G protein-coupled receptors (GPCRs) are a superfamily of membrane proteins that, in humans, comprises about 1000 members. They are activated by a wide range of natural ligands and are targeted by many of the marketed and leisure drugs. Hence, there is great interest in the experimental elucidation and the theoretical modeling of their three-dimensional (3D) structures, which can be employed as ligand discovery platforms. To date, 140 structures have been solved for 33 GPCRs, more than half of which reflect the inactive state of 24 different Class A GPCRs – see our searchable table at www.costanziresearch.com/p/table.html. Beyond providing detailed topological information on the solved receptors, these experimental structures can be used as templates for the construction of 3D homology models of other family members.<br/>With this work, we aimed at verifying the possible existence of a linear correlation between the model/template sequence identity and the accuracy of the models. Moreover, as a corollary question, we inquired whether or not sequence alignments strategies that allow gaps within the transmebrane domains afford better models than the classical alignment procedures that do not allow for the presence of such gaps. To address these questions, we constructed models of the beta2 adrenergic receptor, a prototypical Class A GPCR, using as templates all the other 23 Class A GPCRs solved in the inactive state. Our results highlighted a detectable linear correlation between model/template sequence identity and model accuracy, suggesting that the likely accuracy of GPCR models can be forecasted on the basis of the available templates. Moreover, they suggested that the two above-mentioned alignment strategies do not yield significantly different results.<br/>We thank American University, the Schwartz Fellowship of the Chemistry Department, and the Mathias Fellowship of the College of Arts and Sciences for funding.

Homology modeling of class A GPCRs in the inactive conformation: A quantitative analysis of the correlation between model-/template-sequence identity and model accuracy

251st National Meeting (2016)

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