Journal
BIOORGANIC & MEDICINAL CHEMISTRY
Volume 20, Issue 18, Pages 5343-5351Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.bmc.2011.11.064
Keywords
Lipinski Rules; Soft Rule of Five; Utility functions; Analytic hierarchy process; Drug likeness; Decision theory; Molecular properties
Funding
- National Institute Of Mental Health [RC2MH090878]
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In order to improve the discovery and development of new drugs, a broad effort is being made to assess the 'drug-like' properties of molecules in early stages of the discovery-research process. Although there are numerous approaches to this problem, perhaps the simplest and most widespread one is that developed by Chris Lipinski and his co-workers at Pfizer, which is generally referred either as the Lipinski Rules or the Rule of Five (ROF). The ROF is based on four properties of molecules, namely, molecular weight (MW), logP, number of hydrogen bond donors (HBD), and the number of hydrogen bond acceptors (HBA). A 'flag' is set if the value of a given property exceeds the chosen threshold value for that property-MW 500 Da, logP 5, the number of HBDs 5, and the number of HBAs 10. Each flag corresponds to an ROF violation. The total number of violations is the ROF-Score, which lies between '0' and '4'. Molecules with ROF-Scores greater than one are considered to be marginal for further development. The difficulty with this approach is that two molecules with nearly identical property values can, nonetheless, possess ROF-Scores that can differ by two or more. Thus, one molecule could be considered for further studies while the other, nearly identical molecule (in terms of its four ROF properties), would most likely not be. This problem arises because of the sharp thresholds imposed by the present formulation of the ROF, which is based upon classical sets. In the current work an alternative approach based on the use of utility functions, within the framework of the analytic hierarchy process (AHP), are employed to 'soften' the sharp boundaries inherent in classical sets. This provides a more realistic assessment of compounds in terms of their potential suitability in drug-discovery research programs. (C) 2011 Elsevier Ltd. All rights reserved.
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