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Cannabinoid receptor 1 (CB1) is a G protein-coupled receptor that regulates critical physiological processes including pain, appetite, and cognition. Understanding the conformational dynamics of CB1 associated with transitions between inactive and active signaling states is imperative for developing targeted modulators. Using microsecond-level all-atom molecular dynamics simulations, we identified marked differences in the conformational ensembles of inactive and active CB1 in apo. The inactive state exhibited substantially increased structural heterogeneity and plasticity compared to the more rigidified active state in the absence of stabilizing ligands. Transmembrane helices TM3 and TM7 were identified as distinguishing factors modulating the state-dependent dynamics. TM7 displayed amplified fluctuations selectively in the inactive state simulations attributed to disruption of conserved electrostatic contacts anchoring it to surrounding helices in the active state. Additionally, we identified significant reorganizations in key salt bridge and hydrogen bond networks contributing to the CB1 activation/inactivation. For instance, D213-Y224 hydrogen bond and D184-K192 salt bridge showed marked rearrangements between the states. Collectively, these findings reveal the specialized role of TM7 in directing state-dependent CB1 dynamics through electrostatic switch mechanisms. By elucidating the intrinsic enhanced flexibility of inactive CB1, this study provides valuable insights into the conformational landscape enabling functional transitions. Our perspective advances understanding of CB1 activation mechanisms and offers opportunities for structure-based drug discovery targeting the state-specific conformational dynamics of this receptor.

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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.

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The cannabinoid receptor CB1 is a G protein-coupled receptor that regulates critical physiological processes including pain, appetite, and cognition. Understanding the conformational dynamics of CB1 associated with transitions between inactive and active signaling states is imperative for developing targeted modulators. Using microsecond-level all-atom molecular dynamics simulations, we identified marked differences in the conformational ensembles of inactive and active CB1 states in apo conditions. The inactive state exhibited substantially increased structural heterogeneity and plasticity compared to the more rigidified active state in the absence of stabilizing ligands. Transmembrane helices TM3 and TM7 were identified as distinguishing factors modulating the state-dependent dynamics. TM7 displayed amplified fluctuations selectively in the inactive state simulations attributed to disruption of conserved electrostatic contacts anchoring it to surrounding helices in the active state. Additionally, we identified significant reorganization of key salt bridge and hydrogen bond networks known to control CB1 activation between states. For instance, a conserved D213-Y224 hydrogen bond and D184-K192 salt bridge interactions showed marked rearrangements between the states. Collectively, these findings reveal the specialized role of TM7 in directing state-dependent CB1 dynamics through electrostatic switch mechanisms. By elucidating the intrinsic enhanced flexibility of inactive CB1, this study provides valuable insights into the conformational landscape enabling functional transitions. Our perspective advances understanding of CB1 activation mechanisms and offers opportunities for structure-based drug discovery targeting the state-specific conformational dynamics of this receptor.

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The novel multidomain protein, cpSRP43, is a unique subunit of the post-translational chloroplast signal recognition particle (cpSRP) targeting pathway in higher plants. The cpSRP pathway is responsible for targeting and insertion of light-harvesting chlorophyll a/b binding proteins (LHCPs) to the thylakoid membrane. Upon emergence into the stroma, LHCPs form a soluble transit complex with the cpSRP heterodimer, which is composed of cpSRP43 and cpSRP54. cpSRP43 is irreplaceable as a chaperone to LHCPs in their translocation to the thylakoid membrane and remarkable in its ability to dissolve aggregates of LHCPs without the need for external energy input. In previous studies, cpSRP43 has demonstrated significant flexibility and interdomain dynamics. In this study, we explore the structural stability and flexibility of cpSRP43 using a combination of computational and experimental techniques and find that this protein is concurrently highly stable and flexible. In addition to microsecond-level unbiased molecular dynamics (MD), biased MD simulations based on system-specific collective variables are used along with biophysical experimentation to explain the basis of the flexibility and stability of cpSRP43, showing that the free and cpSRP54-bound cpSRP43 has substantially different conformations and conformational dynamics.

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The major facilitator superfamily (MFS) of transporters consists of three classes of membrane transporters: symporters, uniporters, and antiporters. Despite such diverse functions, MFS transporters are believed to undergo similar conformational changes within their distinct transport cycles, known as the rocker-switch mechanism. While the similarities between conformational changes are noteworthy, the differences are also important since they could potentially explain the distinct functions of symporters, uniporters, and antiporters of the MFS superfamily. We reviewed a variety of experimental and computational structural data on a select number of antiporters, symporters, and uniporters from the MFS family to compare the similarities and differences of the conformational dynamics of three different classes of transporters.

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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.

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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.

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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.

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Mechanosensitive channel of large conductance (MscL) detects and responds to changes in the pressure profile of cellular membranes and transduces the mechanical energy into electrical and/or chemical signals. MscL can be activated using ultrasonic or chemical activation methods to improve the absorption of medicines and bioactive compounds into cells. However, re-engineering chemical signals such as pH change can trigger channel activation in MscL. This study elucidates the activation mechanism of an engineered MscL at an atomic level through a combination of equilibrium and non-equilibrium (NE) molecular dynamics (MD) simulations. Comparing the wild-type (WT) and engineered MscL activation processes suggests that the two systems are likely associated with different active states and different transition pathways. These findings indicate that (1) periplasmic loops play a key role in the activation process of MscL, (2) the loss of various backbone-backbone hydrogen bonds and salt bridge interactions in the engineered MscL channel causes the spontaneous opening of the channel, and (3) the most significant interactions lost during the activation process are between the transmembrane helices 1 and 2 in engineered MscL channel. The orientation-based biasing approach for producing and optimizing an open MscL model used in this work is a promising way to characterize unknown protein functional states and investigate the activation processes in ion channels and transmembrane proteins in general. This work paves the way for a computational framework for engineering more efficient pH-sensing mechanosensitive channels.

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Within the last 2 decades, severe acute respiratory syndrome coronaviruses 1 and 2 (SARS-CoV-1 and SARS-CoV-2) have caused two major outbreaks; yet, for reasons not fully understood, the coronavirus disease 2019 pandemic caused by SARS-CoV-2 has been significantly more widespread than the 2003 SARS epidemic caused by SARS-CoV-1, despite striking similarities between these two viruses. The SARS-CoV-1 and SARS-CoV-2 spike proteins, both of which bind to host cell angiotensin-converting enzyme 2, have been implied to be a potential source of their differential transmissibility. However, the mechanistic details of prefusion spike protein binding to angiotensin-converting enzyme 2 remain elusive at the molecular level. Here, we performed an extensive set of equilibrium and nonequilibrium microsecond-level all-atom molecular dynamics simulations of SARS-CoV-1 and SARS-CoV-2 prefusion spike proteins to determine their differential dynamic behavior. Our results indicate that the active form of the SARS-CoV-2 spike protein is more stable than that of SARS-CoV-1 and the energy barrier associated with the activation is higher in SARS-CoV-2. These results suggest that not only the receptor-binding domain but also other domains such as the N-terminal domain could play a crucial role in the differential binding behavior of SARS-CoV-1 and SARS-CoV-2 spike proteins.

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The coronavirus spike protein, which binds to the same human receptor in both SARS-CoV-1 and 2, has been implied to be a potential source of their differential transmissibility. However, the mechanistic details of spike protein binding to its human receptor remain elusive at the molecular level. Here, we have used an extensive set of unbiased and biased microsecond-level all-atom molecular dynamics (MD) simulations of SARS-CoV-1 and 2 spike proteins to determine the differential dynamic behavior of prefusion spike protein structure in the two viruses. Our results indicate that the active form of the SARS-CoV-2 spike protein is more stable than that of SARS-CoV-1 and the energy barrier associated with the activation is higher in SARS-CoV-2. Our results also suggest that not only the receptor binding domain (RBD) but also other domains such as the N-terminal domain (NTD) could play a role in the differential binding behavior of SARS-CoV-1 and 2 spike proteins.