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Computational science new horizons and relevance to pharmaceutical design
J M Briggs1, T J Marrone, J A McCammon
1Department of Pharmacology, University of California,San Diego, CA 92093-0365USA.
Trends in Cardiovascular Medicine
|January 15, 2011
Summary
Computational drug design methods, including QSAR and docking, accelerate pharmaceutical development. Advances in scoring and computational power enhance predictive accuracy for faster drug discovery.
Area of Science:
- Computational chemistry and medicinal chemistry.
- Drug discovery and pharmaceutical development.
Background:
- Computer-aided drug design (CADD) is integral to modern pharmaceutical research.
- Various computational techniques aid in identifying and optimizing drug candidates.
Purpose of the Study:
- To summarize computational methods used in drug lead design and refinement.
- To illustrate applications in designing drugs for the renin-angiotensin system and cholinergic synapses.
Main Methods:
- Quantitative Structure-Activity Relationship (QSAR) analysis.
- Comparative Molecular Field Analysis (CoMFA).
- 3D database searching, de novo ligand design, molecular docking, and computational alchemy (FEP, MCTI).
Main Results:
- These methods facilitate drug design with or without detailed binding site structural information.
- Commercial pharmaceutical design extensively utilizes these computational approaches.
- A key challenge lies in accurately scoring or ranking molecular interactions.
Conclusions:
- Further advancements in scoring, methods, and computational capabilities will improve predictive power.
- Enhanced computational drug design promises to accelerate the time-to-market for new pharmaceuticals.
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