Quantifying the chemical beauty of drugs

Abstract

Druglikeness is a key consideration when selecting compounds during the early stages of drug discovery. However, evaluation of druglikeness in absolute terms does not adequately reflect the whole spectrum of compound quality. More worryingly, widely used rules may inadvertently foster undesirable molecular property inflation as they permit the encroachment of rule-compliant compounds toward their boundaries. We propose a measure of druglikeness based on the concept of desirability called Quantitative Estimate of Druglikeness (QED). The empirical rationale of QED reflects the underlying distribution of molecular properties. QED is intuitive, transparent, straightforward to implement in many practical settings and allows compounds to be ranked by their relative merit. We extend the utility of QED by applying it to the problem of molecular target druggability assessment by prioritizing a large set of published bioactive compounds. The measure may also capture the abstract notion of aesthetics in medicinal chemistry.The concept of druglikeness provides useful guidelines for early stage drug discovery 1, 2 . Analysis of the observed distribution of some key physicochemical properties of approved drugs, including molecular weight, hydrophobicity and polarity, reveals they preferentially occupy a relatively narrow range of possible values 3 . Compounds that fall within this range are described as "druglike." Note that this definition holds in the absence of any obvious structural similarity to an approved drug. It has been shown that preferential selection of druglike compounds increases the likelihood of surviving the well-documented high rates of attrition in drug discovery 4 .Druglikeness can be rationalized by consideration of how simple physicochemical properties impact molecular behavior in vivo, with particular respect to solubility, permeability, metabolic stability and transporter effects. Indeed druglikeness is often used as a proxy for Correspondence should be addressed to A.L.H. (a.hopkins@dundee.ac.uk).. Additional InformationSupplementary information is available online at XXXX. We have implemented QED as simple functions in Python, SQL (Structure Query Language), Accelrys Pipeline Pilot and Microsoft Excel, the codes for which are available in the Supplementary Information. The Microsoft Excel example also includes data on the 771 oral drugs used to derive the desirability functions. Pre-calculated QED values and desirability functions for 657,736 compounds from ChEMBL (release ChEMBL09) are also available. Author contributions Europe PMC Funders Author ManuscriptsEurope PMC Funders Author Manuscripts oral bioavailability. However, druglikeness provides a broad composite descriptor that implicitly captures several criteria, with bioavailability amongst the most prominent.In practical terms, assessment of druglikeness is most commonly manifested as rules, the original and most well known of which is Lipinski's Rule of Five (Ro5) 5 . The rule states that a compound is more likely to exhibit poor a...

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