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A perspective on quantum mechanics calculations in ADMET predictions
J Phillip Bowen1, Osman F Güner
1Center for Drug Design, Department of Pharmaceutical Sciences, College of Pharmacy and Health Sciences, Mercer University, 3001 Mercer University Drive, Atlanta, GA 30341, USA. bowen_jp@mercer.edu
Current Topics in Medicinal Chemistry
|May 17, 2013
Summary
Quantum mechanics aids drug discovery by analyzing pharmacokinetics at the molecular level. This computational approach helps predict absorption, distribution, metabolism, excretion, and toxicity (ADMET) issues early, reducing costly failures.
Area of Science:
- Computational chemistry
- Drug discovery
- Pharmacokinetics
Background:
- Drug development is lengthy, expensive, and has a low success rate.
- Attrition is often due to ADMET (absorption, distribution, metabolism, excretion, and toxicity) issues.
- Computational methods are increasingly used to address these challenges.
Purpose of the Study:
- To review the application of quantum mechanics in drug discovery.
- To highlight the use of quantum mechanics for pharmacokinetic analysis.
- To provide examples of computational methods in drug development.
Main Methods:
- Utilizing quantum mechanics (QM) for molecular-level analysis.
- Combining QM with classical computational methods.
- Reviewing theoretical aspects and case studies.
Main Results:
- Quantum mechanics can predict pharmacokinetic properties.
- Computational approaches can identify ADMET issues earlier.
- QM methods offer insights into molecular interactions relevant to drug behavior.
Conclusions:
- Quantum mechanics is a valuable tool for understanding pharmacokinetics.
- Early computational analysis of ADMET properties can improve drug discovery success rates.
- Integrating QM into drug discovery workflows can reduce costs and timelines.
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