Michele Vendruscolo

The paper maps the proteostasis network of membraneless organelles, revealing the role of anabolic components and molecular chaperones in regulating protein conformations.

The paper investigates the connection between Aβ and tau proteostasis networks, identifying HSP90 as a central hub that links their dysregulation in Alzheimer's disease.

This study identifies two critical sites in the C-terminal β-chain tail of clusterin that mediate its interaction with misfolded proteins, including amyloid β, through experimental and computational approaches.

The paper designs protein sequences with tailored kinetic properties using IF-MD, demonstrating slower unbinding kinetics in nanobody variants against SARS-CoV-2 RBD.

This paper shows that Alzheimer's amyloid-beta peptide forms biomolecular condensates on lipid bilayers, accelerating amyloid aggregation and revealing a new early step in the disease mechanism.

This study uses MEMMI to analyze the transient interactions between the fuzzy coat and cross-β core of Aβ42 filaments, revealing differences in solubility between familial and sporadic AD forms.

The paper identifies Imood as an intrinsically disordered protein with distinct expression patterns in T cells and plasma of OCD patients.

This paper introduces Molecular Dynamics Language Models (MDLMs) to generate MD trajectories efficiently, showing they can discover undersampled conformational states in proteins.

This paper introduces AlphaFold-Metainference to predict structural ensembles of disordered proteins using AlphaFold-derived distances in molecular dynamics simulations.

This study shows that A{beta}40 can undergo liquid-liquid phase separation and that this process enhances amyloid fibril formation in Alzheimer's disease.

This study shows that downregulating FBXO2 in human iPSC-derived neurons leads to Alzheimer's disease-like features including Aβ aggregation and tau hyperphosphorylation.

This study generates Aβ42 oligomers in human iPSC-derived neurons to model Alzheimer's disease and assess inhibitor effects.

This study develops a human iPSC-derived cortical neuron model that recapitulates AD pathology through TNFα treatment, showing Aβ aggregation, synaptic dysfunction, and hypermetabolism.

This study shows α-synuclein oligomers form via secondary nucleation on fibril surfaces, not from monomers, and this process is enhanced by agitation under physiological conditions.

CryoENsemble improves conformational ensembles from molecular dynamics simulations to better match cryo-EM data and extract dynamics information.

This study evaluates k-fold n-step forward cross-validation for improving out-of-distribution bioactivity predictions in drug discovery and recommends its use with specific metrics.

The paper identifies novel SNCA transcripts in human dopaminergic neurons and demonstrates their impact on antisense oligonucleotide therapy for Parkinson's disease.

RASP detects fluorescent puncta in complex cellular backgrounds with high precision and speed, outperforming existing methods by using image gradients to separate objects from noise.

The paper investigates droplet size distributions in protein phase separation and finds they follow a scale-invariant log-normal function, suggesting universal behavior and a method to estimate critical concentration.

This study investigates how Aβ42 amyloid fibrils change over time, showing increased length, thickness, and cross-β sheet content, which affects their ability to seed new aggregates.

This study uses liquid-phase transmission electron microscopy to visualize Aβ aggregation dynamics and intermediate oligomers in solution.

This paper introduces Ligand-Transformer, a deep learning framework for predicting protein-ligand interactions, and demonstrates its application in identifying inhibitors for specific targets and studying disordered proteins.

This paper introduces a single-molecule method using solid-state nanopores and DNA barcoding to detect and characterize misfolded protein oligomers, demonstrating its application to α-synuclein in Parkinson's disease.

This study identifies the αC-β4 loop as a key regulator of allosteric cooperativity between nucleotide and substrate in PKA-C through simulations and mutagenesis experiments.

The paper investigates the formation of amyloid loops in brain tissues and finds that protofibril flexibility, not hydrogen bonding, enables loop formation and disease-related toxicity.

A fragment-based computational method designs nanobodies targeting specific epitopes with nanomolar affinities, without requiring high-resolution antigen structures.

The paper identifies MOAG-4/SERF as modifiers of amyloid formation through charge complementation, showing that charge interactions drive protein aggregation and toxicity.

The paper shows that mitochondrial protein import defects lead to cytosolic aggregation of proteins, disrupting homeostasis and contributing to neurodegenerative disease mechanisms.

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 predicts droplet-promoting proteins in the human proteome using FuzDrop, concluding most proteins can undergo liquid-liquid phase separation.