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A desirability function-based scoring scheme for selecting fragment-like class A aminergic GPCR ligands

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An Erratum to this article was published on 14 November 2014

Abstract

A physicochemical property-based desirability scoring scheme for fragment-based drug discovery was developed for class A aminergic GPCR targeted fragment libraries. Physicochemical property distributions of known aminergic GPCR-active fragments from the ChEMBL database were examined and used for a desirability function-based score. Property-distributions such as log D (at pH 7.4), PSA, pKa (strongest basic center), number of nitrogen atoms, number of oxygen atoms, and the number of rotatable bonds were combined into a desirability score (FrAGS). The validation of the scoring scheme was carried out using both public and proprietary experimental screening data. The scoring scheme is suitable for the design of aminergic GPCR targeted fragment libraries and might be useful for preprocessing fragments before structure based virtual or wet screening.

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Abbreviations

FrAGS:

Fragment Aminergic GPCR Score

GPCR:

G-protein coupled receptor

PSA:

Polar surface area

FBDD:

Fragment-based drug discovery

HTS:

High-throughput screening

FS:

Fragment-screening

7TM:

Seven-transmembrane

SILE:

Size-independent ligand-efficiency

SMILES:

Simplified molecular-input line-entry system

EF:

Enrichment factor

TPR:

True positive rate

TNR:

True negative rate

FPR:

False positive rate

FNR:

False negative rate

ROC:

Receiver operating characteristic

TAAR1 :

Trace-amine receptor subtype 1

5HT1 :

5-Hydroxy-tryptamine receptor subtype 1

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Acknowledgments

We thank for Gedeon Richter Plc for providing GPCR-related fragment-screening and high-throughput screening data for the validation studies and particularly Márton Vass for helpful discussions.

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Authors and Affiliations

  1. Medicinal Chemistry Research Group, Research Centre for Natural Sciences, Hungarian Academy of Sciences, Magyar Tudósok Körútja 2, Budapest, 1117, Hungary

    Ádám A. Kelemen, György G. Ferenczy & György M. Keserű

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  1. Ádám A. Kelemen
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  2. György G. Ferenczy
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  3. György M. Keserű
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Correspondence to György M. Keserű.

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Kelemen, Á.A., Ferenczy, G.G. & Keserű, G.M. A desirability function-based scoring scheme for selecting fragment-like class A aminergic GPCR ligands. J Comput Aided Mol Des 29, 59–66 (2015). https://doi.org/10.1007/s10822-014-9804-5

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