Biology subjects

Eberini, I.

Publications and source records attributed to Eberini, I..

3 recordsLinked to original sources

bioRxiv2026

Biophysical characterization of novel biomarkers and bioaffinity reagents (NanoMIPs): on the road for a low-cost diagnostic test for intestinal schistosomiasis

Schistosoma mansoni is a vector-borne intestinal parasite, endemic in [~]70 tropical countries. Most of the World Health Organization interventions are based on mass drug administration (MDA) and sanitation. Since the parasite does not induce permanent immunity, reinfection rate is high, inducing scheduling of several MDA campaigns. To follow up after treatment and avoid blind MDA, providing a new rapid and cheap diagnostic test is needed, since the most used method is fifty years-old, lacks sensitivity and efficiency. Venom Allergen-Like proteins (SmVALs) have been previously identified as secreted/excreted proteins and potential biomarkers. Here we present the biophysical characterization of SmVAL11 and SmVAL13, their recognition by both specific antibodies and molecularly imprinted polymers (nanoMIPs), an easy-to-standardize alternative. The specific antibodies showed no cross-reactivity, while initial characterization of the nanoMIPs indicates a promising level of selectivity, establishing them as a reliable, cost-effective alternative. Therefore, our results are promising for the future development of a new cheap diagnostic test of intestinal schistosomiasis.

biophysics↗

bioRxiv2026

ThermoFusion: A Multimodal Deep Learning Framework for Generalizable Prediction of Enzyme Thermostability

Protein thermostability is a critical property for both industrial and biomedical enzyme applications, yet experimental evaluation of mutation-induced stability changes remains laborious and costly. Here, we present ThermoFusion, a hybrid deep learning framework that integrates 3D protein structure embeddings from ThermoMPNN with sequence-based embeddings from the pretrained protein language model ESM2 to predict the effects of single-point mutations on protein stability ({Delta}{Delta}G). ThermoFusion exhibits robust generalization, maintaining high predictive accuracy across out of distribution sequences with low identity to the training set - a scenario where many other machine learning models, including ThermoMPNN and state-of-the-art tools, perform poorly due to reliance on memorization. Benchmarking on a curated enzyme dataset comprising of 105 enzymes and 3144 mutations shows that ThermoFusion reliably identifies stabilizing mutations while accurately predicting stability for enzymes beyond its training set. These results establish ThermoFusion as a powerful tool for rational enzyme design beyond its training set.

bioinformatics↗

bioRxiv2024

Identification of neuronatin as a SERCA2b regulin-like protein and assessment of its aggregation propensity via coarse grained simulations.

Neuronatin (NNAT) is small transmembrane protein involved in a wide range of physiological processes, such as white adipose tissue browning and neuronal plasticity, as well as pathological ones, such as Lafora disease caused by the formation of NNAT aggregates. However, its 3D structure is unknown, and its mechanism of action is still unclear. In this study the two most well-known NNAT isoforms ( and {beta}) were modelled and the interaction with the SERCA2b calcium pump was assessed using computational methods. First, molecular docking identified the same binding region as the one described for phospholamban, a thoroughly described SERCA inhibitor. Then, analyses of the flux of water molecules during molecular dynamics simulations highlighted significant similarities between the behavior of SERCA2b when in complex with phospholamban, and when in complex with either NNAT isoform. These results suggest that NNAT could be considered a "regulin-like" protein. Additional all-atom and coarse-grained simulations of multiple copies of NNAT highlighted a significant aggregation potential of both NNAT isoforms, supporting experimental data. Statement of significanceThis study presents the first structural model of neuronatin (NNAT) isoforms and {beta}. Through molecular docking and molecular dynamics simulations, we propose a NNAT interaction mechanism with the SERCA2b calcium pump similar to that of phospholamban, a known regulin and SERCA inhibitor. Our analyses also suggested a strong aggregation potential of NNAT based on all-atom and coarse-grained simulations, in line with experimental data on its involvement in Lafora disease. These insights suggest NNAT can be considered a "regulin-like" protein, advancing our understanding of its molecular function and contributing to new perspectives in targeting NNAT-related pathologies, as well as reinforcing the role of coarse-grained simulations as a valid tool to assess protein aggregation potential.

bioinformatics↗