Costameric integrin and sarcoglycan protein levels are altered in a Drosophila model for Limb-girdle
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Bawa, Simranjot↗
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Results for “domain structure”
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Geometry-complete perceptron networks for 3D molecular graphs
Abstract Motivation The field of geometric deep learning has recently had a profound impact on several scientific domains such as protein structure prediction and design, leading to methodological advancements within and outside of the realm of traditional machine learning. Within this spirit, in this work, we introduce GCPNet, a new chirality-aware SE(3)-equivariant graph neural network designed for representation learning of 3D biomolecular graphs. We show that GCPNet, unlike previous representation learning methods for 3D biomolecules, is widely applicable to a variety of invariant or equivariant node-level, edge-level, and graph-level tasks on biomolecular structures while being able to (1) learn important chiral properties of 3D molecules and (2) detect external force fields. Results Across four distinct molecular-geometric tasks, we demonstrate that GCPNet’s predictions (1) for protein–ligand binding affinity achieve a statistically significant correlation of 0.608, more than 5%, greater than current state-of-the-art methods; (2) for protein structure ranking achieve statistically significant target-local and dataset-global correlations of 0.616 and 0.871, respectively; (3) for Newtownian many-body systems modeling achieve a task-averaged mean squared error less than 0.01, more than 15% better than current methods; and (4) for molecular chirality recognition achieve a state-of-the-art prediction accuracy of 98.7%, better than any other machine learning method to date. Availability and implementation The source code, data, and instructions to train new models or reproduce our results are freely available at https://github.com/BioinfoMachineLearning/GCPNet.
59 BASIC BIOLOGICAL SCIENCES↗
Spin-orbital order and excitons in magnetoresistive HoBi
The magnetism of the rocksalt fcc rare-earth monopnictide HoBi, a candidate topological material with extreme magnetoresistance, is investigated. From the Ho 3+ non-Kramers J=8 spin-orbital multiplet, the cubic crystal electric field yields six nearly degenerate low-energy levels. These constitute an anisotropic magnetic moment with a Jahn-Teller-like coupling to the lattice. In the cubic phase for T>T N =5.72(1)K, the paramagnetic neutron scattering is centered at k=($\frac{1}{2}$$\frac{1}{2}$$\frac{1}{2}$) and was fit to dominant antiferromagnetic interactions between Ho spins separated by {100} and ferromagnetic interactions between spins displaced by {$\frac{1}{2}$ $\frac{1}{2}$ 0}. For T < T N , a type-II AFM long-range order with k=($\frac{1}{2}$$\frac{1}{2}$$\frac{1}{2}$) develops along with a tetragonal lattice distortion. While neutron diffraction from a multidomain sample cannot unambiguously determine the spin orientation within a domain, the bulk magnetization, structural distortion, and our measurements of the magnetic excitations all show the easy axis coincides with the tetragonal axis. Finally, the weakly dispersive excitons for T < T N can be accounted for by a spin Hamiltonian that includes the crystal electric field and exchange interactions within the random phase approximation.
36 MATERIALS SCIENCE↗
Molecular Mechanism of Polysaccharide Acetylation by the Arabidopsis Xylan O-acetyltransferase XOAT1
Xylans are a major component of plant cell walls. O-Acetyl moieties are the dominant backbone substituents of glucuronoxylan in dicots and play a major role in the polymer-polymer interactions that are crucial for wall architecture and normal plant development. Here, we describe the biochemical, structural, and mechanistic characterization of Arabidopsis (Arabidopsis thaliana) xylan O-acetyltransferase 1 (XOAT1), a member of the plant-specific Trichome Birefringence Like (TBL) family. Detailed characterization of XOAT1-catalyzed reactions by real-time NMR confirms that it exclusively catalyzes the 2-O-acetylation of xylan, followed by nonenzymatic acetyl migration to the O-3 position, resulting in products that are monoacetylated at both O-2 and O-3 positions. In addition, we report the crystal structure of the catalytic domain of XOAT1, which adopts a unique conformation that bears some similarities to the a/ß/a topology of members of the GDSL-like lipase/acylhydrolase family. Finally, we use a combination of biochemical analyses, mutagenesis, and molecular simulations to show that XOAT1 catalyzes xylan acetylation through formation of an acyl-enzyme intermediate, Ac–Ser-216, by a double displacement bi-bi mechanism involving a Ser-His-Asp catalytic triad and unconventionally uses an Arg residue in the formation of an oxyanion hole.
acetylation↗
Fully Homomorphic Encryption
This code implements a Fully Homomorphic Encryption (FHE) system, enabling secure computation on encrypted data without requiring decryption. It supports encryption, decryption, and homomorphic operations like matrix multiplication and addition. This code is adaptable for integrating FHE into linear-time invariant (LTI) systems, including digital control and filtering. With proper configuration from subject matter expertise, encrypted system parameters and signals can be manipulated to perform tasks like state updates, output calculations, and convolution in the encrypted domain. By preserving the structure of LTI systems while ensuring privacy, the framework facilitates secure applications in areas such as autonomous systems, signal processing, and industrial automation. The code initializes the encryption system using parameters provided in the env dictionary. These parameters include the ciphertext modulus, key dimension, plaintext fixed-point scaling factor, and noise bound. During initialization, a secret key is generated, which is essential for encrypting and decrypting data securely. The modular design allows users to tailor these parameters to specific use cases or security requirements. The code implements multiple cryptographic schemes. The learning with errors (LWE) encryption method encodes cleartext message to their plaintext fixed-point representation then encrypted into ciphertext space with additive noise. This noise ensures the security of the scheme, relying on the computational hardness of the LWE problem. The code also includes the Gentry-Sahai-Waters (GSW) scheme based off the LWE problem. Homomorphic matrix multiplication is performed between the LWE and GSW to encrypted data. This is achieved using a decomposition function on the LWE ciphertext during the multiplication operation. For higher-dimensional data, the code includes a method to encrypt entire matrices (GSWMat) using GSW encryption. These encrypted matrices can then be used for homomorphic matrix multiplications (MatMult). The decryption function uses the secret key to recover the original plaintext, removing the added noise and scaling that was originally applied during encryption.
Lois, Roberts [Idaho National Laboratory (INL), Id↗
Insight into Molecular Basis and Dynamics of Full-length CRaf Kinase in Cellular Signaling Mechanism
This study presents the first large-scale simulation using an initial structure predicted by AI/ML algorithms for the 648-amino-acid CRaf kinase, which plays a key role in cellular signaling. Simulation results show the evolution of the predicted structure into much more compact structures with inter-domain interactions that shed insights into auto-inhibition mechanism, paradoxical effect, activation, and recruitment pathways in the CRaf kinase. Newly identified epitopes in the CRaf may suggest additional drug targets. The results were published in Biophysical Journal, DOI:10.1016/j.bpj.2024.06.028.
59 BASIC BIOLOGICAL SCIENCES↗
Adjoint-optimized nanoscale light extractor for nitrogen-vacancy centers in diamond
Abstract We designed a nanoscale light extractor (NLE) for the efficient outcoupling and beaming of broadband light emitted by shallow, negatively charged nitrogen-vacancy (NV) centers in bulk diamond. The NLE consists of a patterned silicon layer on diamond and requires no etching of the diamond surface. Our design process is based on adjoint optimization using broadband time-domain simulations and yields structures that are inherently robust to positioning and fabrication errors. Our NLE functions like a transmission antenna for the NV center, enhancing the optical power extracted from an NV center positioned 10 nm below the diamond surface by a factor of more than 35, and beaming the light into a ±30° cone in the far field. This approach to light extraction can be readily adapted to other solid-state color centers.
42 ENGINEERING↗
Assessing Critical Conditions for Scour Near Obstructions using Bed Shear, Particle Onset of Motion Balances, and CFD-DEM Modeling of Granular Beds
Computational Fluid Dynamics combined with a Discrete Element Method is one of the computational methods that can be used to model multiphase flows. In this method various phases, gas and liquid or solid, are present in the same computational domain. The local averaged Navier–Stokes equations determine the flow of the continuous phase fluid and are solved using the traditional CFD finite volume approach. DEM is based on a Lagrangian formulation, which solves the equations of motion, expressed in ordinary differential equations, for representative particles as they move in space and time. The interactions between the continuous fluid phase and discrete solid phase are modeled with the use of Newton’s laws of motion via drag force. The particles interact with each other and with the boundaries of the fluid continuum, and the resulting contact forces are included in the equations of motion. The properties of solid particles and boundaries are treated as elastic bodies, with specified density, elastic modulus, and Poisson’s ratio. Particle shapes may vary from single spherical particles to more complex-shaped composite particles. The particles may be introduced into the domain by random or structured injection at a point, surface, or volume, depending on the application. More details on the formulation can be found in the Simcenter STAR-CCM+ User’s Manual and OpenFOAM website.
97 MATHEMATICS AND COMPUTING↗
Automated Energy-Dispersive X-ray Spectroscopy Analysis for Multi-Modal Few-Shot Learning
Scanning transmission electron microscopy (STEM) is a powerful tool that allows for the atomic-scale analysis of a materials’ structure, chemistry, and defect domains (Akers et al. 2021). The current generation of microscopes generate vast amounts of data, surpassing the limits of effective manual analysis traditionally performed by domain experts (Spurgeon et al. 2021). While recent strides in machine learning have significantly enhanced the processing of large and intricate datasets acquired through electron microscopy, the prevalent use of proprietary software packages for initial data collection poses a challenge. In many cases, these software packages act as a ‘black box’, constraining user functionality and hindering the output of data in a format that is conducive to seamless integration into machine learning models. This work addresses these challenges by adapting HyperSpy, an open-source Python library, for the analysis and quantification of raw energy dispersive spectroscopy (EDS) data acquired through STEM. The modified HyperSpy code successfully facilitates user-defined segmentation of the data, enabling the integration of atomic %, weight %, and raw EDS spectra for each segmented region into an existing few-shot machine learning model. While initial results reveal discrepancies in quantified atomic and weight percentages when compared to proprietary software, ongoing efforts aim to rectify this issue by refining the fit of the HyperSpy model to the EDS spectra. Overall, this research underscores the potential of open-source tools like HyperSpy to enhance the accessibility of analytical tools, fostering a transparent and user-friendly environment for seamlessly incorporating electron microscopy data into machine learning models.
36 MATERIALS SCIENCE↗
Simultaneous Inversion and Sensing for Damage Detection
Presentation of damage detection and experimental design approaches for structures under frequency-domain dynamics
Chen, Mark Jia Yan↗
Structure and conformational dynamics of Clostridioides difficile toxin A
Clostridioides difficile toxin A and B (TcdA and TcdB) are two major virulence factors responsible for diseases associated with C. difficile infection (CDI). Here, we report the 3.18-Å resolution crystal structure of a TcdA fragment (residues L843–T2481), which advances our understanding of the complete structure of TcdA holotoxin. Our structural analysis, together with complementary single molecule FRET and limited proteolysis studies, reveal that TcdA adopts a dynamic structure and its CROPs domain can sample a spectrum of open and closed conformations in a pH-dependent manner. Furthermore, a small globular subdomain (SGS) and the CROPs protect the pore-forming region of TcdA in the closed state at neutral pH, which could contribute to modulating the pH-dependent pore formation of TcdA. A rationally designed TcdA mutation that trapped the CROPs in the closed conformation showed drastically reduced cytotoxicity. Taken together, these studies shed new lights into the conformational dynamics of TcdA and its roles in TcdA intoxication.
59 BASIC BIOLOGICAL SCIENCES↗
Swine Host Protein Coiled-Coil Domain-Containing 115 (CCDC115) Interacts with Classical Swine Fever Virus Structural Glycoprotein E2 during Virus Replication
Interactions between the major structural glycoprotein E2 of classical swine fever virus (CSFV) with host proteins have been identified as important factors affecting virus replication and virulence. Previously, using the yeast two-hybrid system, we identified swine host proteins specifically interacting with CSFV E2. In this report, we use a proximity ligation assay to demonstrate that swine host protein CCDC115 interacts with E2 in CSFV-infected swine cells. Using a randomly mutated E2 library in the context of a yeast two-hybrid methodology, specific amino acid mutations in the CSFV E2 protein responsible for disrupting the interaction with CCDC115 were identified. A recombinant CSFV mutant (E2ΔCCDC115v) harboring amino acid changes disrupting the E2 protein interaction with CCDC115 was produced and used as a tool to assess the role of the E2–CCDC115 interaction in viral replication and virulence in swine. CSFV E2ΔCCDC115v showed a slightly decreased ability to replicate in the SK6 swine cell line and a greater replication defect in primary swine macrophage cultures. A decreased E2–CCDC115 interaction detected by PLA is observed in cells infected with E2ΔCCDC115v. Importantly, animals intranasally infected with 105 TCID50 of E2ΔCCDC115v experienced a significantly longer survival period when compared with those infected with the parental Brescia strain. This result would indicate that the ability of CSFV E2 to bind host CCDC115 protein during infection plays an important role in virus replication in swine macrophages and in virus virulence during the infection in domestic swine.
59 BASIC BIOLOGICAL SCIENCES↗
Solving the Dynamics-Aware Economic Dispatch Problem with the Koopman Operator
The dynamics-aware economic dispatch (DED) problem embeds low-level generator dynamics and operational constraints to enable near real-time scheduling of generation units in a power network. DED produces a more dynamic supervisory control policy than traditional economic dispatch (T-ED) that reduces overall generation costs. However, in contrast to T-ED, DED is a nonlinear, non-convex optimization problem that is computationally prohibitive to solve. We introduce a machine learning-based operator-theoretic approach for solving the DED problem efficiently. Specifically, we develop a novel discrete-time Koopman Operator (KO) formulation that embeds domain information into the structure of the KO to learn high-fidelity approximations of the generator dynamics. Using the KO approximation, the DED problem can be reformulated as a computationally tractable linear program (abbreviated DED-KO). We demonstrate the high solution quality and computational-time savings of the DED-KO model over the original DED formulation on a 9-bus test system.
King, Ethan↗
Measuring the Neutron Spin Asymmetry A1n in the Valence Quark Region in Hall C at Jefferson Lab
The quest to understand how the nucleon spin is decomposed into its constituent quark and gluon spin and orbital angular momentum (OAM) components has been at the forefront of nuclear physics for decades. Due to the non-perturbative nature of Quantum Chromodynamics (QCD) - the theory describing how quarks and gluons bind together to form protons and neutrons - making absolute predictions of nucleon spin structure is generally difficult, especially as a function of its quark and gluon longitudinal momentum fraction x. Measurements involving nucleon spin structure serve as a sensitive test for QCD, including ab-initio lattice QCD calculations due to the advent of the quasi-PDF formalism, and various predictions that diverge at large-x. The neutron spin asymmetry An 1 at high?x is a key observable for probing nucleon spin structure. In the valence domain (x > 0.5), sea effects are expected to be negligible, and so the total nucleon spin is considered to be carried by the valence quarks. The valence region can therefore enable us to study the role of quark OAM and other non-perturbative effects of the strong force. An 1 was measured in the deep inelastic scattering region of 0.40 < x < 0.75 and 6 < Q2 < 10 GeV2 in Hall C at Jefferson Lab using a 10.4 GeV longitudinally polarized electron beam, upgraded polarized 3He target, and the High Momentum Spectrometer (HMS) and Super High Momentum Spectrometer (SHMS). E12- 06-110 provides the first precision data in the valence quark region above x = 0.60, and its preliminary results proved consistent with earlier data disqualifying a pQCD model that excluded quark OAM. Combined with previous world proton data, the ratio of the polarized-to-unpolarized up quark momentum distribution (?u + ?u)/(u + u) remained positive at large-x, and the down quark (?d + ?d)/(d + d) remained negative.
Rehfuss, Melanie↗
A deubiquitylase with an unusually high-affinity ubiquitin-binding domain from the scrub typhus pathogen Orientia tsutsugamushi
Ubiquitin mediated signaling contributes critically to host cell defenses during pathogen infection. Many pathogens manipulate the ubiquitin system to evade these defenses. Here we characterize a likely effector protein bearing a deubiquitylase (DUB) domain from the obligate intracellular bacterium Orientia tsutsugamushi, the causative agent of scrub typhus. The Ulp1-like DUB prefers ubiquitin substrates over ubiquitin-like proteins and efficiently cleaves polyubiquitin chains of three or more ubiquitins. The co-crystal structure of the DUB (OtDUB) domain with ubiquitin revealed three bound ubiquitins: one engages the S1 site, the second binds an S2 site contributing to chain specificity and the third binds a unique ubiquitin-binding domain (UBD). The UBD modulates OtDUB activity, undergoes a pronounced structural transition upon binding ubiquitin, and binds monoubiquitin with an unprecedented ~5 nM dissociation constant. The characterization and high-resolution structure determination of this enzyme should aid in its development as a drug target to counter Orientia infections.
59 BASIC BIOLOGICAL SCIENCES↗
Comprehensive analysis of the human ESCRT-III-MIT domain interactome reveals new cofactors for cytokinetic abscission
The 12 related human ESCRT-III proteins form filaments that constrict membranes and mediate fission, including during cytokinetic abscission. The C-terminal tails of polymerized ESCRT-III subunits also bind proteins that contain Microtubule-Interacting and Trafficking (MIT) domains. MIT domains can interact with ESCRT-III tails in many different ways to create a complex binding code that is used to recruit essential cofactors to sites of ESCRT activity. Here, we have comprehensively and quantitatively mapped the interactions between all known ESCRT-III tails and 19 recombinant human MIT domains. We measured 228 pairwise interactions, quantified 60 positive interactions, and discovered 18 previously unreported interactions. We also report the crystal structure of the SPASTIN MIT domain in complex with the IST1 C-terminal tail. Three MIT enzymes were studied in detail and shown to: (1) localize to cytokinetic midbody membrane bridges through interactions with their specific ESCRT-III binding partners (SPASTIN-IST1, KATNA1-CHMP3, and CAPN7-IST1), (2) function in abscission (SPASTIN, KATNA1, and CAPN7), and (3) function in the ‘NoCut’ abscission checkpoint (SPASTIN and CAPN7). Our studies define the human MIT-ESCRT-III interactome, identify new factors and activities required for cytokinetic abscission and its regulation, and provide a platform for analyzing ESCRT-III and MIT cofactor interactions in all ESCRT-mediated processes.
59 BASIC BIOLOGICAL SCIENCES↗
Interface Nucleus Templating of Modular Intermetallic Morphologies: Chemical Pressure Complementarity, Columnar Domains, and Complex Disorder in Y 13 Ag 42.7 Zn 29.7
One element of the diversity of intermetallic phases is the formation of complex structures from the assembly of fragments of simpler structures. Recently, we devised the Interface Nuclear Approach as a model for understanding such modular arrangements, in which the intergrowth of different structures is driven by chemical pressure (CP) relief at shared motifs at the domain interfaces, referred to as interface nuclei. In this Article, we present the synthesis, crystal structure, and CP analysis of a new compound that expands on this theme, Y 13 Ag 42.7 Zn 29.7 . Its hexagonal structure contains interpenetrating domains based on the CaPd 5+x and EuMg 5 types. The CaPd 5+x -based regions are reminiscent of the lamellar intergrowth structures previously observed in the Y−Ag−Zn system. In Y 13 Ag 42.7 Zn 29.7 , however, the domains have a different morphology, forming columns that adopt a hexagonal rod-packing. The geometrical features of the remaining spaces are assigned, using the program GrowDomain, to the cores of trigonal units of the EuMg 5 type, while layers of disordered atoms occur at heights along z where the parent structures are mismatched. At the CaPd 5+x -type/EuMg 5 -type interfaces, simple interface nucleus motifs with strong CP-complementarity can be identified, while their distribution within the parent structures supports the notion of templated architectures in modular intermetallics.
Chemical structure↗
Proximity Ferroelectricity in Compositionally Graded Structures
Proximity ferroelectricity is a novel paradigm for inducing ferroelectricity in a non-ferroelectric polar material, such as AlN or ZnO that are typically unswitchable with an external field below their dielectric breakdown field. When placed in direct contact with a thin switchable ferroelectric layer (such as Al 1-x Sc x N or Zn 1-x Mg x O), they become a practically switchable ferroelectric. Using the thermodynamic Landau-Ginzburg-Devonshire theory, in this work, we perform the finite element modeling of the polarization switching in the compositionally graded AlN-Al 1-x Sc x N, ZnO-Zn 1-x Mg x O, and MgO-Zn 1-x Mg x O structures sandwiched in both a parallel-plate capacitor geometry as well as in a sharp probe-planar electrode geometry. We reveal that the compositionally graded structure allows the simultaneous switching of spontaneous polarization in the whole system by a coercive field significantly lower than the electric breakdown field of unswitchable polar materials. The physical mechanism is the depolarization electric field determined by the gradient of chemical composition “x”. The field lowers the steepness of the switching barrier in the otherwise unswitchable parts of the compositionally graded AlN-Al 1-x Sc x N and ZnO-Zn 1-x Mg x O structures. In the MgO-like regions of the compositionally graded MgO-Zn 1-x Mg x O structure, a shallow double-well free energy potential emerges. Proximity ferroelectric switching of the compositionally graded structures placed in the probe-electrode geometry occurs due to nanodomain formation under the tip. We predict that a gradient of chemical composition “x” significantly lowers effective coercive fields of the compositionally graded AlN-Al 1-x Sc x N and ZnO-Zn 1-x Mg x O structures compared to the coercive fields of the corresponding multilayers with a uniform chemical composition in each layer. A tip-induced switching further lowers the coercive field, enabling control of ferroelectric domains in otherwise unswitchable compositionally graded structures, which can provide nanoscale domain control for memory, actuation, sensing, and optical applications.
36 MATERIALS SCIENCE↗