This paper optimizes AlphaFold3 for rapid and reliable structural modeling of antibodies and T-cell receptors, achieving 45-fold faster MSA phase and 3.6-fold faster inference.

Computational and Structural Biotechnology Journal · Oct 26, 2026Peer-reviewedImmunology

Knowledge-guided machine-learning and reverse screening combined method to predict cancer cell line responses to cytotoxic molecules

Alessandro Cuozzo, Marta A. S. Perez, Antoine Daina, Vincent Zoete

The paper develops a method combining machine learning and reverse screening to predict cancer cell line responses to cytotoxic molecules, achieving 71% accuracy in identifying experimental targets.

bioRxiv · Dec 19, 2025 · PreprintBioinformatics

Key determinants of T cell epitope recognition revealed by TCR specificity profiles

Yan Liu, Giancarlo Croce, Daniel M. Tadros, Dana Léa Moreno, Alexandra Michel, Anne‐Christine Thierry, Raphaël Genolet, Marta A. S. Perez, Rachid Lani, Philippe Guillaume, Michaël Hebeisen, Matei Teleman, Kelvin Lau, Amédé Larabi, Julien Racle, , David Gfeller

The paper introduces TCR specificity profiles to identify key determinants of TCR-epitope recognition and shows their ability to predict cross-reactivity and interpret machine learning models.

bioRxiv · Nov 17, 2025 · PreprintImmunology

Phage display enables machine learning discovery of cancer antigen specific TCRs

Giancarlo Croce, Rachid Lani, Delphine Tardivon, Sara Bobisse, Mariastella de Tiani, Maiia E. Bragina, Marta A. S. Perez, Justine Michaux, Hui Song Pak, Alexandra Michel, Talita Gehret, Julien Schmidt, Philippe Guillame, Michal Bassani‐Sternberg, Vincent Zoete, , David Gfeller

The paper uses phage display and machine learning to discover TCRs specific to cancer antigens, identifying functional TCRs from large repertoires.

Science Advances · Jun 11, 2025Peer-reviewedBioinformatics