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.
Keywords: Quantum mechanics, predictive ADME, ADME/tox, ADMET, solubility, metabolism, elimination, toxicity, cytochrome P450, CYP isoenzymes, ab initio calculations, DFT, AM1, QM/MM, AMBER, CHARMM, MMFF, molecular mechanics, drug design, curcumin, curcumin derivatives, angiogenesis, angiogenic inhibitors.
Current Topics in Medicinal Chemistry
Title:A Perspective on Quantum Mechanics Calculations in ADMET Predictions
Volume: 13 Issue: 11
Author(s): J. Phillip Bowen and Osman F. Guner
Affiliation:
Keywords: Quantum mechanics, predictive ADME, ADME/tox, ADMET, solubility, metabolism, elimination, toxicity, cytochrome P450, CYP isoenzymes, ab initio calculations, DFT, AM1, QM/MM, AMBER, CHARMM, MMFF, molecular mechanics, drug design, curcumin, curcumin derivatives, angiogenesis, angiogenic inhibitors.
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.
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Cite this article as:
Bowen Phillip J. and Guner F. Osman, A Perspective on Quantum Mechanics Calculations in ADMET Predictions, Current Topics in Medicinal Chemistry 2013; 13 (11) . https://dx.doi.org/10.2174/15680266113139990032
DOI https://dx.doi.org/10.2174/15680266113139990032 |
Print ISSN 1568-0266 |
Publisher Name Bentham Science Publisher |
Online ISSN 1873-4294 |
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