Francesco Costa

Our group is hiring a postdoc to work on Digital Twin development for rare diseases. Collaborate with me and a fantastic interdisciplinary team! Deadline coming up this Sunday!

@embl @MSCActions @EMBLHeidelberg @EMBLHamburg @EMBLGrenoble @emblebi @EMBLBarcelona @EMBLRome We would welcome applicants who wish to advance @PfamDB and/or @InterProDB

Our paper on the Protein Design Archive has just been published in @NatureBiotech! It describes our web application for exploring designed proteins (link ⬇️) and contains analysis of how they have changed over time. @MartaChronowska @mjstam @WoolfsonLab nature.com/articles/s4158…

De Novo Design of Proteins for Autocatalytic Isopeptide Bond Formation | Journal of the American Chemical Society @UCSDChemBiochem pubs.acs.org/doi/10.1021/ja…

@atsoCF  @IoannisRiziotis   @andreeva789bg  @Alexbateman1

🙏 Special thanks to my amazing collaborators: @IoannisRiziotis , Rob Barringer, @andreeva789bg and to my supervisor @Alexbateman1 for their invaluable contributions to this work!

💻 Available as a Python package for easy integration into bioinformatics workflows, and accessible via Google Colab for everyone: colab.research.google.com/github/FranceC…

📢 Just published! Introducing Isopeptor: a computational tool for detecting intramolecular isopeptide bonds in protein structures with high precision and recall. academic.oup.com/bioinformatics…

Check out this article about my research at @emblebi where I focus on protein modelling and on the study of fibrillar adhesins. Recently, we developed a method to detect isopeptide bonds, a key stabilizing feature in bacterial proteins. Big thanks to @oanastroe123!!👇

NERVE 2.0: Boosting the New Enhanced Reverse Vaccinology Environment via Artificial Intelligence and a User-Friendly Web Interface 1. NERVE 2.0 introduces updates to reverse vaccinology with AI-powered tools and a web interface, aiming to simplify vaccine candidate identification and analysis for diverse users. 2. New modules like ESPAAN predict adhesins with improved accuracy, while Virulent expands the search to virulence factors, addressing broader vaccine development needs. 3. Loop-Razor recovers extracellular regions of transmembrane proteins, allowing researchers to explore potential candidates often overlooked in previous pipelines. 4. Epitope Prediction targets epitopes with broad population coverage, utilizing linear HLA alleles to streamline immunogenicity assessments. 5. The redesigned web platform improves usability with modular options, adjustable parameters, and data storage, making it accessible to researchers with varying levels of bioinformatics expertise. 6. Benchmarking results show NERVE 2.0 performing better than its predecessor and tools like Vaxign2 and VaxiJen, demonstrating reliable enrichment in identifying bacterial protective antigens. 7. With both web-based and standalone versions, NERVE 2.0 supports flexible workflows for comprehensive reverse vaccinology analyses. @Francescop966 💻Code: github.com/nerve-bio/NERVE 📜Paper: bmcbioinformatics.biomedcentral.com/articles/10.11… #ReverseVaccinology #Bioinformatics #VaccineDevelopment #MachineLearning #AI

Prediction confidence scores help #AlphaFold users gauge the reliability of protein structure predictions. But things get more challenging for protein families. This new method helps improve low confidence predictions within protein families. academic.oup.com/bioinformatics…

A special thanks goes to my supervisor @Alexbateman1 and to @matthiasblum for their support and guidance. 7/7

Our findings have important implications for improving structure predictions, especially for proteins from organisms with limited representation in sequence databases or for rapidly evolving taxa. 6/7

Excited to announce our latest publication: “Keeping it in the family: Using protein family templates to rescue low confidence AlphaFold2 models” where we explore plDDT variability in #AF2 models of @PfamDB domains. doi.org/10.1093/bioadv… 1/7

Feature 932 appears to associate with Asn involved in isopeptide bonds. Very cool work! (PDB IDs: 4OFQ, 2OKM, 1AMX)