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Integration of virtual screening into the drug discovery process
D N Chin1, C E Chuaqui, J Singh
1Computational Drug Design Group, Biogen Idec, Inc, 14 Cambridge Center, Cambridge, MA 02142, USA.
Mini Reviews in Medicinal Chemistry
|December 8, 2004
Summary
High-throughput virtual screening methods, including docking and predictive ADME, are advancing drug discovery. While docking identifies novel compounds, predictive ADME requires further validation for broader application.
Area of Science:
- Computational chemistry
- Drug discovery
- Bioinformatics
Background:
- High-throughput virtual screening (HTVS) is crucial for identifying drug candidates.
- Integrating computational methods like docking and ADME prediction accelerates the screening process.
- The synergy between informatics and high-performance computing enhances HTVS capabilities.
Purpose of the Study:
- To review recent advances in HTVS.
- To highlight the role of docking and predictive ADME in drug discovery.
- To discuss the integration of informatics and high-performance computing in HTVS.
Main Methods:
- Review of docking approaches for compound identification.
- Analysis of predictive ADME (Absorption, Distribution, Metabolism, and Excretion) methods.
- Examination of informatics and high-performance computing integration in HTVS.
Main Results:
- Docking methods have successfully identified novel active compounds.
- Predictive ADME methods show improvement with broader training sets but need more validation.
- Integration of computational tools enhances screening efficiency.
Conclusions:
- HTVS, powered by docking and predictive ADME, shows significant promise in drug discovery.
- Further validation of predictive ADME models is essential for reliable application.
- The combined power of computational approaches offers a path to accelerated drug development.