Biology subjects

Saldano, T. E.

Publications and source records attributed to Saldano, T. E..

2 recordsLinked to original sources

bioRxiv2023

Ghost interactions: revealing missing protein-ligand interactions using AlphaFold predictions

Protein-ligand interactions represent an essential step in understanding molecular recognition, an intense field of research for many scientific areas. Structural biology has played a central role in unveiling protein-ligand interactions, but current techniques are still not able to reliably describe the interactions of ligands with highly flexible regions. In this work we explored the capacity of AlphaFold2 (AF2) to estimate the presence of interactions between ligands and residues belonging to disordered regions, which we called "ghost interactions" as they are missing in the crystallographic derived structures. We found that AF2 models are good predictors of regions associated with order-disorder transitions. Additionally, we found that AF2 predicts residues making ghost interactions with ligands, which are mostly buried and show a differential evolutionary conservation. Our findings could fuel current areas of research that consider intrinsically disordered proteins as potentially valuable targets for drug development, given their biological relevance and associated diseases.

bioinformatics↗

bioRxiv2022

Expanding the repertoire of human tandem repeat RNA-binding proteins

Protein regions consisting of arrays of tandem repeats are known to bind other molecular partners, including nucleic acid molecules. Although the interactions between repeat proteins and DNA are already widely explored, studies characterising tandem repeat RNA-binding proteins are lacking. We performed a large-scale analysis of human proteins devoted to expanding the knowledge about tandem repeat proteins experimentally reported as RNA-binding molecules. This work is timely because of the release of a full set of accurate structural models for the human proteome amenable to repeat detection using structural methods. We identified 219 tandem repeat proteins that bind RNA molecules and characterised the overlap between repeat regions and RNA-binding regions as a first step towards assessing their functional relationship. Our results showed that the combination of sequence and structural methods finds more tandem repeat proteins than either method alone. We observed differences in the characteristics of regions predicted as repetitive by sequence-based or structure-based computational methods in terms of their sequence composition, their functions and their protein domains.

bioinformatics↗