Abstract
BackgroundThe design of chemical libraries, an early step in agrochemical discovery programs, is frequently addressed by means of qualitative physicochemical and/or topological rule-based methods. The aim of this study is to develop quantitative estimates of herbicide- (QEH), insecticide- (QEI), fungicide- (QEF), and, finally, pesticide-likeness (QEP).In the assessment of these definitions, we relied on the concept of desirability functions.ResultsWe found a simple function, shared by the three classes of pesticides, parameterized particularly, for six, easy to compute, independent and interpretable, molecular properties: molecular weight, logP, number of hydrogen bond acceptors, number of hydrogen bond donors, number of rotatable bounds and number of aromatic rings. Subsequently, we describe the scoring of each pesticide class by the corresponding quantitative estimate. In a comparative study, we assessed the performance of the scoring functions using extensive datasets of patented pesticides.ConclusionsThe hereby-established quantitative assessment has the ability to rank compounds whether they fail well-established pesticide-likeness rules or not, and offer an efficient way to prioritize (class-specific) pesticides. These findings are valuable for the efficient estimation of pesticide-likeness of vast chemical libraries in the field of agrochemical discovery.Electronic supplementary materialThe online version of this article (doi:10.1186/s13321-014-0042-6) contains supplementary material, which is available to authorized users.
Highlights
The design of chemical libraries, an early step in agrochemical discovery programs, is frequently addressed by means of qualitative physicochemical and/or topological rule-based methods
Three main classes of pesticides are considered i.e., herbicides, insecticides and fungicides, and, we describe the quantitative estimate of herbicide-likeness (QEH), of insecticidelikeness (QEI) and of fungicide-likeness (QEF)
We sought to find a type of function that would accurately fit distributions resulted from molecular properties describing herbicides, insecticides and fungicides
Summary
The design of chemical libraries, an early step in agrochemical discovery programs, is frequently addressed by means of qualitative physicochemical and/or topological rule-based methods. In order to conduct effectively a drug/agrochemical discovery program, a screening library should contain compounds displaying reasonable properties to ease the passage to final products. Lipinski’s rule of five (Ro5) is considered to be the reference in defining physicochemical and structural properties profiles for optimal bioavailability of drug candidates [3]. Molecules that would obey these rules should exert acceptable solubility and cell permeability properties and were defined as ‘drug-like’ [3]. Other simplified rule-based definitions of druglikeness were established by Veber [9] and Ghose [10]
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