Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
173
datasets available to search
ShareScore release 0.9.0
Dataset results
173 results for “molecular recognition”
Fig. 6 in Enlarging the monotypic Monocarpieae (Annonaceae, Malmeoideae): recognition of a second genus from Vietnam informed by morphology and molecular phylogenetics
Fig. 6. – Leoheo domatiophorus Chaowasku, D.T. Ngo & H.T. Le, showing habit with inflorescences and flowers. [HUAF collectors 2009-03-19-ND,CMUB] [Drawing: A. Damthongdee]
Fig. 5 in Enlarging the monotypic Monocarpieae (Annonaceae, Malmeoideae): recognition of a second genus from Vietnam informed by morphology and molecular phylogenetics
Fig. 5. – Reproductive organs of Leoheo domatiophorus Chaowasku, D.T. Ngo & H.T. Le: A. Flower with petals and stamens removed; B. Flower with petals, stamens, and carpels removed, back view, showing outer side of sepals; C. Same as (B), but on another side, showing a volcano-shaped torus and inner side of sepals; D. Inner side of an outer petal; E. Outer side of an outer petal; F. Inner side of an inner petal; G. Outer side of an inner petal; H. Stamen, abaxial side; I. Stamen, adaxial side; J. Carpels, showing enlarged and irregularly lobed stigmas; K. Fruit, showing longitudinal ridges on monocarp surface; L. Seed, lateral view, showing a raphe; M. Seed, lateral view, showing a pitteand slightly rugose surface; N. Cross section of a seed, showing spiniform endosperm ruminations. [A–J: HUAF collectors 2009-03-19-ND, CMUB; K: Chaowasku 131, CMUB; L–N: Chaowasku 165, CMUB] [Drawing: A. Damthongdee]
Fig. 3 in Enlarging the monotypic Monocarpieae (Annonaceae, Malmeoideae): recognition of a second genus from Vietnam informed by morphology and molecular phylogenetics
Fig. 3. – Inflorescence position of Leoheo Chaowasku (A) and Monocarpia Miq. (B). A. Axillary inflorescences/infructescences of Leoheo domatiophorus Chaowasku, D.T. Ngo & H.T. Le; B. Terminal inflorescence of Monocarpia kalimantanensis Kessler. [A: HUAF collectors 2009-03-19-ND, CMUB; B: Sidiyasa et al. 3469, L] [Photos: A: D.T. Ngo; B: Arbainsyah]
Fig. 4 in Enlarging the monotypic Monocarpieae (Annonaceae, Malmeoideae): recognition of a second genus from Vietnam informed by morphology and molecular phylogenetics
Fig. 4. – Lower leaf surface of Leoheo Chaowasku (A) and Monocarpia Miq. (B). A. Leoheo domatiophorus Chaowasku, D.T. Ngo & H.T. Le, with a hairy domatium; B. Monocarpia maingayi (Hook. f. & Thomson) I.M. Turner, without domatia. [A: Chaowasku 131, CMUB; B: Promchua 18, CMUB]
Fig. 2. – A in Enlarging the monotypic Monocarpieae (Annonaceae, Malmeoideae): recognition of a second genus from Vietnam informed by morphology and molecular phylogenetics
Fig. 2. – A. Leaf of Monocarpia kalimantanensis Kessler, showing conspicuous intramarginal veins; B. Fruit of Monocarpia maingayi (Hook. f. & Thomson) I.M. Turner, showing monocarps without longitudinal ridges; C– H: Leoheo domatiophorus Chaowasku, D.T. Ngo & H.T. Le; C. Leaf without intramarginal veins; D. Fruit, showing monocarps with longitudinal ridges; E. Flowering branches; F. Dissected flower and young fruit; G. Dissected flower, showing detached stamens and stigmas; H. Flower, showing enlarged and irregularly lobed stigmas. [A: Sidiyasa et al. 3469, L; B: Gardner & Sidisunthorn ST0541a, L; C–D: Chaowasku 131, CMUB; E–H: HUAF collectors 2009-03-19-ND, CMUB] [Photos: A: Arbainsyah; B: S. Gardner & P. Sidisunthorn; C–H: D.T. Ngo]
Molecular recognition and dynamics of linear poly-ubiquitins: integrating coarse-grain simulations and experiments
<p>Poly-ubiquitin chains are flexible multidomain proteins, whose conformational dynamics enable their molecular recognition by a large number of partners in multiple biological pathways. By using alternative linkage, it is possible to obtain poly-ubiquitin molecules with different dynamical properties. This flexibility is further increased by the possibility to tune the length of poly-ubiquitin chains. Characterizing the dynamics of poly-ubiquitins as a function of their length is thus relevant to understand their biology. Structural characterization of poly-ubiquitin conformational dynamics is challenging both experimentally and computationally due to increasing system size and conformational variability. Here, by developing highly efficient and accurate small-angle X-ray scattering driven Martini coarse-grain simulations, we characterize the dynamics of linear M1-linked di-, tri- and tetra-ubiquitin chains. Our data show that the behavior of the di-ubiquitin subunits is independent of the presence of additional ubiquitin modules. We propose that the conformational space sampled by linear poly-ubiquitins, in general, may follow a simple self-avoiding polymer model. These results, combined with experimental data from small angle X-ray scattering, biophysical techniques and additional simulations show that binding of NEMO, a central regulator in the NF-κB pathway, to linear poly-ubiquitin obeys a 2:1 (NEMO:poly-ubiquitin) stoichiometry in solution, even in the context of four ubiquitin units. Eventually, we show how the conformational properties of long poly-ubiquitins may modulate the binding with their partners in a length-dependent manner.</p>
pLMMoRF: A web server that accurately predicts membrane-interacting molecular recognition features by employing a protein language model
<p>pLMMMoRF predictor scrips and MemMoRF prediction of the human proteome.</p>
The proteolytic cleavage of TLR8 Z-loop by furin protease - molecular recognition, reaction mechanism and role of water molecules DATASET_v2
<p>The dataset comprises:<br>i) AlphaFold-Multimer predictions for TLR8LRR-furin complex<br>ii) The optimised structures of QM cluster models for reactant (RE), intermediate1-3 (INT1-INT3), and product (PROD)<br>iii) The optimised structures of QM/MM model for RE, INT1-INT3, PROD<br>iv) Input structures used in MD simulations and parameterization files for non-standard residues for RE, INT1-INT3, PROD<br>v) PyMOL sessions from AQUA-DUCT calculations for RE, INT1-INT3, PROD</p>
FEater dataset: A molecular fragment dataset to benchmark the robustness of 3D flexible object recognition
<p>This dataset is associated with the work: Benchmarking the robustness of the correct identification of flexible 3D objects using common machine learning models</p> <pre><code># Original FEater-Single and FEater_Dual dataset. FEater_Single ├── TestSet_coord.h5 ├── TrainingSet_coord.h5 └── ValidationSet_coord.h5 FEater_Dual ├── TestSet_coord.h5 ├── TrainingSet_coord.h5 └── ValidationSet_coord.h5 # Non-redundant baseline dataset FEater_Baseline ├── TestSet_Dual.h5 ├── TestSet_Single.h5 ├── TrainingSet_Dual.h5 └── TrainingSet_Single.h5 # FEater-Single and FEater_Dual in different sample size FEater_Mini200 ├── Mini200_Dual.h5 └── Mini200_Single.h5 FEater_Mini400 ├── Mini400_Dual.h5 └── Mini400_Single.h5 FEater_Mini800 ├── Mini800_Dual.h5 └── Mini800_Single.h5</code></pre> <p>For further details of the usage, please visit the original GitHub repository: <a title="FEater_repo" href="https://github.com/miemiemmmm/FEater" target="_blank" rel="noopener">https://github.com/miemiemmmm/FEater</a></p>
Molecular Dynamics (MD) Simulation Data for Dynamics Underlie the Drug Recognition Mechanism by the Efflux Transporter EmrE
<p>MD simulations on the proton bound (PDB 8UWU), deprotonated on E14A (PDB 8UWU), TPP Bound (PDB 8UWU) on our NMR derived structures.</p> <p> </p> <p>MD simulations on the proton bound (7MH6) and deprotonated on E14A (7MH6) on X-ray structures. </p> <p> </p> <p>Total raw simulation data would be too large for uploading to repositories. To reduce size of file, starting structure and tpr files are uploaded. Final structure at 2.5 μs are also uploaded. </p>
Molecular dynamics trajectories of pYEEI:SH2 recognition, unbiased, at all-atom resolution.
<div> </div> <p>Set of 772 all-atom trajectories simulated from an unbound (apo) configuration of the human p56 -lck tyrosine kinase SH2 domain with its high-specificity phosphopeptide recognition substrate pYEEI (initial structure based on PDB:<a href="https://www.rcsb.org/structure/1LKK">1LKK</a> ). Approximately 24 trajectories spontaneously reach a bound state with ligand RMSD < 2 Â from the crystal. System building and run details are described in [1].</p> <p>A preliminary version of this dataset have been analyzed and discussed in [1] (approx 200 ns per trajectory were available and used in [1]). </p> <p>The trajectories provided here are extended to ~800 ns each, for a total of ~640 μs sampled time. The full dataset is analyzed in [2] with a SOM-based technique.</p> <div> <h2>Notes</h2> </div> <div> <ul> <li>These are all-atom simulations (with TIP3P water). Water molecules have been stripped off from these files (filtered).</li> <li>Not all trajectories have the same length. Some are cut short due to the distributed computing setup.</li> <li>Frame-to-frame interval is 1 ns.</li> </ul> </div> <h2>Acknowledgments</h2> <p>We thank the volunteers of the GPUGRID.net project for donating computing time.</p> <p> </p> <h2>References</h2> <p>[1] T. Giorgino, I. Buch, and G. De Fabritiis. <a href="https://pubs.acs.org/doi/10.1021/ct300003f">Visualizing the Induced Binding of SH2-Phosphopeptide</a>, J. Chem. Theory Comput. 2012, 8, 4, 1171-1175. doi:10.1021/ct300003f</p> <p>[2] Lara Callea, Camilla Caprai, Laura Bonati, Toni Giorgino, Stefano Motta. Self-Organizing Maps of Unbiased Ligand-Target Binding Pathways and Kinetics. J. Chem. Phys, 2024. https://doi.org/10.1063/5.0225183 </p> <p> </p> <div> </div> <div> <p> </p> </div>
Data from: Molecular phylogenetics of Distephanus supports the recognition of a new tribe, Distephaneae (Asteraceae)
<p>The genus <em>Distephanus</em> Cass. comprises 43 distinctive species of shrubs and small trees that have been placed historically within the ironweed tribe, Vernonieae (Asteraceae). Utilizing the most expansive sampling of <em>Distephanus </em>to date, this study aims to test the monophyly of this genus and facilitate its classification. Molecular phylogenetic analyses were conducted using four molecular markers from the nuclear and plastid genomes. These data also supported divergence dating analyses that were performed to understand the timing of diversification events within <em>Distephanus</em> and other related genera. Results from this study indicate that as currently circumscribed, Vernonieae is not monophyletic and that <em>Distephanus </em>is actually sister to a clade that comprises Vernonieae and another tribe, Moquinieae, which only includes two species restricted to Brazil. Based on these findings, <em>Distephanus </em>is recognized in a new tribe that we describe here, Distephaneae. This new tribe comprises 41 species of <em>Disptehanus</em> that are easily distinguished from Moquinieae and Vernonieae based on the presence of florets with yellow corollas and trinervate leaves.</p>
Molecular basis for the increased affinity of an RNA recognition motif with re-engineered specificity: A molecular dynamics and enhanced sampling simulations study.
<p>This repository contains the representative structures of the 20 clusters obtained, which constitute the “MD-adapted structure ensemble”: i.e., sets of atomic coordinates that capture the flexibility and the pre-miR20b (<a href="https://zenodo.org/api/files/ee12021f-4398-465a-9ff6-ddb7be32765f/ensemble_MD_2n7x.pdb?versionId=310a80f6-aa64-445d-8641-45faf9f1ac03">ensemble_MD_2n7x.pdb</a>) and Rbfox/pre-miR20b (<a href="https://zenodo.org/api/files/ee12021f-4398-465a-9ff6-ddb7be32765f/ensemble_MD_2n82.pdb?versionId=82d7afcb-8a92-4daa-8150-789dbd7b2474">ensemble_MD_2n82.pdb</a>) conformers suggested by MD simulations while still retaining the highest possible level of agreement with the primary NMR data.</p>
Molecular basis for the increased affinity of an RNA recognition motif with re-engineered specificity: A molecular dynamics and enhanced sampling simulations study.-PART 8
<p>Simulations of the miR20b RNA with the Case vdW modification to amber force field and OPC water molecules.</p>
Fig. 1. – 50 in Enlarging the monotypic Monocarpieae (Annonaceae, Malmeoideae): recognition of a second genus from Vietnam informed by morphology and molecular phylogenetics
Fig. 1. – 50% majority-rule consensus phylogram derived from Bayesian inference of combined seven plastid DNA regions. Bayesian posterior probabilities (PP) indicated on the right; maximum likelihood bootstrap (BS) percentages in the middle; parsimony symmetric resampling (SR) percentages on the left [** denotes BS/SR <50%]. DEN. = Dendrokingstonieae; MAL. = Malmeeae; MIL. = Miliuseae; MON. = Monocarpieae; PIP. = Piptostigmateae. Scale bar unit = substitutions per site.
Supervised Molecular Dynamics Movies from: Deciphering the molecular recognition mechanism of multidrug resistance Staphylococcus aureus NorA efflux pump using a Supervised Molecular Dynamics approach
<p>Molecular Recognition pathway of Supervised molecular dynamic simulations of MdfA-CLM NorA-CPX and NorA-CPX.</p>
Deciphering the molecular recognition mechanism of multidrug resistance Staphylococcus aureus NorA efflux pump using a Supervised Molecular Dynamics approach.
<p><strong>Legend of Movie-S1</strong></p> <p>The Movie is composed by four synchronized and animated panels that show different aspects of the SuMD simulation. The time evolution is reported in nanosecond. In the first panel (upper left), the molecular representation of the system is shown. The MdfA backbone is represented by the new cartoon style (cyan). The CLM is shown in yellow and by a transparent surface. The protein residues within 3 Å from the ligand are made explicit by a stick representation.</p> <p>In the second panel (upper-right), the CM-distance between the protein and the ligand centers of mass is reported.</p> <p>In the third panel (lower left), the MMGBSA energy profile is reported.</p> <p>In the fourth panel (lower-right) cumulative electrostatic interactions are reported for the 15 MdfA residues most contacted by CLM during the whole simulation.</p> <p> </p> <p><strong>Legend of Video-S2</strong></p> <p>The Movie shows the SuMD trajectory of CLM on MdfA compared to the CLM crystallographic pose. MdfA is represented in cyan new cartoon transparency. The crystallographic pose is showed in yellow while the experimental one in light green. At 16.69 ns a RMSD value of 1.77 Å is highlighted.</p> <p> </p> <p><strong>Legend of Video-S3</strong></p> <p>The Movie is composed by four synchronized and animated panels that show different aspects of the SuMD simulation. The time evolution is reported in nanosecond. In the first panel (upper left), the system is shown. The NorA backbone is represented by the new cartoon style (red) and the protein residues within 3 Å of CPX are showed in stick. CPX is rendered by a green stick.</p> <p>In the second panel (upper-right), the distance between the centre of mass of the ligand and the protein during the trajectory is reported.</p> <p>In the third panel (lower left), the MMGBSA energy profile is reported. In the fourth panel (lower-right) cumulative electrostatic interactions are reported for the 15 NorA residues most contacted by CPX during the whole SuMD trajectory.</p> <p>It is important to note that the following video has a duration that is half of the simulation of SuMD. However, this straid does not alter the description of the trajectory performed by the ligand.</p> <p> </p> <p><strong>Legend of Video-S4</strong></p> <p>The Movie depicts the clustering analysis of CPX during the whole SuMD simulation. The NorA protein is shown in red new cartoon transparency. CPX is rendered by a light-green stick and by a transparent surface. The spheres are shown in 7 different colours, according to the different clusters. Each sphere dimension is in according to the cluster dimensions. After a first recognition site, the ligand conformations are clustered in different sites of the NorA channel. It is important to note that the following video has a duration that is half of the simulation of SuMD. However, this straid does not alter the description of the trajectory performed by the ligand.</p>
Supplementary data for the manuscript: Image2SMILES: Transformer-based Molecular Optical Recognition Engine
<p>This is the supplementary data for the manuscript: <a href="https://chemrxiv.org/engage/chemrxiv/article-details/60c758c6469df4169bf45744">Image2SMILES: Transformer-based Molecular Optical Recognition Engine</a></p> <p>It contains pairs of image-string, generated from 1M SMILES strings. These strings were randomly chosen from PubChem database.<br> It was prepared using the code, published at <a href="https://github.com/syntelly/img2smiles_generator/">https://github.com/syntelly/img2smiles_generator/</a></p> <p>To unpack do:<br> <em>tar xvf subset_1M.tar.xz && tar xvf subset_1M_dump.tar.gz && rm subset_1M_dump.tar.gz</em></p> <p>You'll get the following data:</p> <ul> <li>subset_1M.smi - list of 1M source SMILES</li> <li>subset_1M_dump - directory with images </li> <li>subset_1M_result.csv - list of pairs FGSMILES - pathcode, first 3 chars of pathcode are corresponding subdirs in subset_1M_dump</li> <li>subset_1M_fails.csv - list of failed molecules from subset_1M.smi</li> <li>subset_1M_grpcounter.lst - list of counted groups, used in this generation</li> </ul> <p>You can generate your own data using <a href="https://github.com/syntelly/img2smiles_generator/">https://github.com/syntelly/img2smiles_generator/</a> </p>
Structural determinants of ligands recognition by the human mitochondrial basic amino acids transporter SLC25A29. Insights from molecular dynamics simulations of the c-state.
<p>Initial coordinates, molecular dynamics trajectories and representative snapshots resulting from the study "Structural determinants of ligands recognition by the human mitochondrial basic amino acids transporter SLC25A29. Insights from molecular dynamics simulations of the c-state." by Pasquadibisceglie and Polticelli.</p> <p>The MD folders contain the parameter/topology (parm7) and initial coordinates (rst7) for the molecular dynamics simulations. Moreover, a NetCDF trajectory "prod.nc" of the production phase is also included.<br> In detail:<br> - MD0 -> SLC25A29 in absence of ligands;<br> - MD1, MD3, MD4 -> SLC25A29-ARG complex;<br> - MD1-LYS, MD3-LYS, MD4-LYS -> SLC25A29-LYS complex.</p> <p>The folder PDB_figures contains the PDB files used to produce the figures presented in the manuscript.</p>
Data from: Molecular phylogenetics of Distephanus supports the recognition of a new tribe, Distephaneae (Asteraceae)
Open the record for dataset details and reuse information.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.