title: A perspective on quantum mechanics calculations in ADMET predictions.
abstract: Understanding the molecular basis of drug action has been an important objective for pharmaceutical scientists. With the increasing speed of computers and the implementation of quantum chemistry methodologies, pharmacodynamic and pharmacokinetic problems have become more computationally tractable. Historically the former has been the focus of drug design, but within the last two decades efforts to understand the latter have increased. It takes about fifteen years and over $1 billion dollars for a drug to go from laboratory hit, through lead optimization, to final approval by the U.S. Food and Drug Administration. While the costs have increased substantially, the overall clinical success rate for a compound to emerge from clinical trials is approximately 10%. Most of the attrition rate can be traced to ADMET (absorption, distribution, metabolism, excretion, and toxicity) problems, which is a powerful impetus to study these issues at an earlier stage in drug discovery. Quantum mechanics offers pharmaceutical scientists the opportunity to investigate pharmacokinetic problems at the molecular level prior to laboratory preparation and testing. This review will provide a perspective on the use of quantum mechanics or a combination of quantum mechanics coupled with other classical methods in the pharmacokinetic phase of drug discovery. A brief overview of the essential features of theory will be discussed, and a few carefully selected examples will be given to highlight the computational methods.
authors.affiliation: Center 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
authors.forename: J Phillip
authors.initials: JP
authors.lastname: Bowen
authors.forename: Osman F
authors.initials: OF
authors.lastname: Güner
mesh_terms: D001682:Biological Availability; D017277:Drug Approval; D015195:Drug Design; D055808:Drug Discovery; D004353:Drug Evaluation, Preclinical / Q000379:methods*; D015507:Drugs, Investigational / Q000493:pharmacokinetics* / Q000494:pharmacology; D006801:Humans; D056004:Molecular Dynamics Simulation; D011789:Quantum Theory; D013329:Structure-Activity Relationship
chemical_list: D015507:Drugs, Investigational