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837 results for “Conformity”
Investigating the conformal behaviour of SU(2) with one adjoint Dirac flavor --- data release
<p>This dataset collects data and analysis results for non-perturbative lattice field theory calculations investigating the SU(2) gauge theory with one Dirac fermion in the adjoint representation. More detailed information is included in the file README_datapackage.md</p>
Conformations and cryo-force spectroscopy of spray-deposited single-strand DNA on gold: Lifting atomic coordinates
<p>Here we provide the atomic coordinates and the topology file concerning the lifting process of a single stranded DNA molecule previously adsorbed on gold. In order to visualize it you will need a visualization software. Using VMD, you would only need to do in a terminal:</p> <p>vmd -e visualize.vmd </p> <p>and that is it. If you find this useful, please cite the corresponding paper:<br> Nature Communications 10, 685 (2019) [DOI: https://doi.org/10.1038/s41467-019-08531-4 ]</p>
Aquamarine: Quantum-Mechanical Exploration of Conformers and Solvent Effects in Large Drug-like Molecules
<p>Open challenges in computational drug design include the understanding and accurate description of solvent effects as well as collective dispersion interactions for realistic drug-like molecules. Both interactions profoundly influence the conformational stability of drug molecules and, consequently, the determination of other important quantum-mechanical (QM) observables. In this context, we here introduce the Aquamarine (AQM) dataset -- an extensive QM dataset that contains the structural and electronic information -- of 59,786 low-and high-energy conformers of 1,653 molecules containing up to 54 non-hydrogen atoms (including C, N, O, F, P, S and Cl). To gain insights into the solvent effects, we have carried out QM calculations of structures and properties in gas phase and in an aqueous solution modeled with implicit solvent. AQM contains over 40 global (molecular) and local (atom-in-a-molecule) physicochemical properties (including ground-state and response properties) per molecular structure computed at the tightly converged PBE0+MBD level of theory for gas-phase molecules, whereas PBE0+MBD supplemented with the modified Poisson-Boltzmann (MPB) model of water was used for solvated molecules. By treating both molecule-solvent and dispersion interactions, the AQM dataset can help understand the impact of both interactions in structure-property and property-property relationships of realistic drug-like molecules. Therefore, we propose the AQM dataset as a benchmark for current state-of-the-art machine learning methods for property prediction as well as for the <em>de novo</em> generation of large and flexible (solvated) molecules with pharmaceutical and biological relevance.</p>
Synthetic cryo electron subtomograms containing biomolecular complexes with continuous conformational variability, used for validating TomoFlow method
<p>Two datasets used for validating TomoFlow method, an optical-flow based approach for analyzing continuous conformational variability of biomolecular complexes in cryo electron subtomograms. The TomoFlow method and the methods used to synthesize the two test datasets have been fully described in the following article: "M. Harastani, M. Eltsov, A. Leforestier, S. Jonic, TomoFlow: Analysis of continuous conformational variability of macromolecules in cryogenic subtomograms based on 3D dense optical flow, Journal of Molecular Biology (2021), doi: https://doi.org/10.1016/j.jmb.2021.167381". Additionally, this article describes a test of TomoFlow using one experimental cryo electron tomography dataset (available in EMPIAR and EMDB databases under the accession codes EMPIAR-10679 and EMD-12699). </p>
Ligand binding remodels protein side chain conformational heterogeneity
<p>While protein conformational heterogeneity plays an important role in many aspects of biological function, including ligand binding, its impact has been difficult to quantify. Macromolecular X-ray diffraction is commonly interpreted with a static structure, but it can provide information on both the anharmonic and harmonic contributions to conformational heterogeneity. Here, through multiconformer modeling of time- and space-averaged electron density, we measure conformational heterogeneity of 743 stringently matched pairs of crystallographic datasets that reflect unbound/apo and ligand-bound/holo states. When comparing the conformational heterogeneity of side chains, we observe that when binding site residues become more rigid upon ligand binding, distant residues tend to become more flexible, especially in non-solvent exposed regions. Among ligand properties, we observe increased protein flexibility as the number of hydrogen bonds decrease and relative hydrophobicity increases. Across a series of 13 inhibitor bound structures of CDK2, we find that conformational heterogeneity is correlated with inhibitor features and identify how conformational changes propagate differences in conformational heterogeneity away from the binding site. Collectively, our findings agree with models emerging from NMR studies suggesting that residual side chain entropy can modulate affinity and point to the need to integrate both static conformational changes and conformational heterogeneity in models of ligand binding.</p>
Prediction of Conformational Variability for RRM proteins in inter3m data base
<p>Predictions for protein Conformational Variability for the entries in InteR3M (<a href="https://inter3mdb.loria.fr/">https://inter3mdb.loria.fr/</a>), performed with the software ConforMine (in preparation).</p>
Classification of GTP-dependent K-Ras4B active and inactive conformational states
<p>Dataset for the paper: Classification of GTP-dependent K-Ras4B active and inactive conformational states.</p> <p>Cite as: J. Chem. Phys. 158, 000000 (2023); DOI: 10.1063/5.0139181<br> Submitted: 18 December 2022; Accepted: 13 February 2023; Published Online: 13 February 2023.</p> <p>All molecular dynamics and molecular docking data presented, analyzed, and discussed in this paper are available at reasonable<br> requests submitted to the corresponding author. The following data are also available online: (i) file KRas4B_pdbs.zip, a compressed<br> archive including coordinate (.pdb) and structure (.psf) files for KRas-4B WT and D33E proteins, (ii) KRas4B_WT_traj.zip,<br> a compressed archive including trajectory files (.trr) for the WT KRas-4B runs, including 120 "*.trr"-formatted trajectories each corresponding to 40 ns of MD simulation time, and (iii) a sample Python script to generate a free energy plot as shown in Fig. 2.</p>
Paths to equilibrium in non-conformal collisions
<p>Non-conformal planar shockwave collisions with the typical dataset from the study <strong>arXiv:1703.09681 </strong>published in JHEP.</p>
Water conformation at three-phases contact lines
<p>This dataset contains detailed trajectories obtained from molecular dynamics simulations performed using GROMACS. The simulated system consists in a quasi-2-dimensional SPC/E water meniscus confined between solid substrates composed by silica quadrupoles. Details on the molecular model and the simulation technique can be found in the references article. The data collected in this dataset are utilized in a ongoing project aimed to demystify the motion of three-phases contact lines over hydrophilic surfaces.</p>
Synthetic cryo electron microscopy single particle images containing biomolecular complexes with continuous conformational variability used for validating DeepHEMNMA method and validation results
<p>This archive contains a synthetic dataset used for validating DeepHEMNMA method and the validation results. DeepHEMNMA is a deep learning extension of HEMNMA approach for analyzing continuous conformational variability of biomolecular complexes in cryo electron (cryo-EM) microscopy single particle images. We provide a training set of 20,000 images and an inference set of 50,000 images. The training images were used (1) to estimate the conformational and rigid-body parameters with HEMNMA and (2) to train the neural network using the parameters previously estimated with HEMNMA (the file with the HEMNMA-estimated parameters is provided). The inference images were used to infer the parameters with the trained neural network. Also, we provide (1) the input PDB structure, its normal modes, and the conformational and rigid-body parameters used to synthesize the 20,000 training images (ground-truth parameters) and (2) the conformational and rigid-body parameters inferred from the set of 50,000 inference images.</p> <p>The DeepHEMNMA method and the method for synthesizing images have been fully described in the following article: "Hamitouche I and Jonic S (2022), DeepHEMNMA: ResNet-based hybrid analysis of continuous conformational heterogeneity in cryo-EM single particle images. Front Mol Biosci 9, 965645. <a href="https://doi.org/10.3389/fmolb.2022.965645">https://doi.org/10.3389/fmolb.2022.965645</a> (in press)". Additionally, this article describes a test of DeepHEMNMA using one experimental cryo-EM dataset (available in EMPIAR database under the accession code EMPIAR-10016). </p>
Examples dataset in conformity assessment with measurement uncertainty
<p>Thie dataset summarizes examples that can be used to validate the software developed as part of 17SIP05 CASoft project, which aims at popularizing the use of the methodology described by the reference document JCGM106:2012 for decision-making in conformity assessment problems. </p>
Example dataset for openPMD-conform molecular dynamics data (MD domain extension)
<p>This dataset results from the molecular dynamics (MD) simulation of the photon-sample interaction. The photons are propagated through the SASE1 beamline and the SPB-SFX instrument at European XFEL, with an initial energy of 5 keV. The sample is the two-nitrogenase iron protein (2nip) with 4348 atoms. The simulation is performed with a demo version of XMDYN. The datasets were rewritten from the original XMDYN output into an hdf5 format that complies with the openPMD metadata standard for particle and mesh data and the proposed domain extension of this standard for MD data. The dataset "pure_2nip_pmi_out.opmd.h5" conforms the openPMD metadata MD domain extension strictly, while the dataset "pure_2nip_pmi_out.opmd.ff.h5" stores form factor results additionally for SingFEL diffraction simulation.</p> <p>This dataset is part of the Deliverable D5.1 in Workpackage 5 (Virtual Neutron and X-ray Laboratory) of the Photon and Neutron Open Science Cloud (PaNOSC).</p> <p>This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 823852.<br> </p>
CREMP-CycPeptMPDB: Conformer-rotamer ensembles of macrocyclic peptides for machine learning with permeability annotations
<p>CREMP-CycPeptMPDB: A resource generated for the rapid development and evaluation of machine learning models for permeable macrocyclic peptides. CREMP-CycPeptMPDB contains 3,258 unique macrocyclic peptides and their high-quality structural ensembles generated using the Conformer-Rotamer Ensemble Sampling Tool (CREST). Altogether, this dataset contains nearly 8.7 million unique macrocycle geometries, each annotated with energies derived from semi-empirical tight-binding DFT calculations and with experimental membrane permeability measurements obtained from the <a href="http://cycpeptmpdb.com/" target="_blank" rel="noopener">CycPeptMPDB</a> database. We anticipate that this dataset will enable the development of machine learning models that can improve peptide design and optimization for novel therapeutics.</p> <p>This dataset complements the <a title="CREMP" href="../doi/10.5281/zenodo.7931444" target="_blank" rel="noopener">CREMP dataset</a>, which contains a larger selection of conformer ensembles for homodetic macrocyclic peptides.</p> <p>We provide the data in two available formats, either as Python pickle files, which provide quick read access with RDKit version 2022.09.5 or later, and as text-based SDF files with associated metadata in JSON format. Each file is named based on its amino acid sequence, with residues separated by periods, using standard one-letter codes with lowercase letters representing D-amino acids and "Me" prefixes representing <em>N</em>-methylated amino acids. The sequences are in no particular order, e.g., "C.R.E.M.P" and "R.E.M.P.C" correspond to the same peptide macrocycle. The filename extensions are ".pickle", ".sdf", and ".json".</p> <p>Each file in the “pickle” folder contains a Python dictionary with amino acid sequence, SMILES, CREST metadata, and a single RDKit molecule object containing all conformers. All files in the folder were compressed into a single “pickle.tar.gz” archive. In the “sdf_and_json” folder, each individual SDF file contains all conformers, each associated with its own JSON file that contains CREST metadata. Similarly, all are compressed into another single archive, “sdf_and_json.tar.bz2”. A single summary CSV file is also provided containing ”sequence”, “smiles”, “num_monomers”, “num_atoms”, “num_heavy_atoms”, along with the CREST metadata “totalconfs”, “uniqueconfs”, “lowestenergy”, “poplowestpct”, “temperature”, “ensembleenergy”, “ensembleentropy”, and “ensemblefreeenergy”. The number of unique conformers with different 3D structures is given by “uniqueconfs”, while “totalconfs” includes the number of rotamers in addition.</p> <p>The unzipped sizes of the archives are approximately 13 GB for "pickle.tar.gz" and 84 GB for "sdf_and_json.tar.bz2". If you encounter errors when trying to load the pickle files, please make sure your RDKit version is at least 2022.09.5. If that doesn't work, try other Python versions.</p>
Data for the paper "Construction of an invertible mapping to boundary conforming coordinates for arbitrarily shaped toroidal domains."
<p>Data and scripts for the paper "Construction of an invertible mapping to boundary conforming coordinates for arbitrarily shaped toroidal domains."</p> <p>Presented at the "JOINT VARENNA - LAUSANNE INTERNATIONAL WORKSHOP: THEORY OF FUSION PLASMAS, 2024" and published in PPCF.</p>
Checkweigher Conformity Test Data
<p>Checkweighers (a type of industrial scale) were tested under different circumstances in laboratory conditions. Mass and speed were varied and, for each variation, 60 deviations of the measured mass from the nominal mass recorded. The checkweigher passes the test if the absolute mean error is at most the Maximum Permissible Mean Error (MPME) and the standard deviation is at most the Maximum Permissible Standard Deviation (MPSD). If any or both of these values are exceeded, the checkweigher fails the test. This dataset contains only passing checkweighers.</p> <p>File Format:</p> <p>The file contains one instance per row. The columns are tab-separated. The file extension (*.tsv) stands for "tab-separated values".</p> <p>Attributes:</p> <ul> <li>identifier: Data with the same identifier were collected on the same machine. String.</li> <li>mass: Nominal ("true") mass in g. Float.</li> <li>speed: Conveyor belt speed of the checkweigher in m/s. Not available for all instances. Float.</li> <li>mpme: Maximum Permissible Mean Error according to OIML R 51. Float.</li> <li>mpsd: Maximum Permissible Standard Deviation according to OIML R51. Float.</li> <li>deviation_0 - deviation_59: Deviations of the measured value from the nominal mass in g (60 repeated measurements). Float.</li> </ul> <p>Remarks:</p> <p>There is a typo in the OIML Bulletin publication using this dataset. It speaks of 95 measurements, but actually used and contained in this dataset are 94.</p>
'Invisible' Molecular Dynamics Revealed for a Conformationally Chiral π-Stacked Perylene Bisimide Foldamer
<p>Additional data to report <a href="https://doi.org/10.1002/anie.202414069">https://doi.org/10.1002/anie.202414069</a>:</p> <p><a name="_Hlk172654864"></a>Whilst energetic and kinetic aspects of folding processes are meanwhile well understood for natural biomacromolecules, the folding dynamics in so far studied artificial foldamer counterparts remain largely unexplored. This is due to the low energy barriers between their conformational isomers that make the dynamic processes undetectable with conventional methods such as UV/vis absorption, fluorescence, and NMR spectroscopy, making such processes ‘invisible’. Here we present an asymmetric perylene bisimide dimer (bis-PBI <strong>1</strong>) that possesses conformational chirality in its folded state. Owing to the large interconversion barrier (≥ 116 kJ mol<sup>–1</sup>), four stereoisomers could be separated and isolated. Since the interconversion between these stereoisomers requires the foldamer to first open and then to re-fold, the transformation of one stereoisomer into others allowed us to ‘visualize’ the dynamics of folding with time and determine its lifetimes and the energetic barriers associated with the folding process. Supported by quantum chemical calculations, we identified the open structure to be only a fleeting metastable state of higher energy. Our experimental observation of the kinetics associated with the molecular dynamics in the PBI foldamer advances the fundamental understanding of folding in synthetic foldamers and paves the way for the design of smart functional materials.</p>
Synthetic dataset used for validating MDSPACE method for analyzing continuous conformational variability of biomolecules in cryo-EM single particle images
<p>Synthetic dataset used for validating MDSPACE method for analyzing continuous conformational variability of biomolecules in cryo-EM single particle images. A README file with the contents of the dataset is included. </p>
Raw MS data for "Ligand-specific changes in conformational flexibility mediate long-range allostery in the lac repressor"
<p>These are the raw HDX/MS data for our paper: "Ligand-specific changes in conformational flexibility mediate long-range allostery in the lac repressor."</p>
Rereferenced Chemical Shift files used to select dihedrals for the 5 secondary structure conformations used to calculate Conformational Variability (ConVa).
<p>These Chemical Shifts in this repository were processed with ShiftCrypt (1) and then processed as described in the manuscript. </p> <p> </p> <p>1- Gabriele Orlando, Daniele Raimondi, Luciano Porto Kagami, Wim F Vranken, ShiftCrypt: a web server to understand and biophysically align proteins through their NMR chemical shift values, <em>Nucleic Acids Research</em>, Volume 48, Issue W1, 02 July 2020, Pages W36–W40, <a href="https://doi.org/10.1093/nar/gkaa391">https://doi.org/10.1093/nar/gkaa391</a></p>
Higher-order H1-conforming hierarchical basis functions for triangles and tetrahedra
<p>This data set contains H1-conforming basis functions for triangular and tetrahedral finite elements. They are hierarchical in terms of the polynomial order and feature symmetries in terms of barycentric coordinates. Moreover, they are pairwise orthogonal with respect to the interpolation operator. The resulting element matrices exhibit high levels of sparsity and moderate condition numbers in the higher-order case.</p> <p>The functions are given in terms two different formats:</p> <p>*.mat MATLAB data file with a MATLAB structure.</p> <p>*.xml file with a structure.</p>
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Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
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