Protein arginine methyltransferases (PRMTs) catalyze arginine methylation, a key post-translational modification (PTM) regulating chromatin organization, RNA metabolism, and signaling. Recent studies reveal that PRMT-mediated methylation also modulates liquid-liquid phase separation (LLPS), which organizes membraneless condensates controlling transcription, stress response, and genome stability. Dysregulated PRMT activity disrupts condensate dynamics, contributing to cancer and neurodegenerative diseases. In cancer, PRMT1, PRMT5, and PRMT6 promote tumor progression via methylation-dependent condensates that enhance oncogenic transcription and stress resistance. In the nervous system, PRMT1, PRMT4, PRMT5, PRMT6, and PRMT8 regulate LLPS of proteins, linking aberrant methylation to ALS and Huntington’s disease. This review highlights PRMTs as key modulators of phase separation and potential therapeutic targets in both oncology and neurodegeneration.
In the quantitative characterization of experimental systems the observation of a time-independent response can signify the attainment of thermodynamic equilibrium. However, there are also situations where the time-independence of experimental response merely reflects the attainment of a kinetic steady state. Although quantitative expressions derived on the basis of kinetic steady-state attainment retain validity for a system at thermodynamic equilibrium, those based on attainment of thermodynamic equilibrium do not apply to systems merely reflecting the attainment of a kinetic steady state. This survey of experimental procedures encountered during research endeavours over the past six decades has revealed many situations where the source of the time-independent instrumental response was correctly identified, but also a number where the responses were misinterpreted.
The article presents a study on the disruption of the bacterial membrane by celandine (CME) and dandelion (TOE) extracts containing bioactive compounds responsible for their antibacterial activity. The in vitro microbiological tests showed antibacterial effect both on Gram-positive (Staphylococcus aureus and Streptococcus pyogenes) and Gram-negative (Escherichia coli and Pseudomonas aeruginosa) pathogenic bacteria species. However, in the case of celandine herb extract, the effect was stronger, especially for Gram-positive bacteria. For a deeper understanding of the mechanism of antibacterial action, both studied extracts were subjected to biophysical studies on artificial bacterial lipid membranes, modeled with the Langmuir monolayers technique. The monolayer investigations were performed using two approaches: (i) monitoring the penetration of extracts injected into the aqueous subphase beneath a compressed lipid film, and (ii) comparing surface pressure-area isotherms recorded on a subphase with and without addition of extracts. These experiments confirmed the activity of TOE and CME at the membrane level, demonstrating the penetration of extract components into the membranes and their fluidizing effect. AFM analysis of the domain structures of the films transferred onto solid supports (Langmuir-Blodgett) revealed differences in film topography induced by the extracts and are in a good agreement with the results of biological tests and analytical analyses of the tested extracts. These findings confirm that the stronger antibacterial effect of CME, associated with a higher content of bioactive compounds, exerts a more destructive effect on the bacterial lipid membranes compared to TOE.
Advances in artificial intelligence, particularly in deep learning, are transforming the field of protein structure prediction. AlphaFold has emerged as a benchmark tool due to its remarkable ability to model protein folding based solely on amino acid sequences. Nevertheless, despite these impressive achievements, several prediction failures still occur. In this study, we focus on two multidomain proteins, LicT from Bacillus subtilis and P1 from the Rice Yellow Mottle Virus, that have long resisted structural characterization. Both proteins exhibit inter-domain flexibility, dimerization, and dynamic behavior in response to phosphorylation (for LicT) or zinc binding (for P1). Here, we screen the performances of AlphaFold versions against these two proteins endowed with a complex conformational landscape and show the present impossibility to correctly predict all domains simultaneously.
