Structure-based drug design: from nucleic acid to membrane protein targets

Area of Science:

• Computational chemistry and drug discovery.
• Bioinformatics and cheminformatics.
• Molecular biology and pharmacology.

Background:

• In silico methods are crucial for modern drug discovery.
• Advancements in computing power enhance virtual screening capabilities.
• Nucleic acids and G-protein coupled receptors (GPCRs) are key therapeutic targets.

Purpose of the Study:

• To review in silico drug discovery efforts for novel anti-cancer agents.
• To highlight the application of virtual screening against neglected targets like nucleic acids.
• To discuss molecular modeling and virtual screening of GPCRs.

Main Methods:

• Utilizing a novel distributed computing grid for enhanced virtual screening.
• Employing both receptor-based and ligand-based virtual screening approaches.
• Applying molecular modeling techniques to understand receptor structures.

Main Results:

• Demonstrated enhanced virtual screening capabilities through distributed computing.
• Identified potential anti-cancer agents by screening diverse targets.
• Explored the potential of targeting various DNA structures (duplex, triplex, quadruplex).

Conclusions:

• In silico methods, powered by advanced computing, significantly boost drug discovery.
• Virtual screening offers a powerful strategy for identifying novel anti-cancer therapeutics.
• Targeting nucleic acids and GPCRs represents a promising frontier in drug development.