2002•Journal of Medicinal ChemistryOpen access

Synthesis, Molecular Modeling Studies, and Pharmacological Activity of Selective A 1 Receptor Antagonists

Francesco Bondavalli, Maurizio Botta, Olga Bruno, Andrea Ciacci, Federico Corelli, Paola Fossa, Antonio Lucacchini, Fabrizio Manetti, Claudia Martini, Giulia Menozzi, Luisa Mosti, Angelo Ranise, Silvia Schenone, Andrea Tafi, Maria Letizia Trincavelli

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Abstract

We present a combined computational study aimed at identifying the three-dimensional structural properties required for different classes of compounds to show antagonistic activity toward the A(1) adenosine receptor (AR). Particularly, an approach combining pharmacophore mapping, molecular alignment, and pseudoreceptor generation was applied to derive a hypothesis of the interaction pathway between a set of A(1) AR antagonists taken from the literature and a model of the putative A(1) receptor. The pharmacophore model consists of seven features and represents an improvement of the N(6)-C8 model, generally reported as the most probable pharmacophore model for A(1) AR agonists and antagonists. It was used to build up a pseudoreceptor model able to rationalize the relationships between structural properties and biological data of, and external to, the training set. In fact, to further assess its statistical significance and predictive power, the pseudoreceptor was employed to predict the free energy of binding associated with compounds constituting a test set. While part of these molecules was also taken from the literature, the remaining compounds were designed and synthesized by our research group. All of the new compounds were tested for their affinity toward A(1), A(2a), and A(3) AR, showing interesting antagonistic activity and A(1) selectivity.

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We present a combined computational study aimed at identifying the three-dimensional structural properties required for different classes of compounds to show antagonistic activity toward the A(1) adenosine receptor (AR). Particularly, an approach combining pharmacophore mapping, molecular alignment, and pseudoreceptor generation was applied to derive a hypothesis of the interaction pathway between a set of A(1) AR antagonists taken from the literature and a model of the putative A(1) receptor. The pharmacophore model consists of seven features and represents an improvement of the N(6)-C8 model, generally reported as the most probable pharmacophore model for A(1) AR agonists and antagonists. It was used to build up a pseudoreceptor model able to rationalize the relationships between structural properties and biological data of, and external to, the training set. In fact, to further assess its statistical significance and predictive power, the pseudoreceptor was employed to predict the free energy of binding associated with compounds constituting a test set. While part of these molecules was also taken from the literature, the remaining compounds were designed and synthesized by our research group. All of the new compounds were tested for their affinity toward A(1), A(2a), and A(3) AR, showing interesting antagonistic activity and A(1) selectivity.

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Available abstract

We present a combined computational study aimed at identifying the three-dimensional structural properties required for different classes of compounds to show antagonistic activity toward the A(1) adenosine receptor (AR). Particularly, an approach combining pharmacophore mapping, molecular alignment, and pseudoreceptor generation was applied to derive a hypothesis of the interaction pathway between a set of A(1) AR antagonists taken from the literature and a model of the putative A(1) receptor. The pharmacophore model consists of seven features and represents an improvement of the N(6)-C8 model, generally reported as the most probable pharmacophore model for A(1) AR agonists and antagonists. It was used to build up a pseudoreceptor model able to rationalize the relationships between structural properties and biological data of, and external to, the training set. In fact, to further assess its statistical significance and predictive power, the pseudoreceptor was employed to predict the free energy of binding associated with compounds constituting a test set. While part of these molecules was also taken from the literature, the remaining compounds were designed and synthesized by our research group. All of the new compounds were tested for their affinity toward A(1), A(2a), and A(3) AR, showing interesting antagonistic activity and A(1) selectivity.

Key concepts: Pharmacophore, Chemistry, Molecular model, Computational biology, Structure–activity relationship, Stereochemistry, Biological activity, Combinatorial chemistry

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