Biology subjects

Scalzitti, N.

Publications and source records attributed to Scalzitti, N..

3 recordsLinked to original sources

bioRxiv2025

Machine learning-based development of Gadolinium binding peptides

Gadolinium-based contrast agents (GBCAs) are indispensable tools in magnetic resonance imaging (MRI), yet their clinical use is limited by non-specific tissue accumulation, low molecular specificity, and safety concerns. Protein and peptide scaffolds provide a promising alternative because they can bind metal ions with high selectivity and enable precise molecular targeting. However, identifying short peptide motifs with optimal gadolinium (Gd3) coordination and high relaxivity remains a major challenge. Here, we used a machine-learning-driven peptide evolution platform, the Protein Optimization Engineering Tool (POET), to design and optimize short Gd-binding motifs that enhance longitudinal relaxivity (r). Two algorithmic strategies were tested; motif-based and regular-expression-based representations, both were trained on an initial set of 74 twelve-amino-acid peptides derived from natural EF-hand scaffolds. Through two rounds of directed evolution and experimental screening, we identified peptides with up to a 24% increase in r ratio compared with the best natural EF-hand, and a 55% improvement in absolute r after removal of unbound Gd. Further analysis revealed that peptides exhibiting higher relaxivity generally possessed a more negative net charge and lower isoelectric point than the buffer pH, indicating stronger electrostatic stabilization of Gd3. Sequence enrichment analysis showed that acidic and small polar residues, particularly aspartic acid, glycine, and threonine, were selectively favored during evolution, while bulky hydrophobic and basic residues were depleted. These compositional trends align with improved solubility and enhanced metal coordination. Together, these results demonstrate a generalizable framework that integrates computational evolution with biophysical screening to discover new biologically derived Gd-binding motifs. This approach provides a scalable route to engineer responsive, tunable, and biocompatible MRI contrast tags for precision imaging and molecular diagnostics.

biophysics↗

bioRxiv2025

Do 5' regions of human protein-coding genes contain the blueprints for alternative splicing?

To investigate alternative splicing capacity, we statistically compared the properties of human protein-coding genes with multiple transcript isoforms (MISOG) and single transcript isoforms (SISOG). Apart from global exon content, differential features are concentrated in the 5 gene regions, with MISOG presenting complex 5 untranslated region architecture and a distinctive flanking environment around first 5 intron. Importantly, we found that 5 exons are more prone to alternative splicing in MISOG. These results unravel previous observations indicating the importance of 5 gene regions in some transcriptional processes and call for their reassessment in light of the MISOG/SISOG profiles.

bioinformatics↗

bioRxiv2022

CeGAL: revisiting a widespread fungal-specific TF family using an in silico error-aware approach to identify missing zinc cluster domains

Transcription factors (TF) regulate gene activity in eukaryotic cells by binding specific regions of genomic DNA. In fungi, the most abundant TF class contains a fungal-specific GAL4-like Zn2C6 DNA binding domain (DBD), while the second class contains another fungal-specific domain, known as fungal_trans or Middle Homology Domain (MHD), whose function remains largely uncharacterized. Remarkably, almost a third of MHD-containing TF in public sequence databases apparently lack DNA binding activity, since they are not predicted to contain a DBD. Here, we reassess the domain organization of these MHD-only proteins using an in silico error-aware approach. Our large-scale analysis of ~17000 MHD-only TF sequences showed that the vast majority (>90%) result from gene annotation errors, thus contradicting previous findings that the MHD-only TF are widespread in fungi. We show that they are in fact exceptional cases, and that the Zn2C6-MHD domain pair represents the canonical domain signature defining a new TF family composed of two fungal-specific domains. We call this family CeGAL, after the most characterized members: Cep3, whose 3D structure has been determined and GAL4, an archetypal eukaryotic TF. This definition should improve the classification of the Zn2C6 TF and provide critical insights into fungal gene regulatory networks. IMPORTANCEIn fungi, extensive efforts focus on genome-wide characterization of potential Transcription Factors (TFs) and their targets genes to provide a better understanding of fungal processes and a rational for transcriptional manipulation. The second most abundant families of fungal-specific TFs, characterized by a Middle Homology Domain, are major regulators of primary and secondary metabolisms, multidrug resistance and virulence. Remarkably, one third of these TFs do not have a DNA Binding Domain (DBD-orphan) and thus are excluded from genome-wide studies. This particularity has been the subject of debate for many years. By computationally inspecting the close genomic environment of about 20,000 DBD-orphan TFs from a wide range of fungal species, we reveal that more than 90% contained sequences encoding a zinc-finger DBD. This analysis implies that the arrays of DBD containing TFs and their control DNA-sequences in target genes need to be reconsidered and expands the combinatorial regulation degree of the crucial fungal processes controlled by this TF family.

bioinformatics↗