Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

The functional dynamics of G protein-coupled receptors (GPCRs) encompasses multiple spatiotemporal scales, ranging from femtoseconds to seconds and Ångströms to micrometers. Computational approaches, often in close collaboration with experimental methods, have been invaluable in unraveling GPCR structure and dynamics at these various hierarchical levels. The binding of natural and synthetic ligands to the wild-type and naturally occurring variant receptors have been analyzed by several computational methods. The activation of receptors from the inactive to the active state has been investigated by atomistic simulations and ongoing work on several receptors will help uncover general and receptor-specific mechanisms. The interaction of GPCRs with complex membranes that contain phospholipids and cholesterol have been probed by coarse-grain methods and shown to directly influence receptor association. In this chapter, we discuss computational approaches that have been successful in analyzing each scale of GPCR dynamics. An overview of these approaches will allow a more judicious choice of the appropriate method. We hope that an appreciation of the power of current computational approaches will encourage more critical collaborations. A comprehensive integration of the different approaches over the entire spatiotemporal scales promises to unravel new facets of GPCR function.

Download full-text PDF

Source
http://dx.doi.org/10.1016/bs.mcb.2015.11.007DOI Listing

Publication Analysis

Top Keywords

computational approaches
12
spatiotemporal scales
8
approaches will
8
approaches
5
simulations gpcrs
4
gpcrs integrating
4
integrating scales
4
scales functional
4
functional dynamics
4
dynamics protein-coupled
4

Similar Publications

Treating neurological disorders is challenging due to the blood-brain barrier (BBB), which limits therapeutic agents, including proteins and peptides, from entering the central nervous system. Despite their potential, the BBB's selective permeability is a significant obstacle. This review explores recent advancements in protein therapeutics for BBB-targeted delivery and highlights computational tools.

View Article and Find Full Text PDF

Self-supervised representation learning with continuous training data improves the feel and performance of myoelectric control.

Comput Biol Med

September 2025

Department of Electrical and Computer Engineering and the Institute of Biomedical Engineering, University of New Brunswick, Fredericton, E3B 5A3, NB, Canada.

Pattern recognition-based myoelectric control is traditionally trained with static or ramp contractions, but this fails to capture the dynamic nature of real-world movements. This study investigated the benefits of training classifiers with continuous dynamic data, encompassing transitions between various movement classes. We employed both conventional (LDA) and deep learning (LSTM) classifiers, comparing their performance when trained with ramp data, continuous dynamic data, and an LSTM pre-trained with a self-supervised learning technique (VICReg).

View Article and Find Full Text PDF

Background: Primary liver cancer, particularly hepatocellular carcinoma (HCC), poses significant clinical challenges due to late-stage diagnosis, tumor heterogeneity, and rapidly evolving therapeutic strategies. While systematic reviews and meta-analyses are essential for updating clinical guidelines, their labor-intensive nature limits timely evidence synthesis.

Objective: This study proposes an automated literature screening workflow powered by large language models (LLMs) to accelerate evidence synthesis for HCC treatment guidelines.

View Article and Find Full Text PDF

Computational modeling for PPE filtration: Informed by material characterization, microbial penetration, and particle mechanics.

J Occup Environ Hyg

September 2025

Division of Biology, Chemistry, and Materials Science, Office of Science and Engineering Laboratories, US Food and Drug Administration (FDA), Oak Ridge, Tennessee.

This work assesses the current characterization framework of single-use personal protective equipment (PPE) per recognized consensus standards and presents a novel quantitative approach to refining characterization of barrier materials and predicting PPE performance. Scanning electron microscopy (SEM) and image analysis software (Diameter J) were used to examine the microscopic fiber and pore structure of filter layers of surgical N95 filtering facepiece respirators, before and after exposure to chemicals used in decontamination modalities (vaporized hydrogen peroxide or ozone). The effect of porosity on penetration was assessed by bacterial filtration efficiency (BFE) testing.

View Article and Find Full Text PDF

Azolo[1,5-]pyrimidines (APs) are widely recognized as challenging scaffolds for diverse applications in both medicinal chemistry and materials science. Owing to their high potential, active research is focused on developing new derivatives through the derivatization and functionalization of their molecular structure. Herein, we report an unusual transformation in the AP series initiated by a hydroperoxide anion.

View Article and Find Full Text PDF