Pasquale Miglionico

Atlantis integrates structural and functional residue-level data for the human proteome, enabling complex queries and analysis of protein interactions and mutations.

This study shows that activating GABAergic circuits with baclofen enhances the effectiveness of anti-PD-L1 immunotherapy in glioblastoma, leading to tumor regression and prolonged survival in mice.

This study shows that evolutionary divergence in LRRK2 interaction domains leads to species-specific protein interaction networks in humans and mice.

This study identifies a LRRK2-regulatory network through proximity proteomics and structural analysis, showing its link to centrosomes and how its conformation and activity state influence interactions.

This study predicts 3D structures of human GPCR-G protein complexes using AlphaFold3 and uses machine learning to predict coupling potency, revealing new signaling mechanisms and coupling preferences across GPCR subtypes.

The paper analyzes cell-cell interactions (CCIs) in transcriptomic data, showing they are more co-expressed in cancer and associated with patient survival and immunotherapy response.

The paper develops interpretable models to predict cancer drug sensitivity using transcriptomics data and enhances predictions with large language models, validated on clinical samples.

This study develops a method to predict protein-protein direct interactions and stable complexes using co-expression and co-evolution data, achieving high AUROC scores and better performance than existing tools.

The paper analyzes GPCR-G-protein complexes to identify structural determinants of G-protein coupling selectivity, revealing differences in contact patterns and stability between Gs and Gi/o complexes.