Matteo Cagiada

This study uses NMR to measure nanosecond methyl dynamics in the RNA exosome core, showing that relaxation-violated coherence transfer experiments can quantify side chain order parameters in large protein complexes.

The paper identifies synergistic antibody interactions against the malaria protein RIPR, showing how combinations of antibodies targeting specific domains inhibit parasite invasion.

This paper introduces ProtEGNN, a model combining protein language models with geometric equivariance to improve protein property and function prediction with fewer parameters than fine-tuned PLMs.

The paper reverse-engineers a TCR to reduce cross-reactivity while maintaining potency by reverting specific residues.

ABB4-STEROIDS generates antibody conformational ensembles with state-of-the-art accuracy, outperforming existing methods in experimental benchmarks.

The paper develops a framework to train supervised models on MAVE data by accounting for experimental protocol differences, improving variant effect prediction across datasets.

This study introduces a molecular dynamics model and databases to analyze CDR loop flexibility in antibodies and TCRs, enabling detailed study of their dynamics and machine learning training.

AF2χ predicts protein side-chain rotamer distributions using AlphaFold2, outperforming simulations and existing methods in speed and accuracy.

The paper uses generative models to predict absolute protein stability, achieving a mean error of 1.5 kcal/mol and a correlation coefficient of 0.7.

The paper uses machine learning to predict how loss-of-function variants affect protein stability and function across the human proteome, finding that half of such variants disrupt protein stability.

The paper uses deep mutational scanning to show that protein degradation and toxicity are tightly correlated in ASPA variants linked to Canavans disease.

This study maps human glucokinase variant activity using a yeast complementation assay, identifying activity patterns linked to disease and providing insights for variant interpretation and therapeutic development.