Biology subjects

Poley-Gil, M.

Publications and source records attributed to Poley-Gil, M..

4 recordsLinked to original sources

bioRxiv2026

Adaptive and Spandrel-like Constraints at Functional Sites in Protein Folds

How new molecular functions emerge during protein evolution remains a fundamental question in molecular biology. The energy landscape theory states that proteins are minimally frustrated, i.e. they have minimized their internal conflicts, to allow robust folding. Yet, not all energetic conflicts are eliminated, with functional regions such as catalytic residues and ligand-binding sites being often enriched in frustrated interactions, trading localized stability for biological activity. However, it is still uncertain whether this functional frustration is an evolutionary adaptation, positively selected despite its energetic cost or an inevitable physical byproduct of the fold architecture. Here, we combine reverse folding, structure prediction, and sequence analysis with local frustration profiling to address this long-standing question. Unexpectedly, we found that reverse folding algorithms are unable to energetically minimize evolutionary conserved frustration at specific residues, even when detrimental to overall structural stability. We propose that these frustration hotspots act as architectural spandrels, inherent physical constraints of the fold that evolution subsequently co-opts for function. Our findings connect biophysical constraints and evolutionary selection, providing a new framework to understand how functional specificity emerges in protein landscapes.

bioinformatics↗

bioRxiv2026

FrustrAI-Seq: Scaling Local Energetic Frustration to the Protein Sequence Space

Proteins fold into their native three-dimensional (3D) structures by navigating complex energy landscapes shaped by the biophysical and biochemical properties of their sequence. Once folded, some sequence positions (dubbed residues) remain locally frustrated, reflecting functional constraints incompatible with optimal packing. This local energetic frustration provides important insights into protein function and dynamics, but its analysis typically relies on structure-based energy calculations and remains energetically costly at scale. Here, we introduce an ultra-fast sequence-based prediction of local energetic frustration directly from protein sequences using embeddings from protein language models (pLMs). Our method, coined FrustrAI-Seq, enables proteome-wide frustration profiling in minutes (17 minutes for the entire human proteome on a single Nvidia H100 GPU) while retaining biologically relevant performance as shown for the alpha-globin and beta-lactamase family. By eliminating the need for explicit structural or evolutionary information, this approach expands frustration analysis to protein regions and classes that were previously inaccessible, including intrinsically disordered regions and high-throughput de novo designed protein datasets. To support reproducibility and large-scale applications, we provide the largest freely available resource of precomputed local frustration scores to date (10^6 proteins), along with model weights and complete training and inference code at: github.com/leuschjanphilipp/FrustrAI-Seq.

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↗

bioRxiv2023

Novel diagnosis and progression microRNA signatures in melanoma

Melanoma incidence is rising, and accurate risk stratification remains challenging because of the molecular heterogeneity underlying disease progression. Specifically, the transition from benign nevi to malignant melanoma and the acquisition of the aggressive ulcerated phenotype represent critical barriers in clinical management that require novel biomarkers. In addition, there is a critical need for novel biomarkers to identify patients with primary melanoma who, despite complete surgical resection, remain at high risk of recurrence and would benefit from adjuvant therapy. We applied an integrative systems biology approach to decipher the miRNA-dependent regulatory architecture of melanoma. Following PRISMA guidelines, we conducted a robust meta-analysis of six independent transcriptomic studies, overcoming inter-study heterogeneity. This was coupled with network inference algorithms to construct validated miRNA-mRNA interactomes and identify dynamic functional modules. In the diagnostic scenario, we identified a consensus signature of 24 miRNAs. Network topology analysis revealed hsa-miR-142-5p as a master regulator that orchestrates the dismantling of the Oncogene-Induced Senescence (OIS) barriers by targeting CDK6, SIRT1, and TGFBR2. In the prognostic scenario (ulceration), we identified a specific "stress-adaptive" signature of 23 miRNAs. Notably, the upregulation of hsa-miR-223-3p emerged as a key driver of invasiveness by suppressing the motility-limiting tumor suppressor RHOB, while the concurrent loss of hsa-miR-200c and hsa-miR-489-3p may unleash Epithelial-Mesenchymal Transition (EMT) and EGFR-driven survival pathways. Our study supports a double-switch mechanism where specific miRNA alterations first drive senescence escape and subsequently promote survival in the hypoxic ulcerated niche. These signatures offer robust biomarkers for diagnosis and highlight the miR-142-5p/CDK6 and miR-223-3p/RHOB axes as potential therapeutic targets for precise intervention.

cancer biology↗