ArticleBiophysical journal2023
Multiscale simulations reveal TDP-43 molecular-level interactions driving condensation.
Article in Biophysical journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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28 citing papers in PubMed, 44 citations in OpenAlex.
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- Origin of the ionic-strength dependent reentrant behavior in the liquid-liquid phase separation of uncharged intrinsically disordered proteins.Communications chemistry · 2026Article
- Oxygen depletion in biomolecular condensates is dominated by macromolecular density.Nature communications · 2026Article
- Multiscale simulations of folded and intrinsically disordered region-containing protein condensates.Biophysical journal · 2026Article
- Amyloidogenic oligomers derived from TDP-43 LCD promote the condensation and phosphorylation of TDP-43.Chemical science · 2026Article
- Molecular dynamics simulation in traditional Chinese medicine research: from molecular mechanisms to multiscale validation.Frontiers in chemistry · 2026Review
- Multi-scale simulations of MUT-16 scaffold protein phase separation and client recognition.Biophysical journal · 2025Article
- Direct Observation of the Conformational Transitions in Tau and Their Correlation with Phase Behavior.JACS Au · 2025Article
- Biomolecular Condensates as Emerging Biomaterials: Functional Mechanisms and Advances in Computational and Experimental Approaches.Advanced materials (Deerfield Beach, Fla.) · 2025Review
- The Origin of the Ionic-strength Dependent Reentrant Behavior in Liquid-Liquid Phase Separation of Uncharged IDPs.bioRxiv : the preprint server for biology · 2025Article
- Uncovering protein conformational dynamics within two-component viral biomolecular condensates.Protein science : a publication of the Protein Society · 2025Article
- Determining the Role of Electrostatics in the Making and Breaking of the Caprin1-ATP Nanocondensate.The journal of physical chemistry. B · 2025Article
- MartiniGlass: a Tool for Enabling Visualization of Coarse-Grained Martini Topologies.Journal of chemical information and modeling · 2025Article
- Martini3-IDP: improved Martini 3 force field for disordered proteins.Nature communications · 2025Article
- Nonspecific Yet Selective Interactions Contribute to Small Molecule Condensate Binding.Journal of chemical theory and computation · 2024Article
- RNA binding tunes the conformational plasticity and intradomain stability of TDP-43 tandem RNA recognition motifs.Biophysical journal · 2024Article
- The molecular picture of the local environment in a stable model coacervate.Communications chemistry · 2024Article
- Martini 3 OliGo̅mers: A Scalable Approach for Multimers and Fibrils in GROMACS.Journal of chemical theory and computation · 2024Article
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Authors and funding
9 authors at 5 institutions in 3 countries.
Funding
Abstract
The RNA-binding protein TDP-43 is associated with mRNA processing and transport from the nucleus to the cytoplasm. TDP-43 localizes in the nucleus as well as accumulating in cytoplasmic condensates such as stress granules. Aggregation and formation of amyloid-like fibrils of cytoplasmic TDP-43 are hallmarks of numerous neurodegenerative diseases, most strikingly present in >90% of amyotrophic lateral sclerosis (ALS) patients. If excessive accumulation of cytoplasmic TDP-43 causes, or is caused by, neurodegeneration is presently not known. In this work, we use molecular dynamics simulations at multiple resolutions to explore TDP-43 self- and cross-interaction dynamics. A full-length molecular model of TDP-43, all 414 amino acids, was constructed from select structures of the protein functional domains (N-terminal domain, and two RNA recognition motifs, RRM1 and RRM2) and modeling of disordered connecting loops and the low complexity glycine-rich C-terminus domain. All-atom CHARMM36m simulations of single TDP-43 proteins served as guides to construct a coarse-grained Martini 3 model of TDP-43. The Martini model and a coarser implicit solvent C⍺ model, optimized for disordered proteins, were subsequently used to probe TDP-43 interactions; self-interactions from single-chain full-length TDP-43 simulations, cross-interactions from simulations with two proteins and simulations with assemblies of dozens to hundreds of proteins. Our findings illustrate the utility of different modeling scales for accessing TDP-43 molecular-level interactions and suggest that TDP-43 has numerous interaction preferences or patterns, exhibiting an overall strong, but dynamic, association and driving the formation of biomolecular condensates.
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