F. Noe

Sub-membrane actin rings compartmentalize the plasma membrane

This paper shows that sub-membrane actin rings compartmentalize the plasma membrane by confining membrane protein motion in a periodic pattern, observed in neurons and other cell types.

Protein nanobarcodes enable single-step multiplexed fluorescence imaging

This paper introduces protein nanobarcodes for single-step multiplexed fluorescence imaging, enabling precise analysis of protein combinations.

Deep learning to decompose macromolecules into independent Markovian domains

This paper introduces a method combining independent Markov decomposition with VAMPnets to decompose large molecular systems into Markovian subdomains, improving data efficiency and interpretability.

Thermodynamics and kinetics of aggregation of flexible peripheral membrane proteins

This study develops a coarse-grained model to investigate the thermodynamics and kinetics of protein aggregation on membranes, showing how protein flexibility and surface concentration influence macroscopic aggregation behavior.

Independent Markov Decomposition: Towards modeling kinetics of biomolecular complexes

This paper introduces Independent Markov Decomposition (IMD) to model kinetics of biomolecular complexes by decomposing systems into weakly coupled subsystems, reducing sampling requirements while preserving accuracy.

Molecular mechanism of SARS-CoV-2 cell entry inhibition via TMPRSS2 by Camostat and Nafamostat mesylate

This study investigates how camostat and nafamostat inhibit SARS-CoV-2 entry by targeting TMPRSS2 through molecular simulations and experiments, showing nafamostat's higher efficacy due to increased Michaelis complex binding.

What Markov state models can and cannot do: Correlation versus path-based observables in protein folding models

This study evaluates the ability of Markov state models (MSMs) to reproduce path-based observables in protein folding, finding they are reliable only when state lifetimes exceed the lag time, and history-augmented MSMs improve reliability.

Alpha 1 Antitrypsin is an Inhibitor of the SARS-CoV-2-Priming Protease TMPRSS2

This study identifies alpha 1 antitrypsin (A1AT) as a TMPRSS2 inhibitor that limits SARS-CoV-2 dissemination by inhibiting extracellular proteases involved in viral entry.

Discovery of a hidden transient state in all bromodomain families

The paper identifies a transient state in all bromodomain families using molecular dynamics simulations and structural data, suggesting it acts as an allosteric regulatory switch.

Coupling of conformational switches in calcium sensor unraveled with local Markov models and transfer entropy

The paper uses molecular dynamics and Markov models to analyze conformational coupling in the C2A domain of Synaptotagmin-1, revealing how calcium binding influences domain switching.

Large-scale simulation of biomembranes: bringing realistic kinetics to coarse-grained models

The paper introduces a framework that integrates coarse-grained membrane models with hydrodynamics to simulate biomembranes with realistic kinetics at low computational cost.

Polymer-like model to study the dynamics of dynamin filaments on deformable membrane tubes

The paper develops a polymer-like model to study dynamin filament dynamics on deformable membrane tubes, finding that filament pitch, not radius, is sensitive to membrane tension and stiffness.

Dynamic Graphical Models of Molecular Kinetics

This paper introduces Dynamic Graphical Models (DGMs) to describe molecular kinetics and thermodynamics, showing they can predict new metastable states with fewer parameters than traditional methods.

Reactive SINDy: Discovering governing reactions from concentration data

This paper introduces reactive SINDy, a method to estimate reaction networks from time series data, and demonstrates its application to gene regulation networks.

ReaDDy 2: Fast and flexible software framework for interacting-particle reaction dynamics

ReaDDy 2 is a software framework for simulating interacting-particle reaction dynamics, offering efficient and flexible simulation capabilities with Python and C++ interfaces.

OpenPathSampling: A Python framework for path sampling simulations. II. Building and customizing path ensembles and sample schemes

This paper introduces theoretical developments in the OpenPathSampling framework for path sampling simulations, focusing on path ensemble construction and Monte Carlo procedure customization.

OpenPathSampling: A Python framework for path sampling simulations. I. Basics

The paper introduces OpenPathSampling, a Python framework for path sampling simulations, providing tools for various transition path sampling methods and demonstrating their application to benchmark problems.