Search for: All records

Abstract Metabotropic glutamate receptors (mGluRs) are class C G protein-coupled receptors that function as obligate dimers in regulating neurotransmission and synaptic plasticity in the central nervous system. The mGluR1 subtype has been shown to be modulated by the membrane lipid environment, particularly cholesterol, though the molecular mechanisms remain elusive. In this study, we employed all-atom molecular dynamics simulations to investigate the effects of cholesterol on the conformational dynamics of the mGluR1 seven-transmembrane (7TM) domain in an inactive state model. Simulations were performed with three different cholesterol concentrations (0%, 10%, and 25%) in a palmitoyl-oleoyl phosphatidylcholine (POPC) lipid bilayer system. Our results demonstrate that cholesterol induces conformational changes in the mGluR1 dimer more significantly than in the individual protomers. Notably, cholesterol modulates the dynamics and conformations of the TM1 and TM2 helices at the dimer interface. Interestingly, an intermediate cholesterol concentration of 10% elicits more pronounced conformational changes compared to both cholesterol-depleted (0%) and cholesterol-enriched (25%) systems. Specific electrostatic interaction unique to the 10% cholesterol system further corroborate these conformational differences. Given the high sequence conservation of the 7TM domains across mGluR subtypes, the cholesterol-dependent effects observed in mGluR1 are likely applicable to other members of this receptor family. Our findings provide atomistic insights into how cholesterol modulates the conformational landscape of mGluRs, which could impact their function and signaling mechanisms. 

YidC is a membrane protein that facilitates the insertion of newly synthesized proteins into lipid membranes. Through YidC, proteins are inserted into the lipid bilayer via the SecYEG-dependent complex. Additionally, YidC functions as a chaperone in protein folding processes. Several studies have provided evidence of its independent insertion mechanism. However, the mechanistic details of the YidC SecY-independent protein insertion mechanism remain elusive at the molecular level. This study elucidates the insertion mechanism of YidC at an atomic level through a combination of equilibrium and non-equilibrium molecular dynamics (MD) simulations. Different docking models of YidC-Pf3 in the lipid bilayer were built in this study to better understand the insertion mechanism. To conduct a complete investigation of the conformational difference between the two docking models developed, we used classical molecular dynamics simulations supplemented with a non-equilibrium technique. Our findings indicate that the YidC transmembrane (TM) groove is essential for this high-affinity interaction and that the hydrophilic nature of the YidC groove plays an important role in protein transport across the cytoplasmic membrane bilayer to the periplasmic side. At different stages of the insertion process, conformational changes in YidC’s TM domain and membrane core have a mechanistic effect on the Pf3 coat protein. Furthermore, during the insertion phase, the hydration and dehydration of the YidC’s hydrophilic groove are critical. These results demonstrate that Pf3 coat protein interactions with the membrane and YidC vary in different conformational states during the insertion process. Finally, this extensive study directly confirms that YidC functions as an independent insertase. 

Abstract The protein–ligand binding affinity quantifies the binding strength between a protein and its ligand. Computer modeling and simulations can be used to estimate the binding affinity or binding free energy using data- or physics-driven methods or a combination thereof. Here we discuss a purely physics-based sampling approach based on biased molecular dynamics simulations. Our proposed method generalizes and simplifies previously suggested stratification strategies that use umbrella sampling or other enhanced sampling simulations with additional collective-variable-based restraints. The approach presented here uses a flexible scheme that can be easily tailored for any system of interest. We estimate the binding affinity of human fibroblast growth factor 1 to heparin hexasaccharide based on the available crystal structure of the complex as the initial model and four different variations of the proposed method to compare against the experimentally determined binding affinity obtained from isothermal titration calorimetry experiments. 

The controlled formation of nanoparticles with optimum characteristics and functional aspects has proven successful via peptide-mediated nanoparticle synthesis. However, the effects of the peptide sequence and binding motif on surface features and physicochemical properties of nanoparticles are not well-understood. In this study, we investigate in a comparative manner how a specific peptide known as Pd4 and its two known variants may form nanoparticles both in an isolated state and when attached to a green fluorescent protein (GFPuv). More importantly, we introduce a novel computational approach to predict the trend of the size and activity of the peptide-directed nanoparticles by estimating the binding affinity of the peptide to a single ion. We used molecular dynamics (MD) simulations to explore the differential behavior of the isolated and GFP-fused peptides and their mutants. Our computed palladium (Pd) binding free energies match the typical nanoparticle sizes reported from transmission electron microscope pictures. Stille coupling and Suzuki–Miyaura reaction turnover frequencies (TOFs) also correspond with computationally predicted Pd binding affinities. The results show that while using Pd4 and its two known variants (A6 and A11) in isolation produces nanoparticles of varying sizes, fusing these peptides to the GFPuv protein produces nanoparticles of similar sizes and activity. In other words, GFPuv reduces the sensitivity of the nanoparticles to the peptide sequence. This study provides a computational framework for designing free and protein-attached peptides that helps in the synthesis of nanoparticles with well-regulated properties.