Fluorescence lifetime imaging microscopy can offer insights into biological processes such as metabolic imaging, protein–protein interactions and live-cell intracellular dynamics. In this Primer, Torr...

Schmid and Walter train a classifier that discerns functionally relevant structure predictions in proteome-wide protein-protein interaction (PPI) screens using AlphaFold-Multimer, and they use this co...

🚀 Shaping the future of mass spectrometry! The custom-built Orbitrap Astral Zoom RAPtor 🦖 has just landed in our lab — the only one in the world. This future-generation instrument has been created spe...

A review classifying the available methods to study protein–protein interactions based on the nature of the samples and the information-depth they deliver.

Gastroenterology and Hepatology from Bed to Bench (GHFBB) from a bibliometric perspective (2011-2021)

Background When genes are translated into proteins, mutations in the gene sequence can lead to changes in protein structure and function as well as in the interactions between proteins. These changes…

Many cellular processes are governed by protein–protein interactions. To better understand these processes, it is necessary to understand how different proteins interact under different conditio...

PPIs offer a system-level understanding of cell behavior

Background: Bladder cancer is a disease with complex perturbations in gene networks and heterogeneous in terms of histology, mutations, and prognosis. Advances in high-throughput sequencing technologies, genome-wide association studies, and bioinformatics methods have revealed greater insights into the pathogenesis of complex diseases. Network biology-based approaches have been used to demonstrate the complex physical or functional interactions between molecules which can lead to potential drug targets. Objective: There is a need to better understand gene networks and protein-protein interactions (PPI) specific to urothelial carcinoma. Methods: We performed a multi-sample PPI study comparing two urothelial carcinoma architectures: papillary and non-papillary. We used a novel PPI analysis tool, Proteinarium to identify clusters of patients with shared PPI networks in each architecture. The feature of this tool is to analyze the PPI networks of patients and visualize them in clusters based on their network similarities from any genomic data including Next Generation Sequencing (NGS). Results: We observed distinct networks for the papillary and non-papillary groups. Proteins unique to the papillary urothelial carcinoma detected in two separate datasets included UBA52, RPS27A, UBR4, CUL1, UBE2K, and CDC5L. Proteins found in the non-papillary urothelial carcinoma specific PPI network were GNB1, UBC, RHOA, FPR2, GNGT1, PIK3CA, PIK3CG, HSP90AA1, SLC11A1, CCT7, ARHGEF1, PAK1, PAK2, PSMA7, and TRIO. Conclusions: We identified distinct PPI networks specific to papillary and non-papillary urothelial carcinomas presenting unique molecular entities. Clinical Trial: N/A

Dear Colleagues, The journal Health and Metabolism (HM) will soon launch a topic issue titled “ High-Resolution Mapping of Dynamic Molecular Conversations: NMR Insights into Protein–Drug and Protein–M...

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