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

Overview of attention for article published in Perspectives in Drug Discovery and Design, October 2014
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Title
A desirability function-based scoring scheme for selecting fragment-like class A aminergic GPCR ligands
Published in
Perspectives in Drug Discovery and Design, October 2014
DOI 10.1007/s10822-014-9804-5
Pubmed ID
Authors

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

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.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 39%
Student > Master 3 17%
Student > Doctoral Student 2 11%
Student > Ph. D. Student 1 6%
Professor > Associate Professor 1 6%
Other 0 0%
Unknown 4 22%
Readers by discipline Count As %
Chemistry 6 33%
Agricultural and Biological Sciences 2 11%
Computer Science 2 11%
Biochemistry, Genetics and Molecular Biology 1 6%
Pharmacology, Toxicology and Pharmaceutical Science 1 6%
Other 0 0%
Unknown 6 33%