#ProteinInteraction
Lots of influx & new followers, so time for a short introduction. I put molecules together and make them wiggle, although I would like them not to. #structuralbiology #bioinformatics #capri #proteininteraction #evolution. May also post about my travels, board games, and various other topics.
November 17, 2024 at 2:22 PM
Next Up in the #LongTREC Series 📽️ : Yalan Bi!
Yalan is a LongTREC Doctoral Candidate working with Ralf Herwig at @molgen.mpg.de Yalan shares insights into her research project and her experience as part of the LongTREC network. #LongReadsTranscriptomics #AlternativeSplicing #ProteinInteraction
July 12, 2025 at 2:21 PM
🔗 RNA-protein interaction prediction without high-throughput data: An overview and benchmark of in silico tools. Computational and Structural Biotechnology Journal, DOI: doi.org/10.1016/j.cs...

📚 CSBJ: www.csbj.org

#RNA #ProteinInteraction #Genomics #Proteomics #Bioinformatics
November 16, 2025 at 6:54 PM
🧠 "NetREm: Network Regression Embeddings reveal cell-type transcription factor coordination for gene regulation" introduces a novel computational method uncovering TF-TF coordination from single-cell data using prior #proteininteraction networks. doi.org/10.1093/bioa... #GeneRegulation
January 15, 2025 at 2:46 PM
PhoXplex: Combining Phospho-enrichable Cross-Linking with Isobaric Labeling for Quantitative Proteome-Wide Mapping of Protein Interfaces

#proteomics #massspec #tmt #xl-ms #proteininteraction

pubs.acs.org/doi/10.1021/...
PhoXplex: Combining Phospho-enrichable Cross-Linking with Isobaric Labeling for Quantitative Proteome-Wide Mapping of Protein Interfaces
Integrating cross-linking mass spectrometry (XL-MS) into structural biology workflows provides valuable information about the spatial arrangement of amino acid stretches, which can guide elucidation of protein assembly architecture. Additionally, the combination of XL-MS with peptide quantitation techniques is a powerful approach to delineate protein interface dynamics across diverse conditions. While XL-MS is increasingly effective with isolated proteins or small complexes, its application to whole-cell samples poses technical challenges related to analysis depth and throughput. The use of enrichable cross-linkers has greatly improved the detectability of protein interfaces in a proteome-wide scale, facilitating global protein–protein interaction mapping. Therefore, bringing together enrichable cross-linking and multiplexed peptide quantification is an appealing approach to enable comparative characterization of structural attributes of proteins and protein interactions. Here, we combined phospho-enrichable cross-linking with TMT labeling to develop a streamline workflow (PhoXplex) for the detection of differential structural features across a panel of cell lines in a global scale. We achieved deep coverage with quantification of over 9000 cross-links and long loop-links in total including potentially novel interactions. Overlaying AlphaFold predictions and disorder protein annotations enables exploration of the quantitative cross-linking data set, to reveal possible associations between mutations and protein structures. Lastly, we discuss current shortcomings and perspectives for deep whole-cell profiling of protein interfaces at large-scale.
pubs.acs.org
November 25, 2024 at 5:04 PM
🧵(2/2) By integrating 12 state-of-the-art predictors, it delivers robust meta-predictions and interactive visualization from both protein sequences and structures.
🌐 Try PROBind: www.csuligroup.com/PROBind 📖 Read the paper in academic.oup.com/gpb/advance-... #Genomics #ProteinInteraction
PROBind: A Web Server for Prediction, Analysis, and Visualization of Protein-Protein and Protein-Nucleic Acid Binding Residues
Abstract. Protein–protein and protein–nucleic acid interactions are fundamental to numerous cellular functions, yet only a small fraction have been experim
academic.oup.com
July 18, 2026 at 8:15 AM
Pair-EGRET: enhancing the prediction of protein-proteininteraction sites through graph attention networks and protein language models https://www.biorxiv.org/content/10.1101/2023.12.25.572648v1
Pair-EGRET: enhancing the prediction of protein-proteininteraction sites through graph attention networks and protein language models https://www.biorxiv.org/content/10.1101/2023.12.25.572648v1
Proteins are responsible for most biological functions, many of which require the interaction of mor
www.biorxiv.org
December 27, 2023 at 7:51 AM
Pair-EGRET: enhancing the prediction of protein-proteininteraction sites through graph attention networks and protein language models https://www.biorxiv.org/content/10.1101/2023.12.25.572648v1
Pair-EGRET: enhancing the prediction of protein-proteininteraction sites through graph attention networks and protein language models https://www.biorxiv.org/content/10.1101/2023.12.25.572648v1
Proteins are responsible for most biological functions, many of which require the interaction of mor
www.biorxiv.org
December 27, 2023 at 7:51 AM