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WIREs Comput Mol Sci
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Understanding drug‐likeness

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Abstract ‘Drug‐likeness’, a qualitative property of chemicals assigned by experts committee vote, is widely integrated into the early stages of lead and drug discovery. Its conceptual evolution paralleled work related to Pfizer's ‘rule of five’ and lead‐likeness, and is placed within this framework. The discrimination between ‘drugs’ (represented by a collection of pharmaceutically relevant small molecules, some of which are marketed drugs) and ‘nondrugs’ (typically, chemical reagents) is possible using a wide variety of statistical tools and chemical descriptor systems. Here we summarize 18 papers focused on drug‐likeness, and provide a comprehensive overview of progress in the field. Tools that estimate drug‐likeness are valuable in the early stages of lead discovery, and can be used to filter out compounds with undesirable properties from screening libraries and to prioritize hits from primary screens. As the goal is, most often, to develop orally available drugs, it is also useful to optimize drug‐like pharmacokinetic properties. We examine tools that evaluate drug‐likeness and some of their shortcomings, challenges facing these tools, and address the following issues: What is the definition of drug‐likeness and how can it be utilized to reduce attrition rate in drug discovery? How difficult is it to distinguish drugs from nondrugs? Are nondrug datasets reliable? Can we estimate oral drug‐likeness? We discuss a drug‐like filter and recent advances in the prediction of oral drug‐likeness. The heuristic aspect of drug‐likeness is also addressed. © 2011 John Wiley & Sons, Ltd. WIREs Comput Mol Sci 2011 1 760–781 DOI: 10.1002/wcms.52 This article is categorized under: Computer and Information Science > Chemoinformatics

Examples of representative nonoverlapping fragments with up to five bonds radius having high frequencies in DRUGS (a), and available chemicals directory (b). The depicted fragments are highlighted according to their occurrence in DRUGS/ACD data sets.

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Distribution of the molecular properties of the low/high oral bioavailability drug‐like index (OB‐DLI) drugs, (a) molecular weight, (b) rings, and (c) rigid bonds.

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Oral bioavailability drug‐like index (OB‐DLI) values of 600 randomly selected molecules from two databases—300 chemicals from available chemicals directory (red squares) and 300 drugs from MDDR‐clinical (blue rectangles).

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Compounds that have an oral bioavailability drug‐like index (OB‐DLI) above a certain threshold are considered as potentially orally bioavailable drugs (OBDs) while others are nondrugs. Figure 2a demonstrates the change of MCC along the OB‐DLI axis while Figure 2b focuses on the enrichment factors along that axis.

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