Uncovering Intermolecular Interactions Driving the Liquid–Liquid Phase Separation of the TDP-43 Low-Complexity Domain via Atomistic Dimerization Simulations
Huayuan Tang, Yunxiang Sun, Lei Wang, Pu Chun Ke, Feng Ding
{"title":"Uncovering Intermolecular Interactions Driving the Liquid–Liquid Phase Separation of the TDP-43 Low-Complexity Domain via Atomistic Dimerization Simulations","authors":"Huayuan Tang, Yunxiang Sun, Lei Wang, Pu Chun Ke, Feng Ding","doi":"10.1021/acs.jcim.4c00943","DOIUrl":null,"url":null,"abstract":"Liquid–liquid phase separation (LLPS) of transactive response DNA-binding protein of 43 kDa (TDP-43), which exerts multiple functions in the splicing, trafficking, and stabilization of RNA, mediates the formation of membraneless condensates with crucial physiological roles, while its aberrant LLPS is linked to multiple neurodegenerative diseases. However, due to the heterogeneous and dynamic nature of LLPS, major gaps remain in understanding the precise intermolecular interactions driving LLPS and how specific mutations alter LLPS dynamics. Here, we investigated the molecular mechanisms underlying the LLPS of the TDP-43 low-complexity domain (LCD) by simulating the dimerization process using all-atom discrete molecular dynamics with microsecond-long simulations. Our results showed that the TDP-43 LCD was intrinsically disordered, with helical structures consistent with prior nuclear magnetic resonance studies. Phase separation propensity was assessed by simulating the dimerization of the TDP-43 LCD and four mutants, showing that A321G, W334G, and M337V inhibited self-association, while G335D promoted it, fully consistent with experimental reports. During the dimerization process, two peptides experienced both elastic and nonelastic collisions, and the self-associated dimer featured both high- and low-contact states. These results suggested that the dimerization process of the TDP-43 LCD was accordingly dynamic and heterogeneous. Additionally, we identified crucial regions containing hydrophobic clusters and aromatic residues in the N-terminus, central region, and C-terminus that were essential for the self-association of the TDP-43 LCD. These residues with high binding affinities can act as stickers to form peptide networks in LLPS. Together, our simulation provides a comprehensive picture of the intermolecular interactions driving the phase separation of the TDP-43 LCD, offering insights into both physiological functions and pathological mechanisms.","PeriodicalId":44,"journal":{"name":"Journal of Chemical Information and Modeling ","volume":null,"pages":null},"PeriodicalIF":5.6000,"publicationDate":"2024-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Chemical Information and Modeling ","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1021/acs.jcim.4c00943","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
引用次数: 0
Abstract
Liquid–liquid phase separation (LLPS) of transactive response DNA-binding protein of 43 kDa (TDP-43), which exerts multiple functions in the splicing, trafficking, and stabilization of RNA, mediates the formation of membraneless condensates with crucial physiological roles, while its aberrant LLPS is linked to multiple neurodegenerative diseases. However, due to the heterogeneous and dynamic nature of LLPS, major gaps remain in understanding the precise intermolecular interactions driving LLPS and how specific mutations alter LLPS dynamics. Here, we investigated the molecular mechanisms underlying the LLPS of the TDP-43 low-complexity domain (LCD) by simulating the dimerization process using all-atom discrete molecular dynamics with microsecond-long simulations. Our results showed that the TDP-43 LCD was intrinsically disordered, with helical structures consistent with prior nuclear magnetic resonance studies. Phase separation propensity was assessed by simulating the dimerization of the TDP-43 LCD and four mutants, showing that A321G, W334G, and M337V inhibited self-association, while G335D promoted it, fully consistent with experimental reports. During the dimerization process, two peptides experienced both elastic and nonelastic collisions, and the self-associated dimer featured both high- and low-contact states. These results suggested that the dimerization process of the TDP-43 LCD was accordingly dynamic and heterogeneous. Additionally, we identified crucial regions containing hydrophobic clusters and aromatic residues in the N-terminus, central region, and C-terminus that were essential for the self-association of the TDP-43 LCD. These residues with high binding affinities can act as stickers to form peptide networks in LLPS. Together, our simulation provides a comprehensive picture of the intermolecular interactions driving the phase separation of the TDP-43 LCD, offering insights into both physiological functions and pathological mechanisms.
期刊介绍:
The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery.
Astute chemists, computer scientists, and information specialists look to this monthly’s insightful research studies, programming innovations, and software reviews to keep current with advances in this integral, multidisciplinary field.
As a subscriber you’ll stay abreast of database search systems, use of graph theory in chemical problems, substructure search systems, pattern recognition and clustering, analysis of chemical and physical data, molecular modeling, graphics and natural language interfaces, bibliometric and citation analysis, and synthesis design and reactions databases.