarity searches.
• Advancements enable more efficient screening of large chemical libraries.
• Improved algorithms reduce computational bottlenecks in virtual screening.

Conclusions:

• HPC-supported similarity search algorithms are crucial for modern drug discovery.
• These techniques facilitate effective ligand-based virtual screening.
• Continued development in HPC is vital for advancing chemical informatics and lead identification.