Biology subjects

Fernandez-Martin, M.

Publications and source records attributed to Fernandez-Martin, M..

2 recordsLinked to original sources

bioRxiv2024

Sequence-based coevolutionary prediction of species-specific interactomes

Evolutionarily conserved protein-protein interactions (PPIs) reveal fundamental biological processes. However, predicting protein function solely from these interactions provides an incomplete picture of biological systems. Computational methods for predicting PPIs often struggle due to limited functional annotations in databases, making it difficult to fully understand unique biological systems.. This study introduces ContextMirror2.0 (CM2.0), a coevolution-based method designed to address these limitations. Coevolutionary approaches, unlike supervised machine learning methods, do not rely on labelled datasets, proving valuable in addressing the scarcity of data for species-specific PPIs. While around 40% of CM2.0s top-1000 predicted PPIs for E. coli, S. enterica, and S. aureus are present in experimental PPI databases, a comparative analysis of predicted functional communities revealed highly conserved interaction patterns and species-specific interactions. CM2.0 leverages coevolutionary information to explore protein interaction dynamics and understand the functional consequences of species-specific variations. This information can inform further studies on the emergence of novel functions, adaptation to specific environments, and the development of targeted therapies.

bioinformatics↗

bioRxiv2023

Frustraevo: A Web Server To Localize And Quantify The Conservation Of Local Energetic Frustration In Protein Families

According to the Principle of Minimal Frustration, folded proteins can have only a minimal number of strong energetic conflicts in their native states. However, not all interactions are energetically optimized for folding but some remain in energetic conflict, i.e. they are highly frustrated. This remaining local energetic frustration has been shown to be statistically correlated with distinct functional aspects such as protein-protein interaction sites, allosterism and catalysis. Fuelled by the recent breakthroughs in efficient protein structure prediction that have made available good quality models for most proteins, we have developed a strategy to calculate local energetic frustration within large protein families and quantify its conservation over evolutionary time. Based on this evolutionary information we can identify how stability and functional constraints have appeared at the common ancestor of the family and have been maintained over the course of evolution. Here, we present FrustraEvo, a web server tool to calculate and quantify the conservation of local energetic frustration in protein families. The webserver is freely available at URL: https://frustraevo.qb.fcen.uba.ar

bioinformatics↗