Archives

  • 2018-07
  • 2019-04
  • 2019-05
  • 2019-06
  • 2019-07
  • 2019-08
  • 2019-09
  • 2019-10
  • 2019-11
  • 2019-12
  • 2020-01
  • 2020-02
  • 2020-03
  • 2020-04
  • 2020-05
  • 2020-06
  • 2020-07
  • 2020-08
  • 2020-09
  • 2020-10
  • 2020-11
  • 2020-12
  • 2021-01
  • 2021-02
  • 2021-03
  • 2021-04
  • 2021-05
  • 2021-06
  • 2021-07
  • 2021-08
  • 2021-09
  • 2021-10
  • 2021-11
  • 2021-12
  • 2022-01
  • 2022-02
  • 2022-03
  • 2022-04
  • 2022-05
  • 2022-06
  • 2022-07
  • 2022-08
  • 2022-09
  • 2022-10
  • 2022-11
  • 2022-12
  • 2023-01
  • 2023-02
  • 2023-03
  • 2023-04
  • 2023-05
  • 2023-06
  • 2023-08
  • 2023-09
  • 2023-10
  • 2023-11
  • 2023-12
  • 2024-01
  • 2024-02
  • 2024-03
  • Which is the preferred dimer

    2022-05-25

    Which is the preferred dimer configuration, the one corresponding to the active state or the one corresponding to the desensitized state? Umbrella sampling simulations of a pair of GluA2 LBDs, using distances at the top (proximal to the ATD) and the bottom (proximal to the TMD), indicate that the desensitized configuration is more stable by ∼17 kcal/mol [60]. These results were consistent with 5 μs free simulations, in which a trajectory initiated from an active LBD dimer configuration transitioned to a desensitized one in ∼2 μs, while a trajectory initiated from a desensitized configuration remained in that configuration. An LBD mutant (L483Y) that experimentally prevents desensitization was found to stably occupy the active dimer configuration in the simulations.
    Ligand-binding pathways The calculation of ligand binding free energies to the GluA2 LBD does not depend on how the ligand is translocated from bulk solvent into the binding site. As such, in calculations, the translocation has been either along an arbitrarily chosen pathway (for the PMF-based method) or along a non-physical one (for FEP or TI). The use of MD simulations in conjunction with the string method with swarms-of-trajectories [61,62], a pathway sampling technique, demonstrated that residues outside the LBD binding cleft metastably interact with the glutamate ligand and help the ligand navigate its way into the recessed binding pocket [63] (Fig. 3). The free energies along glutamate-binding pathways, calculated using umbrella sampling simulations, indicate that the metastable interactions lower the energetic barriers to ligand binding. In a complementary study, a combination of conventional MD simulations (totaling almost 50 μs), free energy calculations, and experimental electrophysiological recordings of a panel of GluA2 mutants showed that strategically positioned flexible sidechains on the surface of the LBD grab glutamate and help guide it into its recessed binding pocket [64]. Eliminating the transient ghrelin receptor slowed the rates of activation and deactivation of the receptor. These results suggest that preferential ligand-binding pathways have evolved to optimize rapid responses of iGluRs at central nervous system synapses.
    Conclusions Enhanced sampling methods have been used to great effect in studying functionally important conformational transitions and ligand/ion binding in isolated iGluR LBD monomers and dimers. Because of the extensive sampling permitted by the modest size of an isolated LBD, it remains the system of choice when it is sufficient for addressing a particular iGluR question. However, as computational power steadily increases, and as more experimentally determined intact tetrameric iGluR structures in different functional states, bound to different ligands, become available, demanding all-atom MD simulation studies of intact receptors are becoming more tractable. Performing free energy calculations involving individual domains but in the context of an intact receptor is a logical step. Simulations that include the modeled attachment of glycans, which have recently been performed [65,66], are also an intriguing avenue of exploration. Enhanced sampling simulations will no doubt help shed light on functionally important thermodynamic properties of intact iGluRs just as they have done for isolated domains.
    Introduction Astrocytes have historically thought to be passive housekeeping cells. Brain astrocytes in primary culture have been shown to metabolize membrane phospholipids to produce arachidonic acid (AA) (Stella et al., 1994a), which can be used to synthesize vasodilatory substances such as prostaglandins and epoxyeicosatrienoic acids (EETs) within astrocytes (Amruthesh et al., 1993; Alkayed et al., 1996c). The epoxygenase pathway has been confirmed in cultured rat hippocampal astrocyte homogenate (Amruthesh et al., 1993; Stella et al., 1994b; Alkayed et al., 1996a). The generation of 20-hydroxyeicosatetraenoic acid (20-HETE) was increased after incubation with AA using rat cerebral vessel microsomes (Gebremedhin et al., 2000). The inhibition of 20-HETE synthesis ameliorated the reduction in cerebral blood flow followed by cortical spreading depression or subarachnoid hemorrhage in the rat (Kehl et al., 2002a). Furthermore, the inhibition of the epoxygenase pathway of AA reduced cerebral blood flow in vivo (Alkayed et al., 1996b). It was thus suggested that neuronal activation may lead to the release of astrocyte-derived AA metabolites to affect the functional neurovascular unit. David Attwell and Raymond C. Koehler et al. hypothesize that blood flow in the brain is regulated by neurotransmitter-mediated signaling via the AA pathways (Koehler et al., 2009; Attwell et al., 2010). Cytochrome P450 2C (CYP2C) and CYP4 A have been shown as epoxygenase and ω-hydroxylase involved in the production of EETs and HETEs from AA in heart, kidney, lung, and the liver (El-Sherbeni et al., 2013). However, CYP2C and CYP4 A were present at lower levels or not observed in the human brain (Dutheil et al., 2009a). Do the neurotransmitters released from the neurons change AA epoxygenation and monooxygenation via astrocytic CYPs?