Diego Javier Zea

AlphaConformers improves AlphaFold2 by generating multiple protein conformations using structural information from databases, outperforming existing methods in capturing alternative states.

This study identifies PDZD-8 as an ER protein that interacts with LGG-2/LC3 to promote autolysosome formation by bridging ER-autophagosome contacts.

The paper demonstrates that AlphaFold2-Multimer can identify interaction sites in intrinsically disordered regions with improved accuracy using fragment-based approaches and evolutionary information integration.

The paper introduces ASPRING, a method to detect alternatively spliced protein repeats across species, identifies over 5,000 conserved repeats, and maps them to 3D structures to study their role in protein interactions.

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 develops evolutionary splicing graphs to assess alternative splicing conservation across species and identifies genes where alternative splicing affects pseudo-repeats.

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 reconstructs the evolutionary history of JNK family transcripts and models their protein structures to understand how alternative splicing and transcription sites contribute to functional diversity.

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.