Development of enhanced conformational sampling methods to probe the activation landscape of GPCRs

Abrol, Ravinder; Serrano, Erik; Santiago, Luis Jaimes

doi:10.1016/bs.apcsb.2021.11.001

Cited by 2 publications

(2 citation statements)

References 153 publications

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“…Overall, the FES of holo-receptor shows that different agonist binding with GRs produces diverse conformational states of GRs, supporting the hypothesis that conformational rearrangement due to ligand binding regulates GR activation. While the present set of 23 0.1 μs MD trajectories provides a robust comparative data set for binding interactions, future work aided by continuous improvements in supercomputing could aim to generate multimicrosecond to millisecond trajectories to provide replicates for enhanced sampling and statistics and possibly capture also collective large-scale motions triggering activation and allostery. − …”

Section: Resultsmentioning

confidence: 99%

“…While the present set of 23 0.1 μs MD trajectories provides a robust comparative data set for binding interactions, future work aided by continuous improvements in supercomputing could aim to generate multimicrosecond to millisecond trajectories to provide replicates for enhanced sampling and statistics and possibly capture also collective large-scale motions triggering activation and allostery. 92 − 94 …”

Section: Resultsmentioning

confidence: 99%

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Computational Peptide Design Cotargeting Glucagon and Glucagon-like Peptide-1 Receptors

Vishnoi,

Bhattacharya,

Walsh

et al. 2023

J. Chem. Inf. Model.

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Peptides are sustainable alternatives to conventional therapeutics for G protein-coupled receptor (GPCR) linked disorders, promising biocompatible and tailorable next-generation therapeutics for metabolic disorders including type-2 diabetes, as agonists of the glucagon receptor (GCGR) and the glucagon-like peptide-1 receptor (GLP-1R). However, single agonist peptides activating GLP-1R to stimulate insulin secretion also suppress obesity-linked glucagon release. Hence, bioactive peptides cotargeting GCGR and GLP-1R may remediate the blood glucose and fatty acid metabolism imbalance, tackling both diabetes and obesity to supersede current monoagonist therapy. Here, we design and model optimized peptide sequences starting from peptide sequences derived from earlier phage-displayed library screening, identifying those with predicted molecular binding profiles for dual agonism of GCGR and GLP-1R. We derive design rules from extensive molecular dynamics simulations based on peptide−receptor binding. Our newly designed coagonist peptide exhibits improved predicted coupled binding affinity for GCGR and GLP-1R relative to endogenous ligands and could in the future be tested experimentally, which may provide superior glycemic and weight loss control.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Computational Peptide Design Cotargeting Glucagon and Glucagon-like Peptide-1 Receptors

Vishnoi,

Bhattacharya,

Walsh

et al. 2023

J. Chem. Inf. Model.

View full text Add to dashboard Cite

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Metadynamics simulations leveraged by statistical analyses and artificial intelligence-based tools to inform the discovery of G protein-coupled receptor ligands

Fiorillo

Filizola

2022

Front. Endocrinol.

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G Protein-Coupled Receptors (GPCRs) are a large family of membrane proteins with pluridimensional signaling profiles. They undergo ligand-specific conformational changes, which in turn lead to the differential activation of intracellular signaling proteins and the consequent triggering of a variety of biological responses. This conformational plasticity directly impacts our understanding of GPCR signaling and therapeutic implications, as do ligand-specific kinetic differences in GPCR-induced transducer activation/coupling or GPCR-transducer complex stability. High-resolution experimental structures of ligand-bound GPCRs in the presence or absence of interacting transducers provide important, yet limited, insights into the highly dynamic process of ligand-induced activation or inhibition of these receptors. We and others have complemented these studies with computational strategies aimed at characterizing increasingly accurate metastable conformations of GPCRs using a combination of metadynamics simulations, state-of-the-art algorithms for statistical analyses of simulation data, and artificial intelligence-based tools. This minireview provides an overview of these approaches as well as lessons learned from them towards the identification of conformational states that may be difficult or even impossible to characterize experimentally and yet important to discover new GPCR ligands.

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Development of enhanced conformational sampling methods to probe the activation landscape of GPCRs

Cited by 2 publications

References 153 publications

Computational Peptide Design Cotargeting Glucagon and Glucagon-like Peptide-1 Receptors

Computational Peptide Design Cotargeting Glucagon and Glucagon-like Peptide-1 Receptors

Metadynamics simulations leveraged by statistical analyses and artificial intelligence-based tools to inform the discovery of G protein-coupled receptor ligands

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