Paloma Tejera Nevado

The paper identifies shared amino acid patterns in cancer-related proteins and explores their potential for drug interaction analysis, focusing on ALDH2 and disulfiram.

This study benchmarks docking tools on experimental and AI-predicted protein structures to assess their accuracy in simulating protein-ligand interactions.

This study identifies conserved sequence patterns in cancer-related proteins and their structural implications, providing insights into potential biomarkers and therapeutic targets.

This work evaluates the confidence of deep learning models in predicting protein folding using two proteins with four domains of unknown function.