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Strategy of computer-aided drug design
1V. N. Orekhovich Institute of Biomedical Chemistry, Russian Academy of Medical Science, Pogodinskaya str., 10, Moscow, 119121, Russia. veselov@ibmh.msk.su
Current Drug Targets. Infectious Disorders
|February 7, 2003
Summary
Computer-aided drug design (CADD) accelerates the discovery and optimization of new drug compounds. This review covers structure-based and ligand-based CADD methods, including de novo design and database mining for drug development.
Area of Science:
- Medicinal Chemistry
- Computational Chemistry
- Drug Discovery
Background:
- Computer-aided drug design (CADD) is crucial for accelerating the drug discovery pipeline.
- CADD strategies focus on identifying novel lead compounds and optimizing their structures for pharmacological testing.
Purpose of the Study:
- To review modern strategies in computer-aided drug design (CADD).
- To discuss the interrelationship between different CADD approaches.
- To explore new avenues and future perspectives in CADD.
Main Methods:
- Structure-based drug design (SBDD) when the target macromolecule's 3D structure is known.
- Ligand-based drug design (LBDD) using known ligand structures when the target structure is unknown.
- Molecule de novo design and database mining.
Main Results:
- CADD significantly speeds up the identification and optimization of potential drug candidates.
- Both SBDD and LBDD are vital, with their interrelationship being key to effective drug design.
- Methods like molecular docking, pharmacophore design, and quantitative structure-activity relationship (QSAR) modeling are central to CADD.
Conclusions:
- CADD is an indispensable tool in modern drug discovery, offering diverse strategies for lead identification and optimization.
- The integration of various CADD approaches, including de novo design and database mining, enhances efficiency.
- Future perspectives in CADD promise further advancements in developing novel therapeutics.