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29 results for “frustrated”
Geometric Frustration Directs the Self-assembly of Nanoparticles with Crystallized Ligand Bundles
<p>This is the supporting dataset of the publication "Geometric Frustration Directs the Self-assembly of Nanoparticles with Crystallized Ligand Bundles".</p> <p><a href="https://doi.org/10.1021/acs.jpcb.4c04562">https://doi.org/10.1021/acs.jpcb.4c04562</a></p> <p>The description of the dataset can be found in the file README.txt</p>
The complex non-collinear magnetic orderings in Ba2YOsO6: A new approach to tuning spin-lattice interactions and controlling magnetic orderings in frustrated complex oxides
<p><strong>Project abstract</strong>: Frustrated magnets are one class of fascinating materials that host many intriguing phases such as spin ice, spin liquid and complex long-range magnetic orderings at low temperatures. In this work we use first-principles calculations to find that in a wide range of magnetically frustrated oxides, at zero temperature a number of non-collinear magnetic orderings are more stable than the type-I collinear ordering that is observed at finite temperatures. The emergence of non-collinear orderings in those complex oxides is due to higher-order exchange interactions that originate from second-row and third-row transition metal elements. This implies a collinear-to-noncollinear spin transition at sufficiently low temperatures in those frustrated complex oxides. Furthermore, we find that in a particular oxide Ba2YOsO6, experimentally feasible uniaxial strain can tune the material between two different non-collinear magnetic orderings. Our work predicts new non- collinear magnetic orderings in frustrated complex oxides at very low temperatures and provides a mechanical route to tuning complex non-collinear magnetic orderings in those materials. <br> <br> <strong>About this entry</strong>: We provide the input files of our DFT calculations for the studied complex oxides. The structures in POSCAR format and the INCAR files for all stabilized magnetic orderings in our study are all included. These files can be directly used into DFT calculations with VASP. Only the versions of PAW potentials are included in POT.info files owing to the VASP license restrictions.</p>
Supplementary material for "Surface frustration re-patterning underlies the structural landscape and evolvability of fungal orphan candidate effectors"
<p><strong>Tables</strong></p> <p>Table S1. List of fungal genomes analyzed in this work, associated references and properties.</p> <p>Table S2. List of all secreted proteins less than 300 amino-acids from the 20 fungal genomes. The table includes Signalp4.0 output, mature sequence, Espritz % disorder, pfam domains, AlphaFold top prediction pLDDT and the associated pdb file in Dataset S1.</p> <p>Table S3. Top Hits to pdb database for all OCE structures. 'network_node_name' corresponds to the portein identifier in the OCE structure similarity network provided in Dataset S3. 'Hidef_raw_community' corresponds to groups of structural OCE analogs identified by HiDEF community detection performed on the network provided in Dataset S3.</p> <p>Table S4. Table S4. List of the 62 major OCE folds with associated statistics. Columns I to AB provide the number of occurrences per species. Note that the actual number of members per species might be underestimated due to the stringent pipeline used for OCE identification (excluding proteins larger than 300 amino acids or containing PFAMs for instance).</p> <p> </p> <p>Table S5. Relative surface exposure, conformational flexibility and conservation data mapped on residues of members of the Alt-A1 and BoNT families. RMSD, root mean square deviation for all aligned atoms; Conservation, percentage conservation in multiple structure alignment.</p> <p>Table S6. Assignment of NCBI accessions to MMseqs clusters and assignment of MMseqs clusters to HMM matching-based super-clusters.</p> <p>Table S7. Co-mutation occurrences and associated p-values in two OCE clades from the Alt-A1 and KP6 families.</p> <p>Table S8. Amino acid properties inferred from mutation scans and frustration analyses in Alt-A1 cluster yellow1 and KP6 cluster 43. 'Number of aa variants' corresponds to the number of different amino acids found at each position (deletion counts as 1). 'Alanine scan ∆Z' and 'Deletion scan ∆Z' correspond to the difference between Z-score for the native protein agains itself and Z-score for the native protein against mutant at each position (either Alanine replacement or 5-aa deletion). 'Destabilization factor' is the average of column E and F. 'Stabilization factor' corresponds to the difference between expected structural variation due to destabilization factor and the observed structural variation in multiple mutants. 'netEffect' is difference between column G and H. 'Max co-mutation %' is the highest frequency of co-mutation observed with other residues in natural variants, with 'Min co-mutation p-value (Bonferroni corrected)' the associated p-value.Table S9. Sequence and delta Z of natural variants and mutants from AA1_cl25</p> <p>Table S9. List of natural variants and <em>in silico</em> mutants from the Alt-A1 cluster 25 analyzed in this work, including protein sequence and structure comparison scores (comparison with the reconstructed clade ancestor n0).</p> <p>Table S10. List of natural variants and in silico mutants from the KP6 cluster 43 analyzed in this work, including protein sequence and structure comparison scores (comparison with the reconstructed clade ancestor n0).</p> <p>Table S11. Summary statistics for the phylogenetic trees of 15 OCE clades analyzed for structure and frustration evolution.</p> <p>Table S12. Mapping of structural and frustration data onto phylogenetic trees for 15 OCE clades. The corresponding trees and protein structures are provided in Dataset S7.</p> <p><strong>Datasets</strong></p> <p>Dataset S1. AlphaFold rank1 models for 3 927 OCEs (.pdb format).</p> <p>Dataset S2. Pairwise structure comparison for 3 911 OCE. DALI matrix output containing pairwise Z-scores.</p> <p>Dataset S3. Network file including 2 561 OCEs with 3 or more vertices of Z-score weight 5.2 or more, in .sif and .xgmml formats.</p> <p>Dataset S4. Videos illustrating the mapping of relative surface exposure and structural variability in Alt-A1 and BoNT groups, amino-acids conservation, co-selected mutation patches and residue net stabilization effects on Alt-A1 clade 25 ancestor and KP6 cluster 43 ancestor. Color scales are as in Figure 2 and 3 respectively (.mp4 format).</p> <p>Dataset S5. Phylogenetic trees (.nwk), ancestral (.fasta) and modern variant (.faa) sequences, and AlphaFold best protein models (.pdb) for members of KP6 cluster 43 and Alt-A1 cluster 25. The archive includes 140 Alt-A1 protein structure and 128 KP6 protein structures.</p> <p>Dataset S6. Best predicted structures for 917 natural variants and mutants of AA1_cl25 and 801 natural variants and mutants of KP6_cl43 (.pdb format).</p> <p>Dataset S7. Phylogenetic trees (.nwk) and AlphaFold best protein models (.pdb) for 15 OCE clades. The file includes 2 598 protein structures distributed from clades AA1_s (139), AA1_t (135), AA1_y1 (140), AA1_y2 (90), AA1_y3 (128), BoNT_s (291), CIP_s (167), CIP_t (231), crystallin (233), GNK2 (189), KP6_cl3 (203), KP6_cl26 (111), KP6_cl43 (123), KP6_cl96 (231), KP6_cl242 (187).</p> <p><strong>Text and Figures</strong></p> <p>Text S1. Contains supplementary methods, results and figures S1 to S13.</p>
Supplementary Material for Design of Frustrated Lewis Pair Catalysts for Direct Hydrogenation of CO2
<p>Supplementary Material for "Design of Frustrated Lewis Pair Catalysts for Direct Hydrogenation of CO<sub>2</sub>"</p>
EmoPairCompete - Physiological Signals Dataset for Emotion and Frustration Assessment under Team and Competitive Behaviours
<p>Please refer to the documentation at: https://github.com/DTUComputeStatisticsAndDataAnalysis/EmoPairCompete</p>
Supplementary Simulation Data for "A contact-based analysis of local energetic frustration dynamics identifies key residues enabling RfaH fold-switch"
<p>Additional simulation data for "A contact-based analysis of local energetic frustration dynamics identifies key residues enabling RfaH fold-switch"</p> <p><strong>Content:</strong></p> <p>'clusters_foldswitch': Contains representative structures in PDB format of the refolding landscape of RfaH using all-atom structure-based models. The QA and QB values indicated in each filename correspond to the fraction of native contacts contain in the representative structure in comparison to the total number of contacts in the structure of the autoinhibited ⍺-folded (A) and active β-folded (B) states of the C-terminal domain of RfaH.</p> <p>'input_one_fs': Contains a trajectory of RfaH refolding from the ⍺-folded to the β-folded state, with each frame contained into a separate PDB file, totalling 400 PDB files. These files can be used with the frustration-based windowing method scripts and Colab notebook made available at https://github.com/pb3lab/RfaH-frustration</p> <p>'input_many_fs': Contains several trajectory of RfaH reversible refolding between the ⍺-folded and β-folded states, with each frame contained into a separate PDB file, totalling 11,999 PDB files. These files can be used with the frustration-based windowing method scripts and Colab notebook made available at https://github.com/pb3lab/RfaH-frustration</p> <p>'output_one_fs': Contains output results from the analysis of local energetic frustration dynamics of the 400 frames contained in 'input_one_fs' using the windowing method available in the Colab notebook at https://github.com/pb3lab/RfaH-frustration.</p> <p>'output_many_fs': Contains output results from the analysis of local energetic frustration dynamics of the 11,999 frames contained in 'input_many_fs' using the windowing method available in the Python script at https://github.com/pb3lab/RfaH-frustration.</p>
Frustration Between Preferred States of Complementary Trinucleotide Repeat DNA Hairpins Anticorrelates with Expansion Disease Propensity
<p>The expansion of DNA trinucleotide repeats (TRs) beyond a threshold often results in neurodegenerative diseases in humans. The mechanisms causing these expansions remain unknown, although the tendency of TR ssDNA to self-associate into hairpins that slip along their length is widely presumed to be related. Here we apply single molecule FRET (smFRET) experiments and molecular dynamics simulations to determine conformational stabilities and slipping dynamics for CAG, CTG, GAC, and GTC hairpins. By developing novel analysis approaches for states with closely spaced FRET efficiencies along with improved transition detection algorithms, we determined the kinetic slipping schemes for these hairpins. Tetraloops are favored in CAG (89%), CTG (89%) and GTC (69%) while GAC favors triloops. We also determined that TTG interrupts near the loop in the CTG hairpin stabilize the hairpin against slipping (as do CAA substitutions in CAG hairpins). The different loop stabilities have implications for intermediate structures that may form when TR-containing duplex DNA opens. Opposing hairpins in the (CAG) ∙ (CTG) duplex would have matched stability whereas opposing hairpins in a (GAC) ∙ (GTC) duplex would have unmatched stability. This unmatched stability would introduce mechanical stress or frustration in the (GAC) ∙ (GTC) opposing hairpins that would be absent in (CAG) ∙ (CTG) structures. Given the biological observation that the CAG and CTG TR can undergo large, disease-related expansion whereas the GAC and GTC sequences do not, the mechanical stability differences we have identified can inform and constrain models of the expansion mechanisms of TR regions.</p>
The violation of Bell inequality in frustrated interference
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Frustration Between Preferred States of Complementary Trinucleotide Repeat DNA Hairpins Anticorrelates with Expansion Disease Propensity
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Data from: Geometrical frustration in nonlinear mechanics of screw dislocation
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Sequence-structure-function relationships in class I MHC: a local frustration perspective
<p>Class I Major Histocompatibility Complex (MHC) binds short antigenic peptides with the help of Peptide Loading Complex (PLC), and presents them to T-cell Receptors (TCRs) of cytotoxic T-cells and Killer-cell Immunglobulin-like Receptors (KIRs) of Natural Killer (NK) cells. With more than 10000 alleles, the Human Leukocyte Antigen (HLA) chain of MHC is the most polymorphic protein in humans. This allelic diversity provides a wide coverage of peptide sequence space, yet does not affect the three-dimensional structure of the complex. Moreover, TCRs mostly interact with pMHC in a common diagonal binding mode, and KIR-pMHC interaction is allele-dependent. With the aim of establishing a framework for understanding the relationships between polymorphism (sequence), structure (conserved fold) and function (protein interactions) of the MHC, we performed here a local frustration analysis on pMHC homology models covering 1436 HLA I alleles. An analysis of local frustration profiles indicated that (1) variations in MHC fold are unlikely due to minimally-frustrated and relatively conserved residues within the HLA peptide-binding groove, (2) high frustration patches on HLA helices are either involved in or near interaction sites of MHC with the TCR, KIR, or Tapasin of the PLC, and (3) peptide ligands mainly stabilize the F-pocket of HLA binding groove.</p>
Supplementary Material for Mapping Active Site Geometry to Activity in Immobilized Frustrated Lewis Pair Catalysts
<p>Supplementary Material for "Mapping Active Site Geometry to Activity in Immobilized Frustrated Lewis Pair Catalysts".</p>
Spin wave stiffness and damping in a frustrated chiral helimagnet Co8Zn8Mn4 as measured by small-angle neutron scattering
<p>The repository contains the data presented in the figures in the manuscript entitled <br> "Spin wave stiffness and damping in a frustrated chiral helimagnet Co8Zn8Mn4 as measured by small-angle neutron scattering".</p> <p>Requests for further information can be directed to the corresponding authors Victor Ukleev (victor.ukleev 'at' psi.ch).</p>
Raw data from the pCUT+MC approach for the antiferromagnetic Heisenberg square lattice bilayer model with (non-frustrating) long-range interactions
<p>This directory contains the data from the pCUT+MC approach for the antiferromagnetic Heisenberg square lattice bilayer model with (non-frustrating) long-range interactions.</p> <p>To get an overview of the organization of the directory and a description of the data we recommend the README.md file.</p> <p>The data is published in P. Adelhardt, J. A. Koziol, A. Langheld, and K. P. Schmidt, "Monte Carlo based techniques for quantum magnets with long-range interactions", <a href="https://arxiv.org/abs/2403.00421">arXiv:2403.00421</a></p>
Data for "Diabatic Quantum Annealing for the Frustrated Ring Model"
<p>This repository contains data for the paper "Diabatic Quantum Annealing for the Frustrated Ring Model". In particular, the Jupyter notebook within the repository reproduces the figures that contain data in our paper. We also include a Qiskit implementation of our algorithm and the associated code for the population levels.</p>
Tetrafluorenofulvalene as a Sterically Frustrated Open-Shell Alkene
<ul> <li>Cartesian coordinates of calculated structures</li> <li>Source data for Fig. 4 and Supplementary Fig. 12, 16–18, and 21</li> </ul>
Geometrical frustration and incommensurate magnetic order in Na3RuO4 with two triangular motifs
<p>Auxiliary data for the frustrated magnet Na3RuO4: magnetic susceptibility, specific heat, lattice parameters, magnetic moments, and the results of DFT calculations for the magnetic exchange couplings</p>
Sequence-structure-function relationships in class I MHC: a local frustration perspective
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Molecular dynamics trajectories for ionic conductors in: Paradigms of frustration in superionic solid electrolytes
<p>Superionic solid electrolytes have widespread use in energy devices, but the fundamental motivations for fast ion conduction are often elusive. Here, we draw upon atomistic simulations of a wide range of halide, oxide, sulfide, and <em>closo</em>-borate superionic conductors to illustrate some of the key features that enhance local cation mobility in these solids. We classify three types of frustration that create competition between different local atomic preferences, thereby flattening the diffusive energy landscape and enhancing entropy. These include chemical frustration, which derives from competing factors in the anion-cation interaction; structural frustration, which is connected to the lack of a clear site preference for mobile ion ordering; and dynamical frustration, which is associated with temporary fluctuations in the energy landscape due to anion orientations or cation reconfigurations. For each class of frustration, we provide detailed simulation analyses of multiple materials to show how ion mobility is facilitated, resulting in stabilizing factors that are both entropic and enthalpic in origin. Implications for identifying suitable descriptors for superionic conductivity are discussed.</p>
Study Brain Mechanisms of Frustration With Magnetoencephalography in Healthy Volunteers
ClinicalTrials.gov study NCT06484088. IPD Sharing: YES. Countries: 1. Publications: 38.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.