Dataset Information

Understanding Ligand Binding Selectivity in a Prototypical GPCR Family.

ABSTRACT: Adenosine receptors are involved in many pathological conditions and are thus promising drug targets. However, developing drugs that target this GPCR subfamily is a challenging task. A number of drug candidates fail due to lack of selectivity which results in unwanted side effects. The extensive structural similarity of adenosine receptors complicates the design of selective ligands. The problem of selective targeting is a general concern in GPCRs, and in this respect adenosine receptors are a prototypical example. Here we use enhanced sampling simulations to decipher the determinants of selectivity of ligands in A_2a and A₁ adenosine receptors. Our model shows how small differences in the binding pocket and in the water network around the ligand can be leveraged to achieve selectivity.

SUBMITTER: Mattedi G

PROVIDER: S-EPMC7007187 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Publications

Understanding Ligand Binding Selectivity in a Prototypical GPCR Family.

Mattedi Giulio G Deflorian Francesca F Mason Jonathan S JS de Graaf Chris C Gervasio Francesco L FL

Journal of chemical information and modeling 20190604 6

Adenosine receptors are involved in many pathological conditions and are thus promising drug targets. However, developing drugs that target this GPCR subfamily is a challenging task. A number of drug candidates fail due to lack of selectivity which results in unwanted side effects. The extensive structural similarity of adenosine receptors complicates the design of selective ligands. The problem of selective targeting is a general concern in GPCRs, and in this respect adenosine receptors are a p ...[more]

PMID: 31125224

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Project description:G-protein-coupled receptors (GPCRs) mediate diverse cell signaling cascades after recognizing extracellular ligands. Despite the successful history of known GPCR drugs, a lack of mechanistic insight into GPCR challenges both the deorphanization of some GPCRs and optimization of the structure-activity relationship of their ligands. Notably, replacing a small substituent on a GPCR ligand can significantly alter extracellular GPCR-ligand interaction patterns and motion of transmembrane helices in turn to occur post-binding events of the ligand. In this study, we designed 3D multilevel features to describe the extracellular interaction patterns. Subsequently, these 3D features were utilized to predict the post-binding events that result from conformational dynamics from the extracellular to intracellular areas. To understand the adaptability of GPCR ligands, we collected the conformational information of flexible residues during binding and performed molecular featurization on a broad range of GPCR-ligand complexes. As a result, we developed GPCR-ligand interaction patterns, binding pockets, and ligand features as score (GPCR-IPL score) for predicting the functional selectivity of GPCR ligands (agonism versus antagonism), using the multilevel features of (1) zoomed-out 'residue level' (for flexible transmembrane helices of GPCRs), (2) zoomed-in 'pocket level' (for sophisticated mode of action) and (3) 'atom level' (for the conformational adaptability of GPCR ligands). GPCR-IPL score demonstrated reliable performance, achieving area under the receiver operating characteristic of 0.938 and area under the precision-recall curve of 0.907 (available in gpcr-ipl-score.onrender.com). Furthermore, we used the molecular features to predict the biased activation of downstream signaling (Gi/o, Gq/11, Gs and β-arrestin) as well as the functional selectivity. The resulting models are interpreted and applied to out-of-set validation with three scenarios including the identification of a new MRGPRX antagonist.

Dataset Information

Understanding Ligand Binding Selectivity in a Prototypical GPCR Family.

Publications

Understanding Ligand Binding Selectivity in a Prototypical GPCR Family.

Similar Datasets

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