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29 results for “kinome”
KiSSim: Predicting off-targets from structural similarities in the kinome
<p><strong>KiSSim: Predicting off-targets from structural similarities in the kinome</strong></p> <p><strong>Project description.</strong></p> <p>KiSSim (Kinase Structural Similarity) is a novel fingerprint designed specifically for kinase pockets, allowing for similarity studies across the structurally covered kinome. The kinase fingerprint is based on the <a href="https://klifs.net/">KLIFS</a> pocket alignment, which defines 85 pocket residues for all kinase structures. This enables a residue-by-residue comparison without a computationally expensive alignment step.</p> <p>The pocket fingerprint encodes each pocket residue’s spatial and physicochemical properties. The spatial properties describe the residue’s position in relation to the kinase pocket center and important kinase subpockets, i.e. the hinge region, the DFG region, and the front pocket. The physicochemical properties encompass for each residue its size and pharmacophoric features, solvent exposure, and side chain orientation.</p> <p>Some datasets are not part of the `kissim_app` GitHub repository due to their size but can be downloaded from here to the respective kissim_app folders.</p> <p><strong>Data.</strong></p> <ul> <li>`20210902_KLIFS_HUMAN.tar.gz` --- save in `kissim_app/data/external/structures`</li> <li>`complete_SiteAlign.txt.gz` --- save in `kissim_app/data/external/sitealign`</li> </ul> <p><strong>Results.</strong></p> <ul> <li>`results.tar.bz2`--- save as `kissim_app/results`</li> </ul> <p>These are the KiSSim results: fingerprints, feature/fingerprint distances, kinase matrices, and kinase trees for structures in all (`all`), DFG-in (`dfg_in`), and DFG-out (`dfg_out`) conformation. In the case of the DFG-in conformation, we also have KiSSim runs with fingerprint subsets based on only residues that interact with certain ligands in KLIFS IFPs: Erlotinib (`dfg_in_IRE`), Imatinib (`dfg_in_STI`), Bosutinib (`dfg_in_DB8`), and Dopamapimod (`dfg_in_B96`). The folder contains README with a detailed file list.</p> <p><strong>Usage.</strong></p> <p>This dataset can be used to run the notebooks available on <a href="https://github.com/volkamerlab/kissim_app">https://github.com/volkamerlab/kissim_app</a>.</p> <ol> <li>Clone the kissim_app repository.</li> <li>Download the files provided here.</li> <li>If applicable, extract the archive content to the folders as indicated above and run the notebooks.</li> </ol> <pre><code class="language-bash">cd /path/to/your/download tar -xvf results.tar.bz2 -C /path/to/kissim_app/ tar -xvf 20210902_KLIFS_HUMAN.tar.bz2 -C /path/to/kissim_app/data/external/structures/ # In case you want the raw SiteAlign data mv complete_SiteAlign.txt.gz /path/to/kissim_app/data/external/sitealign</code></pre> <p><strong>Citation.</strong></p> <p>These datasets are part of the KiSSim publication: TBA</p>
Selectivity profiling of multi-kinase inhibitors across the Human Kinome from ChEMBL
<p>Reported is the list of 596 protein kinase pairs, consisting of 141 kinases and selectivity profiles of 10,060 multi-kinase inhibitors found in ChEMBL23 high-confidence data. For each of the reported protein kinase pairs, UniProt IDs defining the kinase forming a pair is provided, as well as the shared inhibitors and their selectivity profiles. For each target within the pair, potency value for each compound is reported as pIC50 value, as well as the absolute potency difference used to assess the selectivity profiles.</p>
The raw data from the article "KinomeMETA: meta-learning enhanced kinome-wide polypharmacology profiling"
<p>The raw data from the article "KinomeMETA: meta-learning enhanced kinome-wide polypharmacology profiling"</p>
Data from: The Arabidopsis kinome: phylogeny and evolutionary insights into functional diversification
Background: Protein kinases constitute a particularly large protein family in Arabidopsis with important functions in cellular signal transduction networks. At the same time Arabidopsis is a model plant with high frequencies of gene duplications. Here, we have conducted a systematic analysis of the Arabidopsis kinase complement, the kinome, with particular focus on gene duplication events. We matched Arabidopsis proteins to a Hidden-Markov Model of eukaryotic kinases and computed a phylogeny of 942 Arabidopsis protein kinase domains and mapped their origin by gene duplication. Results: The phylogeny showed two major clades of receptor kinases and soluble kinases, each of which was divided into functional subclades. Based on this phylogeny, association of yet uncharacterized kinases to families was possible which extended functional annotation of unknowns. Classification of gene duplications within these protein kinases revealed that representatives of cytosolic subfamilies showed a tendency to maintain segmentally duplicated genes, while some subfamilies of the receptor kinases were enriched for tandem duplicates. Although functional diversification is observed throughout most subfamilies, some instances of functional conservation among genes transposed from the same ancestor were observed. In general, a significant enrichment of essential genes was found among genes encoding for protein kinases. Conclusions: The inferred phylogeny allowed classification and annotation of yet uncharacterized kinases. The prediction and analysis of syntenic blocks and duplication events within gene families of interest can be used to link functional biology to insights from an evolutionary viewpoint. The approach undertaken here can be applied to any gene family in any organism with an annotated genome.
Data from: The Arabidopsis kinome: phylogeny and evolutionary insights into functional diversification
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Kinome reprogramming of G2/M kinases and repression of MYCN contribute to superior efficacy of lorlatinib in ALK-driven neuroblastoma
GEO Series GSE273349. Homo sapiens. 20 samples. Type: Expression profiling by high throughput sequencing.
Oxygen tension-dependent variability in the cancer cell kinome and response to combination therapies
GEO Series GSE244662. Homo sapiens. 4 samples. Type: Expression profiling by high throughput sequencing.
Human kinome CRISPR knockout screen in H358 parental and sotorasib resistant H358 cells
GEO Series GSE275314. Homo sapiens. 6 samples. Type: Other.
Pecan kinome: classification and expression analysis of all protein kinases in Carya illinoinensis
GEO Series GSE179336. Carya illinoinensis. 18 samples. Type: Expression profiling by high throughput sequencing.
A kinome-wide high-content siRNA screen identifies MEK5-ERK5 signaling as critical for breast cancer cell EMT and metastasis
GEO Series GSE100403. Mus musculus. 8 samples. Type: Expression profiling by high throughput sequencing.
Intrinsic Resistance to MEK Inhibition Through BET Protein Mediated Kinome
GEO Series GSE127886. Homo sapiens. 4 samples. Type: Expression profiling by high throughput sequencing.
shRNA cassette sequencing from disomic and trisomic fibroblasts cultured in the presence of shRNA kinome library for 14 days
GEO Series GSE79840. Homo sapiens. 33 samples. Type: Other.
Defining the Triple Negative Breast Cancer Kinome Response to GSK1120212 (RNA-Seq)
GEO Series GSE107502. Homo sapiens. 28 samples. Type: Expression profiling by high throughput sequencing.
shRNA kinome screen identifies TBK1 as therapeutic target for HER2+ breast cancer
GEO Series GSE53658. Homo sapiens. 6 samples. Type: Expression profiling by array.
Adaptation of the Kinome Promotes Resistance to BET Bromodomain Inhibitors in Ovarian Cancer
GEO Series GSE82329. Homo sapiens. 14 samples. Type: Expression profiling by high throughput sequencing.
Tumor-intrinsic kinome landscape of pancreatic cancer reveals new therapeutic approaches
GEO Series GSE278757. Homo sapiens. 243 samples. Type: Expression profiling by high throughput sequencing.
A kinome-wide CRISPR screen identifies CK1α as a novel target to overcome enzalutamide resistance of prostate cancer
GEO Series GSE203362. Homo sapiens. 14 samples. Type: Expression profiling by high throughput sequencing; Other.
Defining the Triple Negative Breast Cancer Kinome Response to GSK1120212
ClinicalTrials.gov study NCT01467310. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Defining the HER2 Positive (+) Breast Cancer Kinome Response to Trastuzumab, Pertuzumab, Combination Trastuzumab +Pertuzumab, or Combination Trastuzumab + Lapatinib
ClinicalTrials.gov study NCT01875666. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Synthetic lethal siRNA screen for TN-IBC cell line SUM149PT using kinome library with EPA treatment
GEO Series GSE102057. Homo sapiens. 6 samples. Type: Other.
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