Gustavo D. Parisi

The paper identifies transposable elements as a source of intrinsic disorder in human proteins, showing that TE insertions are enriched in disordered regions and their conformational fate depends on their age and TE class.

The paper introduces BAV-LLPS, a database of LLPS proteins from bacteria, archaea, and viruses, containing over 5,000 proteins with annotations and structural models.

This paper identifies a novel Ca2+-binding motif in MICU1 that functions as an early sensor, triggering structural changes that refine its regulatory role in mitochondrial Ca2+ uptake.

The paper uses AlphaFold2 to predict protein-ligand interactions in disordered regions, identifying 'ghost interactions' not captured in crystal structures.

This study shows that AlphaFold2 struggles to predict accurate 3D structures of proteins with conformational epistasis, as seen in the glucocorticoid receptor, but performs well for proteins without such epistasis like the mineralocorticoid receptor.

CoDNaS-Q is a database of conformational diversity in homooligomeric proteins with quaternary structure, providing curated structures and annotations for research.

CaviDB is a database of protein cavities and their features, integrating structural and functional data to support drug design and protein function studies.

This study evaluates AlphaFold2's ability to predict ensemble protein conformations and finds it struggles with conformational diversity, with performance worsening as diversity increases.

The paper identifies a conserved promiscuous reaction in serum albumins across mammals and suggests evolutionary adaptations in residues with unknown functions.

CoDNaS-RNA is a database that clusters known RNA structures to identify alternative conformers and provides structural and functional annotations.

CardIAP is a web application that automates the analysis of calcium fluorescence imaging data to identify spatio-temporal patterns and extract quantitative information on calcium dynamics.

The paper evaluates 43 methods for predicting intrinsically disordered regions and binding regions in proteins, finding that deep learning methods outperform older physicochemical approaches but binding prediction remains challenging.

The paper shows that evolutionary rates of intrinsically disordered proteins correlate with conformational diversity, suggesting that structural constraints from selected conformers influence rate heterogeneity.

The paper compares structural constraints in ordered and disordered protein ensembles, finding similar proportions of constrained sites and long-range contacts.

ProtMiscuity is a manually-curated database of promiscuous proteins containing 57 proteins from 40 organisms with 88 reactions, providing annotated data linked to other resources.

This study shows that structural divergence affects conservation and covariation estimates in protein families, suggesting that using multiple structures improves the interpretation of evolutionary signals.

This paper investigates how conformational diversity affects the correlation between sequence and structural divergence in homology modeling, finding that it reduces correlation and that order/disorder can improve model performance.