A Taxicab geometry quantification system to evaluate the performance of in silico methods: a case study on adenosine receptors ligands

Kamil J Kuder,Katarzyna Kieć-Kononowicz,Peter Kolb,Ilona Michalik

doi:10.1007/s10822-020-00301-5

Kamil J Kuder, Katarzyna Kieć-Kononowicz + Show 2 more

Open Access

https://doi.org/10.1007/s10822-020-00301-5

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Abstract

Among still comparatively few G protein-coupled receptors, the adenosine A2A receptor has been co-crystallized with several ligands, agonists as well as antagonists. It can thus serve as a template with a well-described orthosteric ligand binding region for adenosine receptors. As not all subtypes have been crystallized yet, and in order to investigate the usability of homology models in this context, multiple adenosine A1 receptor (A1AR) homology models had been previously obtained and a library of lead-like compounds had been docked. As a result, a number of potent and one selective ligand toward the intended target have been identified. However, in in vitro experimental verification studies, many ligands also bound to the A2AAR and the A3AR subtypes. In this work we asked the question whether a classification of the ligands according to their selectivity was possible based on docking scores. Therefore, we built an A3AR homology model and docked all previously found ligands to all three receptor subtypes. As a metric, we employed an in vitro/in silico selectivity ranking system based on taxicab geometry and obtained a classification model with reasonable separation. In the next step, the method was validated with an external library of, selective ligands with similarly good performance. This classification system might also be useful in further screens.

Highlights

A particular focus of rational drug design is the selectivity of novel ligands, with the aim to reduce possible side effects
The three best-scoring A3AR models were used for further evaluation strategies based on two main criteria: area under the curve (AUC) of binders/non-binders docking evaluation and visual inspection of the docked ligands
Predicting the subtype selectivity of ligands to G protein-coupled receptors (GPCRs) using in silico methods still remains a challenge for modelers [37] for a number of receptors share a high degree of structural similarity among their subtypes

Summary

Introduction

A particular focus of rational drug design is the selectivity of novel ligands, with the aim to reduce possible side effects. With respect to binding patterns, docking of a set of either newly designed ligands or virtual screening database compounds to various subtypes of a proposed biological target might narrow the group of potential ligands to those that exclusively interact with the intended protein(s). Built of seven transmembrane helices, they mediate signals from the out- to the inside of cells by sensing different agents. Binding of these agents leads to conformational changes and intracellular signaling cascades. Based on the fact that the transmembrane region of all GPCRs is well conserved, and knowing that most of class A GPCRs’ ligand binding cavities are open toward the extracellular region [5], homology modeling provides a useful tool for structure-based ligand design. The reason for that can be sought in highly variable loop sequences often corresponding to unaligned regions in sequence alignments, as well as their location at the solvent-exposed surface of proteins that result in higher conformational flexibility [6]

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