Biology subjects

Mas, P.

Publications and source records attributed to Mas, P..

3 recordsLinked to original sources

bioRxiv2026

Affinity-enhanced peptides delivered by mRNA lipid nanoparticles inhibit influenza A virus replication by disrupting PA-PB1 interaction

Seasonal influenza causes up to 650,000 deaths annually and remains a persistent pandemic threat due to zoonotic strains crossing the species barrier. Current antivirals, which target neuraminidase or the viral polymerase, have limited efficacy and rapidly select for resistant variants, highlighting the urgent need for new therapeutic strategies. The heterotrimeric influenza polymerase (FluPol), comprising PA, PB1, and PB2 subunits, is essential for viral replication and harbors virus-specific protein-protein interfaces that are potential drug targets. We focused on the highly conserved PA-PB1 interface, where the N-terminal peptide of PB1 binds the PA C-terminal domain with high affinity. Disrupting this interaction abrogates polymerase function, halting viral replication. Using phage display, we identified PB1-derived peptides with enhanced affinity for PA and characterized their binding via biophysical methods and X-ray crystallography. Lead peptides efficiently disrupted the PB1-PA interaction and inhibited polymerase activity in cell-based assays. To address peptide delivery challenges, we expressed these inhibitors intracellularly from synthetic mRNA formulated in lipid nanoparticles, achieving robust inhibition of viral replication in cultured cells. This work establishes intracellularly expressed peptide inhibitors as a viable antiviral strategy and provides a generalizable framework for targeting essential protein-protein interactions of influenza and other RNA viruses.

microbiology↗

bioRxiv2023

Deep Batch Active Learning for Drug Discovery

A key challenge in drug discovery is to optimize, in silico, various absorption and affinity properties of small molecules. One strategy that was proposed for such optimization process is active learning. In active learning molecules are selected for testing based on their likelihood of improving model performance. To enable the use of active learning with advanced neural network models we developed two novel active learning batch selection methods. These methods were tested on several public datasets for different optimization goals and with different sizes. We have also curated new affinity datasets that provide chronological information on state-of-the-art experimental strategy. As we show, for all datasets the new active learning methods greatly improved on existing and current batch selection methods leading to significant potential saving in the number of experiments needed to reach the same model performance. Our methods are general and can be used with any package including the popular DeepChem library.

bioinformatics↗

bioRxiv2019

A mobile ELF4 delivers circadian temperature information from shoots to roots

The circadian clock is synchronized by environmental cues, mostly by light and temperature. Elucidating how the plant circadian clock responds to temperature oscillations is crucial to understand plant responsiveness to the environment. Here we found a prevalent temperature-dependent function of the Arabidopsis clock component ELF4 (EARLY FLOWERING 4) in the root clock. Micrografting assays and mathematical analyses show that ELF4 moves from shoots to regulate rhythms in roots. ELF4 movement does not convey photoperiodic information but trafficking is essential to control the period of the root clock in a temperature-dependent manner. At low temperatures, ELF4 mobility is favored and results in a slow-paced root clock while high temperatures decrease movement, leading to a fast clock. Hence, the mobile ELF4 delivers temperature information and establishes a shoot-to-root dialogue that sets the pace of the clock in roots.

plant biology↗