Future De Novo Drug Design.

Area of Science:

• Computational chemistry and cheminformatics
• Drug discovery and development
• Medicinal chemistry

Background:

• Computer-assisted generation of new chemical entities (NCEs) is a mature technology.
• Ligand- and receptor-based methods are widely used in designing molecules.
• Polypharmacology prediction tools are crucial for multi-target drug design.

Purpose of the Study:

• To highlight the advancements in computer-assisted drug discovery.
• To emphasize the role of polypharmacology in designing molecules with multiple activities.
• To discuss the integration of iterative design-synthesis-test cycles and lab-on-a-chip platforms for efficient NCE identification.

Main Methods:

• Utilizing ligand- and receptor-based computational methods for molecular design.
• Employing advanced polypharmacology prediction tools.
• Integrating iterative design-synthesis-test cycles with automated platforms.

Main Results:

• Computer-assisted methods effectively support early drug discovery.
• Design of small, lead- and druglike molecules with multi-target activities is feasible.
• Iterative cycles rapidly identify NCEs with desired profiles.

Conclusions:

• Computer-assisted NCE generation is a robust technology for drug discovery.
• Polypharmacology and iterative design-synthesis-test cycles are vital components.
• Future drug discovery will likely involve lab-on-a-chip platforms and adaptive de novo design software.