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.
641
datasets available to search
ShareScore release 0.9.0
Dataset results
641 results for “Protein interaction”
Data from: Cooperative interactions between different classes of disordered proteins play a functional role in the nuclear pore complex of Baker's yeast
Open the record for dataset details and reuse information.
Data from: Proteomic analysis of barley mapping population subjected to drought identifies proteins with genotype×environment interaction and pQTLs
Open the record for dataset details and reuse information.
A human IgSF cell-surface interactome reveals a complex network of protein-protein interactions
Open the record for dataset details and reuse information.
Interaction of the maturation protein of the bacteriophage MS2 and the F pilus of Escherichia coli
<p>Five 20 ns independent trajectories of a model of the F pilus comprising a trimer of subunits binding to the maturation protein.</p>
TS Ensemble for "Evolution of an interaction between disordered proteins resulted in increased heterogeneity of the binding transition state"
<p>These are the input files for a phi-value restrained molecular dynamics associated with this paper "Evolution of an interaction between disordered proteins resulted in increased heterogeneity of the binding transition state"</p> <p> </p>
Dataset accompanying "SECAT: Quantifying differential protein-protein interaction states by network-centric analysis"
<p>This repository contains input data, processing parameters and results associated with manuscript "SECAT: Quantifying differential protein-protein interaction states by network-centric analysis".</p> <p>Each archive contains a README.txt file that describes the contents.</p> <p>SECAT_scripts_data.tar.xz is an archive containing the scripts and data to generate the manuscript figures.</p>
Data from: Sequence specificity despite intrinsic disorder: how a disease-associated Val/Met polymorphism rearranges tertiary interactions in a long disordered protein
The role of electrostatic interactions and mutations that change charge states in intrinsically disordered proteins (IDPs) is well-established, but many disease-associated mutations in IDPs are charge-neutral. The Val66Met single nucleotide polymorphism (SNP) in precursor brain-derived neurotrophic factor (BDNF) is one of the earliest SNPs to be associated with neuropsychiatric disorders, and the underlying molecular mechanism is unknown. Here we report on over 250 μ s of fully-atomistic, explicit solvent, temperature replica exchange molecular dynamics (MD) simulations of the 91 residue BDNF prodomain, for both the V66 and M66 sequence. The simulations were able to correctly reproduce the location of both local and non-local secondary changes due to the Val66Met mutation when compared with NMR spectroscopy. We find that the change in local structure is mediated via entropic and sequence specific effects. We developed a hierarchical sequence-based framework for analysis and conceptualization, which first identifies "blobs" of 5-15 residues representing local globular regions or linkers. We use this framework within a novel test for enrichment of higher-order (tertiary) structure in disordered proteins; the size and shape of each blob is extracted from MD simulation of the real protein (RP), and used to parameterize a self-avoiding heterogenous polymer (SAHP). The SAHP version of the BDNF prodomain suggested a protein segmented into three regions, with a central long, highly disordered polyampholyte linker separating two globular regions. This effective segmentation was also observed in full simulations of the RP, but the Val66Met substitution significantly increased interactions across the linker, as well as the number of participating residues. The Val66Met substitution replaces β -bridging between Val66 and Val94 (on either side of the linker) with specific side-chain interactions between Met66 and Met95.The protein backbone in the vicinity of Met95 is then free to form β -bridges with residues 31-41 near the N-terminus, which condenses the protein. A significant role for Met/Met interactions is consistent with previously-observed non-local effects of the Val66Met SNP, as well as established interactions between the Met66 sequence and a Met-rich receptor that initiates neuronal growth cone retraction.
Data from: Robust and accurate prediction of residue-residue interactions across protein interfaces using evolutionary information
Do the amino acid sequence identities of residues that make contact across protein interfaces covary during evolution? If so, such covariance could be used to predict contacts across interfaces and assemble models of biological complexes. We find that residue pairs identified using a pseudo-likelihood based method to covary across protein-protein interfaces in the 50S ribosomal unit and 28 additional bacterial protein complexes with known structure are almost always in contact in the complex provided that the number of aligned sequences is greater than the average of the lengths of the two proteins. We use this method to make subunit contact predictions for an additional 36 protein complexes with unknown structures, and present models based on these predictions for the tripartite ATP-independent periplasmic (TRAP) transporter, the tripartite efflux system, the pyruvate formate lyase-activating enzyme complex, and the methionine ABC transporter.
Data from: Global pairwise RNA interaction landscapes reveal core features of protein recognition
RNA–protein interactions permeate biology. Transcription, translation, and splicing all hinge on the recognition of structured RNA elements by RNA-binding proteins. Models of RNA–protein interactions are generally limited to short linear motifs and structures because of the vast sequence sampling required to access longer elements. Here, we develop an integrated approach that calculates global pairwise interaction scores from in vitro selection and high-throughput sequencing. We examine four RNA-binding proteins of phage, viral, and human origin. Our approach reveals regulatory motifs, discriminates between regulated and non-regulated RNAs within their native genomic context, and correctly predicts the consequence of mutational events on binding activity. We design binding elements that improve binding activity in cells and infer mutational pathways that reveal permissive versus disruptive evolutionary trajectories between regulated motifs. These coupling landscapes are broadly applicable for the discovery and characterization of protein–RNA recognition at single nucleotide resolution.
SpatPPI: a geometric deep learning model for predicting protein-protein interactions involving intrinsically disordered regions
Open the record for dataset details and reuse information.
Common protein interactions explain variant oncofusion function and predict a novel oncofusion in rhabdomyosarcoma
<p>Original Westerns from publications</p>
Inferred stacking interactions for a dataset of proteins, nucleic acids and ligands
Open the record for dataset details and reuse information.
MechRNA: prediction of lncRNA mechanisms from RNA-RNA and RNA-protein interactions
<p>Supplementary Data</p>
FACS data for "The genetic architecture of protein interaction affinity and specificity"
Open the record for dataset details and reuse information.
African swine fever virus E120R protein inhibits interferon-β production by interacting with IRF3 to block its activation
<p><span><span>African swine fever is a devastating disease of swine caused by African swine fever virus (ASFV). The pathogenesis of the disease remains largely unknown, leaving the uncontrolled spreading of the disease in many countries and regions. Here, we identified the E120R, a structural protein of ASFV, as a key virulent factor and late phase expression protein of the virus. E120R revealed an activity to suppress host antiviral response through blocking IFN-β production, and the 72-73 amino acid sites in the C-terminal domain were essential for this function. E120R interacted with the interferon regulatory factor 3 (IRF3) and interfered with the recruitment of IRF3 to TBK1, which in turn suppressed IRF3 phosphorylation, decreasing interferon production. The recombinant mutant ASFV was further constructed to confirm the claimed mechanism. The ASFV lacking the complete E120R region could not be rescued, whereas the virus could tolerate the deletion of the 72nd and 73rd residuals in the E120R (ASFV E120R-Δ72-73aa). ASFV E120R with the two amino acids deletion failed to interact with IRF3 during ASFV E120R-Δ72-73aa infection, and the viral infection highly activated IRF3 phosphorylation and induced more robust type I interferon production in comparison with its parental ASFV. An unbiased transcriptome-wide analysis of gene expression also confirmed that a considerably higher level of ISGs was detected in ASFV E120R-Δ72-73aa-infected porcine alveolar macrophages (PAMs) than that in the wildtype ASFV-infected PAMs. Together, our findings found a novel mechanism evolved by ASFV to inhibit host antiviral response and provide a new target for guiding the development of ASFV live-attenuated vaccine.</span></span></p>
PDBscreen with multiple data augmentation strategies suitable for training protein-ligand interaction prediction methods
<p>PDBscreen with multiple data augmentation strategies suitable for training protein-ligand interaction prediction methods.</p> <p>PDBscreen is the training dataset for EquiScore.</p>
Supporting data for protein membrane simulations in "Recalibration of protein interactions in Martini 3"
<p>Coarse-grained molecular dynamics simulations of protein-membrane systems from "Recalibration of protein interactions in Martini 3". Simulations were run with the Martini 3.0 force field, along with two modified versions of Martini 3.0 in which the well-depth, ε, in the Lennard-Jones potential between all protein and water beads was rescaled by a factor <em>λ</em><sub>PW</sub>, ε in the Lennard-Jones potential between all protein beads was rescaled by a factor <em>λ</em><sub>PP</sub>. The simulation files are organized into one tar file for each rescaling approach. The simulation files are in xtc format, and are accompanied by a structure in gro format for system topology and a tpr file to start the simulation.</p>
Fig. 4 in Detection of candidate proteins in the indican biosynthetic pathway of Persicaria tinctoria (Polygonum tinctorium) using protein-protein interactions and transcriptome analyses
Fig. 4. Scheme of the hypothesized indican biosynthetic pathway.
GcForest-based Compound-Protein Interaction Prediction Model and Its Application in Discovering Small-Molecule Drugs Targeting CD47
<p><strong>This is a file of all raw data and processed data concerned in the article "GcForest-based Compound-Protein Interaction Prediction Model and Its Application in Discovering Small-Molecule Drugs Targeting CD47", this file contain 6 sub-files, namely GCVec——humans, GCVec——celegans, GCVec——challenging dataset, GCVec——latest BindingDB, GCVec——known CD47 inhibitors, GCVec——specs, respectively, fully cover all parts of the article.</strong></p>
Splitpea: quantifying protein interaction network rewiring changes due to alternative splicing in cancer
<p>This serves as the supplementary data repo for the paper, <em><a href="https://doi.org/10.1101/2023.09.04.556262">Splitpea: quantifying protein interaction network rewiring changes due to alternative splicing in cancer</a>. </em></p> <p>The file structure is as follows:</p> <ul> <li>Splitpea rewired PPI networks for individual patient samples (files ending in `patient-rewired-networks.zip`). The networks are stored as dat files, which are tab delimited with one row per edge. Gene ids are reported as entrez id, the edge weights determine the directionality of the interaction (positive weights are potential gains, negative weights are edges likely lost). Chaos edges can have a positive or negative weight but will be indicated by a boolean value in the `chaos` column.</li> <li>The consensus networks (files ending in `consensus_networks`) are separated into two networks one for positive edges and one for negative edges present in at least 80% of tumor samples. These files are tab delimited files with one row per edge in the corresponding undirected weighted network. The following columns are included: <ul> <li>node1, node2: genes incident on the edge as entrez gene IDs</li> <li>mean_weight: average weight of edge across networks (where edge is present) used to build the consensus</li> <li>total_weight: sum of weights across networks (where edge is present) used to build the consensus</li> <li>num_graphs: # of networks where edge was present</li> <li>prop_graphs: # of networks where edge was present / total # of networks used to build the consensus</li> </ul> </li> <li>IRIS.zip: Splicing matrix spliced exon files from IRIS (Pan et al. <a href="https://doi.org/10.1073/pnas.2221116120">https://doi.org/10.1073/pnas.2221116120</a>). These are the initial inputs for the Splitpea run described in the paper.</li> <li>BRCA-psi.zip: precalculated PSI values for breast cancer samples as described in the paper</li> <li>PAAD-psi.zip: precalculated PSI values for pancreatic cancer samples as described in the paper</li> <li>*-centralities.zip: precalculated centralities for each patient network</li> <li>*-pickle.zip: network representations as pickle files</li> </ul>
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.