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At least 433 records · Page 24

Covalent labeling of the Arabidopsis plasma membrane H + ‐ ATPase reveals 3D conformational changes involving the C‐terminal regulatory domain

The plasma membrane proton pump is the primary energy transducing, electrogenic ion pump of the plasma membrane in plants and fungi. Compared to its fungal counterpart, the plant plasma membrane proton pump's regulatory C‐terminal domain (CTD) contains an additional regulatory segment that links multiple sensory pathways regulating plant cell length through phosphorylation and recruitment of regulatory 14‐3‐3 proteins. However, a complete structural model of a plant proton pump is lacking. Here, we performed covalent labeling with mass spectrometric analysis (CL‐MS) on the Arabidopsis pump AHA2 to identify potential interactions between the CTD and the catalytic domains. Our results suggest that autoinhibition in the plant enzyme is much more structurally complex than in the fungal enzyme.

Blackburn, Matthew R. [Department of Biochemistry ↗

Ca X ML: Chemistry‐informed machine learning explains mutual changes between protein conformations and calcium ions in calcium‐binding proteins using structural and topological features

Proteins' flexibility is a feature in communicating changes in cell signaling instigated by binding with secondary messengers, such as calcium ions, associated with the coordination of muscle contraction, neurotransmitter release, and gene expression. When binding with the disordered parts of a protein, calcium ions must balance their charge states with the shape of calcium-binding proteins and their versatile pool of partners depending on the circumstances they transmit. Accurately determining the ionic charges of those ions is essential for understanding their role in such processes. However, it is unclear whether the limited experimental data available can be effectively used to train models to accurately predict the charges of calcium-binding protein variants. Here, we developed a chemistry-informed, machine-learning algorithm that implements a game theoretic approach to explain the output of a machine-learning model without the prerequisite of an excessively large database for high-performance prediction of atomic charges. We used the ab initio electronic structure data representing calcium ions and the structures of the disordered segments of calcium-binding peptides with surrounding water molecules to train several explainable models. Network theory was used to extract the topological features of atomic interactions in the structurally complex data dictated by the coordination chemistry of a calcium ion, a potent indicator of its charge state in protein. Our design created a computational tool of Ca X ML, which provided a framework of explainable machine learning model to annotate ionic charges of calcium ions in calcium-binding proteins in response to the chemical changes in an environment. Our framework will provide new insights into protein design for engineering functionality based on the limited size of scientific data in a genome space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chiral limit of 2d QCD revisited with lightcone conformal truncation

We study the chiral limit of 2d QCD with a single quark flavor at finite Nc using LCT. By modifying the LCT basis according to the quark mass in a manner motivated by ’t Hooft’s analysis, we are able to restore convergence for quark masses much smaller than the QCD strong coupling scale. For such small quark masses, the IR of the theory is expected to be well described by the Sine-Gordon model. We verify that LCT numerics are able to capture in detail the spectrum and correlation functions of the Sine-Gordon model. This opens up the possibility for studying deformations of various integrable CFTs using LCT by considering the chiral limit of QCD like theories.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Twist Accumulation in Conformal Field Theory: A Rigorous Approach to the Lightcone Bootstrap

We prove that in any unitary CFT, a twist gap in the spectrum of operator product expansion (OPE) of identical scalar quasiprimary operators (i.e. Φ x Φ) implies the existence of a family of quasiprimary operators O τ,l with spins l → ∞ and twists τ → 2Δ Φ in the same OPE spectrum. A similar twist-accumulation result is proven for any two-dimensional Virasoro-invariant, modular-invariant, unitary CFT with a normalizable vacuum and central charge c > 1, where we show that a twist gap in the spectrum of Virasoro primaries implies the existence of a family of Virasoro primaries Oh, $\overline{h}$ with h → ∞ and $\overline{h}$→ c-1/24 (the same is true with h and $\overline{h}$ interchanged). Here, we summarize the similarity of the two problems and propose a general formulation of the lightcone bootstrap.

97 MATHEMATICS AND COMPUTING↗

Conformational space exploration of cryo-EM structures by variability refinement

Cryo-EM observation of biological samples enables visualization of sample heterogeneity, in the form of discrete states that are separable, or continuous heterogeneity as a result of local protein motion before flash freezing. Variability analysis of this continuous heterogeneity describes the variance between a particle stack and a volume, and results in a map series describing the various steps undertaken by the sample in the particle stack. While this observation is absolutely stunning, it is very hard to pinpoint structural details to elements of the maps. Here, in order to bridge the gap between observation and explanation, we designed a tool that refines an ensemble of structures into all the maps from variability analysis. Using this bundle of structures, it is easy to spot variable parts of the structure, as well as the parts that are not moving. Comparison with molecular dynamics simulations highlights the fact that the movements follow the same directions, albeit with different amplitudes. Ligand can also be investigated using this method. Variability refinement is available in the Phenix software suite, accessible under the program name phenix.varref.

59 BASIC BIOLOGICAL SCIENCES↗