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.
Highlights
Structure-driven fragment-based (SDFB) approaches have provided efficient methods for the design of novel pharmacological probes as well as drug candidates [1]
Protein-coupled receptors (GPCRs) has stimulated an intensive campaign to identify new classes of hit-candidates different from conventional agonists and antagonists, in particular considering the breakthroughs coming from G protein-coupled receptors (GPCRs) crystallographic determination that has resulted in a fast-growing number of structures obtained as complexes with allosteric modulators
It is useful to underline the Allosteric Database (ASD) repository that it has been developed to provide comprehensive information characterizing allosteric regulation ranging from allosteric proteins, modulators of interactions, sites, Molecules 2017, 22, 818; doi:10.3390/molecules22050818
Summary
Structure-driven fragment-based (SDFB) approaches have provided efficient methods for the design of novel pharmacological probes as well as drug candidates [1]. At the end have of recently reported an alternative computational method, Molecular of each Dynamics time window collected are fitted into a linear function f(x) = mx and a (SuMD),distance that allowspoints investigating the ligand-receptor recognition pathway on a nanoseconds time scaleis[11,12,13]. The applicability domain of our methodology, we selected two fragment-like adenosine A2A receptor exploring their possible recognition pathways by performing SuMD simulations in the absence and in PAMs (see Table 1) exploring their possible recognition pathways by performing SuMD simulations presenceinofthe theabsence From this retrospective ourretrospective results suggest in presence of the NECA agonist.
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