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Molecules 2017, 22(5), 818; doi:10.3390/molecules22050818

Supporting the Identification of Novel Fragment-Based Positive Allosteric Modulators Using a Supervised Molecular Dynamics Approach: A Retrospective Analysis Considering the Human A2A Adenosine Receptor as a Key Example

Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Via Marzolo 5, 35131 Padua, Italy
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Academic Editors: Francisco Ciruela and Eddy Sotelo
Received: 9 March 2017 / Revised: 3 May 2017 / Accepted: 10 May 2017 / Published: 16 May 2017
(This article belongs to the Special Issue Adenosine Receptors)
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Abstract

Structure-driven fragment-based (SDFB) approaches have provided efficient methods for the identification of novel drug candidates. This strategy has been largely applied in discovering several pharmacological ligand classes, including enzyme inhibitors, receptor antagonists and, more recently, also allosteric (positive and negative) modulators. Recently, Siegal and collaborators reported an interesting study, performed on a detergent-solubilized StaR adenosine A2A receptor, describing the existence of both fragment-like negative allosteric modulators (NAMs), and fragment-like positive allosteric modulators (PAMs). From this retrospective study, our results suggest that Supervised Molecular Dynamics (SuMD) simulations can support, on a reasonable time scale, the identification of fragment-like PAMs following their receptor recognition pathways and characterizing the possible allosteric binding sites. View Full-Text
Keywords: adenosine receptors; positive allosteric modulators; fragment-based approaches; supervised molecular dynamics adenosine receptors; positive allosteric modulators; fragment-based approaches; supervised molecular dynamics
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Deganutti, G.; Moro, S. Supporting the Identification of Novel Fragment-Based Positive Allosteric Modulators Using a Supervised Molecular Dynamics Approach: A Retrospective Analysis Considering the Human A2A Adenosine Receptor as a Key Example. Molecules 2017, 22, 818.

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