The Metabotropic glutamate receptor 2 (mGluR2) is involved in several neurological and psychiatric disorders and is an attractive drug target. It is believed to form a strict dimer and the dimeric assembly is necessary for glutamate induced activation. Although many studies have focused on glutamate induced conformational changes, the dimerization propensity of mGluR2 with and without glutamate has never been investigated. Also, the role of the unstructured loop in dimerization of mGluR2 is not clear. Here, using Forster Resonance Energy Transfer (FRET) based assay in live cells we show that mGluR2 does not form a "strict dimer" rather it exists in a dynamic monomer-dimer equilibrium. The unstructured loop moderately destabilizes the dimers. Furthermore, binding of glutamate to mGluR2 induces conformational change that promotes monomerization of mGluR2. In the absence of an unstructured loop, mGluR2 neither undergoes conformational change nor monomerizes upon binding to glutamate.
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http://dx.doi.org/10.1016/j.abb.2020.108632 | DOI Listing |
Neuromodulation
December 2024
Neurosciences & Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada. Electronic address:
Objectives: Deep brain stimulation (DBS) is an established neuromodulatory technique for treating drug-resistant epilepsy. Despite its widespread use in carefully selected patients, the mechanisms underlying the antiseizure effects of DBS remain unclear. Herein, we provide a detailed overview of the current literature pertaining to experimental DBS in rodent models of epilepsy and identify relevant trends in this field.
View Article and Find Full Text PDFJ Biol Chem
November 2024
Department of Biochemistry, University of Zurich, Zurich, Switzerland.
Most processes of life are the result of polyvalent interactions between macromolecules, often of heterogeneous types and sizes. Frequently, the times associated with these interactions are prohibitively long for interrogation using atomistic simulations. Here, we study the recognition of N6-methylated adenine (mA) in RNA by the reader domain YTHDC1, a prototypical, cognate pair that challenges simulations through its composition and required timescales.
View Article and Find Full Text PDFNature
November 2024
George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
Lower-limb exoskeletons have the potential to transform the way we move, but current state-of-the-art controllers cannot accommodate the rich set of possible human behaviours that range from cyclic and predictable to transitory and unstructured. We introduce a task-agnostic controller that assists the user on the basis of instantaneous estimates of lower-limb biological joint moments from a deep neural network. By estimating both hip and knee moments in-the-loop, our approach provided multi-joint, coordinated assistance through our autonomous, clothing-integrated exoskeleton.
View Article and Find Full Text PDFJ Biol Chem
November 2024
Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. Electronic address:
Loops in the axial channels of ClpAP and other AAA+ proteases bind a short peptide degron connected by a linker to the N- or C-terminal residue of a native protein to initiate degradation. ATP hydrolysis then powers pore-loop movements that translocate these segments through the channel until a native domain is pulled against the narrow channel entrance, creating an unfolding force. Substrate unfolding is thought to depend on strong contacts between pore loops and a subset of amino acids in the unstructured sequence directly preceding the folded domain.
View Article and Find Full Text PDFFront Neurorobot
September 2024
Center for X-Mechanics, Zhejiang University, Hangzhou, China.
Robot control in complex and unpredictable scenarios presents challenges such as adaptability, robustness, and human-robot interaction. These scenarios often require robots to perform tasks that involve unknown objects in unstructured environments with high levels of uncertainty. Traditional control methods, such as automatic control, may not be suitable due to their limited adaptability and reliance on prior knowledge.
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