Fundación Instituto Leloir

About: Fundación Instituto Leloir is a facility organization based out in Buenos Aires, Argentina. It is known for research contribution in the topics: Dentate gyrus & Neurogenesis. The organization has 702 authors who have published 1052 publications receiving 39299 citations.

Retrograde Bone Morphogenetic Protein Signaling Shapes a Key Circadian Pacemaker Circuit

Abstract: The neuropeptide pigment-dispersing factor (PDF) synchronizes molecular oscillations within circadian pacemakers in the Drosophila brain. It is expressed in the small ventral lateral neurons (sLNvs) and large ventral lateral neurons, the former being indispensable for maintaining behavioral rhythmicity under free-running conditions. How PDF circuits develop the specific connectivity traits that endow such global behavioral control remains unknown. Here, we show that mature sLNv circuits require PDF signaling during early development, acting through its cognate receptor PDFR at postsynaptic targets. Yet, axonal defects by PDF knockdown are presynaptic and become apparent only after metamorphosis, highlighting a delayed response to a signal released early on. Presynaptic expression of constitutively active bone morphogenetic protein (BMP) receptors prevents pdfr mutants misrouting phenotype, while sLNv-restricted downregulation of BMP signaling components phenocopied pdf01. Thus, we have uncovered a novel mechanism that provides an early “tagging” of synaptic targets that will guide circuit refinement later in development.

Impact of protein conformational diversity on AlphaFold predictions

Abstract: After the outstanding breakthrough of AlphaFold in predicting protein 3D models, new questions appeared and remain unanswered. The ensemble nature of proteins, for example, challenges the structural prediction methods because the models should represent a set of conformers instead of single structures. The evolutionary and structural features captured by effective deep learning techniques may unveil the information to generate several diverse conformations from a single sequence. Here we address the performance of AlphaFold2 predictions under this ensemble paradigm. Using a curated collection of apo-holo conformations, we found that AlphaFold2 predicts the holo form of a protein in 70% of the cases, being unable to reproduce the observed conformational diversity with an equivalent error than in the estimation of a single conformation. More importantly, we found that AlphaFold29s performance worsens with the increasing conformational diversity of the studied protein. This impairment is related to the heterogeneity in the degree of conformational diversity found between different members of the homologous family of the protein under study. Finally, we found that main-chain flexibility associated with apo-holo pairs of conformers negatively correlates with the predicted local model quality score plDDT, indicating that plDDT values in a single 3D model could be used to infer local conformational changes linked to ligand binding transitions.