Latest posts tagged with #Interactome on Bluesky
🔦 In our #Highlights2025 collection, you will find a fascinating article shedding light on the interacting partners of Tks5 in invadosomes.
📕 Tks5 interactome reveals endoplasmic-reticulum-associated translation machinery in invadosomes
➡️ buff.ly/YtIn8l2
#invadosome #interactome #ER
BioGRID Build 5.0.252 is released with data from 87,534 publications including 2,905,263interactions (2,253,933 unique), 31,540 chemical interactions and 563,757 unique PTMs 🧪 @biogrid.bsky.social
#interactome #datasharing #openscience #opendata #openaccess #NIH #ORIP
📣 Publication alert: Our paper, “A guide to building the matrisome interactome: from computational predictions to experimental validation” is now published in @febsj.bsky.social!
📄 The paper is available in #OpenAccess at: doi.org/10.1111/febs...
#ECM #Matrisome #Interactome #SystemsBiology
🧫 Explore the curated dataset in IntAct ➡️ tinyurl.com/candidalysin
🎨IntAct Cytoscape visualisation:
Candida albicans ECE1 peptides (orange) and their human protein targets (blue)
#IntActEBI #Interactome #EMBL
I have been using SAINT for #interactome/ #apms analysis forever but always found it cumbersome to pipe into workflows especially on macOS/unix env. But no mas! We made a full Python port of SAINTexpress (spc only for now)
github.com/FossatiLab/s...
BioGRID Build 5.0.251 is released with data from 87,393 publications including 2,901,447 interactions (2,251,953 unique), 31,540 chemical interactions and 563,757 unique PTMs 🧪
@biogrid.bsky.social
#interactome #datasharing #openscience #opendata #openaccess #NIH #ORIP
BioGRID Build 5.0.250 is released with data from 87,320 publications including 2,898,895 interactions (2,249,721 unique), 31,540 chemical interactions and 563,757 unique PTMs 🧪
@biogrid.bsky.social
#interactome #datasharing #openscience #opendata #openaccess #NIH #ORIP
Global genetic interaction map of human cell reveals conserved principles of genetic networks https://www.biorxiv.org/content/10.1101/2025.06.30.662193v1?rss=1 #interactome #MolecularGenetics #genetics #FunctionalGenetics
Global genetic interaction map of human cell reveals conserved principles of genetic networks
www.biorxiv.org/content/10.1...
#interactome #MolecularGenetics #genetics #FunctionalGenetics
Proteomics Analysis of the TDP‐43 Interactome in Cellular Models of ALS Pathogenesis - Cheng - 2025 - Journal of Neurochemistry - Wiley Online Library #mnd #als #tdp43 #interactome @mndaus-research.bsky.social
onlinelibrary.wiley.com/doi/10.1111/...
It is Gold Open Access paper, so everyone can check it out. It is quite extensive work so I want to thanks to Kostia for his great contributions.
doi.org/10.1039/D5CS...
#chemoproteomics #targetID #PPI #Interactome #chemicalpharmacology
BioGRID Build 4.4.244 is released with data from 86,536 publications including 2,840,984 interactions (2,203,605 unique), 31,144 chemical interactions and 563,757 unique PTMs 🧪 @biogrid.bsky.social
#interactome #datasharing #openscience #opendata #openaccess #NIH #ORIP
Figure 1. Combining different treatments and baits determines different components of the TORC interactome. A) Scheme illustrating PUP-IT in the context of TOR signaling. PafA fused to the baits LST8-1, RAPTOR1, and ScFKBP labels individual and TOR complex associated protein interactors, while a GFP fusion acts as a control for unspecific interactions. B–E) Volcano plots showing proteins significantly enriched in LST8-1 B,D) and RAPTOR1 C,E) baits using constitutive B,C) or inducible D,E) FLAG::PUP(E) expression. F–G) Treatment-dependency of identified interactors using LST8-1 G) or RAPTOR1 H) baits and inducible FLAG::PUP(E) expression. Treatment-specific interactors are those only identified in one of the two treatments. H) Rapamycin response of WT and ScFKBP-producing seedlings (n = 10 seedlings). Bar height indicates group median. I) Volcano plot showing proteins significantly enriched in the ScFKBP bait using constitutive FLAG::PUP(E) expression. In all volcano plots, fold changes are calculated from n = 3 replicates using MsqRob2, p-values are corrected for multiple comparisons using the Benjamini–Hochberg FDR method. Different letters in panel (H) indicate statistically significant differences between groups based on a one-way ANOVA followed by a Tukey-HSD test (𝛼 = 0.05).
Figure 2. Identification of phosphorylated direct interactors of the TOR complex and in silico corroboration using AlphaFold2. A,B) Phosphorylated proteins enriched in LST8-1 and RAPTOR1 against the GFP control after 4 h A) and 24 h B) of sucrose treatment and FLAG::PUP(E) induction. Phosphorylation sites previously associated with TOR are indicated in blue, new sites in proteins previously reported to be phosphorylated by TOR in turquoise. Fold changes are calculated from n = 3 replicates using MsqRob2, p-values are corrected for multiple comparisons using the Benjamini–Hochberg FDR method. C,D) The two significantly enriched motifs among the identified phosphorylation sites. The “SP” motif C) mirrors previous reports from TOR substrates, while the “RxxS” motif D) has previously been associated with TOR downstream interactor S6K1. E) Interactions of 20 proteins from the four shown groups with the TORC components TOR, LST8-1, and RAPTOR1 were predicted using AlphaFold2 multimer. Vertical lines indicate the median of the local interaction score (LIS) distribution by group. F) Predicted structures of the top-scoring interactions for each group: newly identified TORC interactor PANK2, TORC subunit RAPTOR1, senescence regulator S40-7, and KIN10 paralog KIN11. Models are colored by predicted local distance difference test (pLDDT), with values above 70 indicating high confidence predictions.
Great work by Zheng et al. (2025) on how employing pupylation-based proximity labeling (PUP-IT) unravels a comprehensive #interactome of #Arabidopsis TOR complex.
Newly identified #PlantTOR interactors, like PANK2, were also supported by #AlphaFold2.
advanced.onlinelibrary.wiley.com/doi/10.1002/...
#Genetic study sheds light on changes that shaped #human #brain #evolution
#regulation #Human_Accelerated_Regions #interactome #neurodevelopment
phys.org/news/2025-02...
BioGRID Build 4.4.241 is released with data from 86,032 publications including 2,826,897 interactions (2,194,102 unique), 31,144 chemical interactions and 563,757 unique PTMs 🧪 @biogrid.bsky.social
#interactome #datasharing #openscience #opendata #openaccess #NIH #ORIP
🍿Need a break from (re)watching a bazillion Christmas movies? Check out this #festiveFEBSJ #Editorschoice by:
Costacurta & team, who used proximity labelling to explore how IMiDs & proteasome inhibition affect cereblon’s #interactome in #multiplemyeloma
🔗 https://buff.ly/3VLpR1r
BioGRID Build 4.4.240 is released with data from 86,032 publications including 2,824,633 interactions (2,192,664 unique), 31,144 chemical interactions and 1,128,339 unique PTMs 🧪 @biogrid.bsky.social
#interactome #datasharing #openscience #opendata #openaccess #NIH #ORIP
Was great to contribute to this story together with
JanGerhartz Dominika Pienkowska Ina Dressel & Thomas Geiger from the lab. #CRBN #Interactome #GLUES
authors.elsevier.com/sd/article/S...
Animation credit PROXIDRUGs. Thanks for fantastic colaboration.
#MedSky🧪#IDSky #ImmunoSky Overview the host-🦠 interactions mediated by #viralRNA & the importance of vRNA in regulating protein function through riboregulation & Uncovering the vRNA #interactome
www.cell.com/molecular-ce...
Last talk of our #SpringSchool2023, organized by @Leibniz_DIfE, @LeibnizLSB and @igz_leibniz:
Pascal Falter-Braun from @HelmholtzMunich is closing the thematic circle of this week with his presentation on Cross-kingdom Principles in #Interactome Networks.
#omics #systemsbiology
