Meenakshi Pillai, Anjali D Patil, Atanu Das, Santosh Kumar Jha
{"title":"病理突变 D169G 和 P112H 会静电加剧 TDP-43 功能域的淀粉样形成。","authors":"Meenakshi Pillai, Anjali D Patil, Atanu Das, Santosh Kumar Jha","doi":"10.1021/acschemneuro.4c00372","DOIUrl":null,"url":null,"abstract":"<p><p>Aggregation of TDP-43 is linked to the pathogenesis of many neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS). Notably, electrostatic point mutations such as D169G and P112H, located within the highly conserved functional tandem RNA recognition motif (RRM) domains of the TDP-43 protein (TDP-43<sup>tRRM</sup>), have been identified in diseased patients as well. In this study, we address how the electrostatic mutations alter both the native state stability and aggregation propensity of TDP-43<sup>tRRM</sup>. The mutants D169G and P112H show increased chemical stability compared to the TDP-43<sup>tRRM</sup> at physiological pH. However, at low pH, both the mutants undergo a conformational change to form amyloid-like fibrils, though with variable rates─the P112H mutant being substantially faster than the other two sequences (TDP-43<sup>tRRM</sup> and D169G mutant) showing comparable rates. Moreover, among the three sequences, only the P112H mutant undergoes a strong ionic strength-dependent aggregability trend. These observations signify the substantial contribution of the excess charge of the P112H mutant to its unique aggregation process. Complementary simulated observables with atomistic resolution assign the experimentally observed sequence-, pH-, and ionic strength-dependent aggregability pattern to the degree of thermal lability of the mutation site-containing RRM1 domain and its extent of dynamical anticorrelation with the RRM2 domain whose combination eventually dictate the extent of generation of aggregation-prone partially unfolded conformational ensembles. Our choice of a specific charge-modulated pathogenic mutation-based experiment-simulation-combination approach unravels the otherwise hidden residue-wise contribution to the individual steps of this extremely complicated multistep aggregation process.</p>","PeriodicalId":13,"journal":{"name":"ACS Chemical Neuroscience","volume":null,"pages":null},"PeriodicalIF":4.1000,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Pathological Mutations D169G and P112H Electrostatically Aggravate the Amyloidogenicity of the Functional Domain of TDP-43.\",\"authors\":\"Meenakshi Pillai, Anjali D Patil, Atanu Das, Santosh Kumar Jha\",\"doi\":\"10.1021/acschemneuro.4c00372\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Aggregation of TDP-43 is linked to the pathogenesis of many neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS). Notably, electrostatic point mutations such as D169G and P112H, located within the highly conserved functional tandem RNA recognition motif (RRM) domains of the TDP-43 protein (TDP-43<sup>tRRM</sup>), have been identified in diseased patients as well. In this study, we address how the electrostatic mutations alter both the native state stability and aggregation propensity of TDP-43<sup>tRRM</sup>. The mutants D169G and P112H show increased chemical stability compared to the TDP-43<sup>tRRM</sup> at physiological pH. However, at low pH, both the mutants undergo a conformational change to form amyloid-like fibrils, though with variable rates─the P112H mutant being substantially faster than the other two sequences (TDP-43<sup>tRRM</sup> and D169G mutant) showing comparable rates. Moreover, among the three sequences, only the P112H mutant undergoes a strong ionic strength-dependent aggregability trend. These observations signify the substantial contribution of the excess charge of the P112H mutant to its unique aggregation process. Complementary simulated observables with atomistic resolution assign the experimentally observed sequence-, pH-, and ionic strength-dependent aggregability pattern to the degree of thermal lability of the mutation site-containing RRM1 domain and its extent of dynamical anticorrelation with the RRM2 domain whose combination eventually dictate the extent of generation of aggregation-prone partially unfolded conformational ensembles. Our choice of a specific charge-modulated pathogenic mutation-based experiment-simulation-combination approach unravels the otherwise hidden residue-wise contribution to the individual steps of this extremely complicated multistep aggregation process.</p>\",\"PeriodicalId\":13,\"journal\":{\"name\":\"ACS Chemical Neuroscience\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.1000,\"publicationDate\":\"2024-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Chemical Neuroscience\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1021/acschemneuro.4c00372\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Chemical Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1021/acschemneuro.4c00372","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
Pathological Mutations D169G and P112H Electrostatically Aggravate the Amyloidogenicity of the Functional Domain of TDP-43.
Aggregation of TDP-43 is linked to the pathogenesis of many neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS). Notably, electrostatic point mutations such as D169G and P112H, located within the highly conserved functional tandem RNA recognition motif (RRM) domains of the TDP-43 protein (TDP-43tRRM), have been identified in diseased patients as well. In this study, we address how the electrostatic mutations alter both the native state stability and aggregation propensity of TDP-43tRRM. The mutants D169G and P112H show increased chemical stability compared to the TDP-43tRRM at physiological pH. However, at low pH, both the mutants undergo a conformational change to form amyloid-like fibrils, though with variable rates─the P112H mutant being substantially faster than the other two sequences (TDP-43tRRM and D169G mutant) showing comparable rates. Moreover, among the three sequences, only the P112H mutant undergoes a strong ionic strength-dependent aggregability trend. These observations signify the substantial contribution of the excess charge of the P112H mutant to its unique aggregation process. Complementary simulated observables with atomistic resolution assign the experimentally observed sequence-, pH-, and ionic strength-dependent aggregability pattern to the degree of thermal lability of the mutation site-containing RRM1 domain and its extent of dynamical anticorrelation with the RRM2 domain whose combination eventually dictate the extent of generation of aggregation-prone partially unfolded conformational ensembles. Our choice of a specific charge-modulated pathogenic mutation-based experiment-simulation-combination approach unravels the otherwise hidden residue-wise contribution to the individual steps of this extremely complicated multistep aggregation process.
期刊介绍:
ACS Chemical Neuroscience publishes high-quality research articles and reviews that showcase chemical, quantitative biological, biophysical and bioengineering approaches to the understanding of the nervous system and to the development of new treatments for neurological disorders. Research in the journal focuses on aspects of chemical neurobiology and bio-neurochemistry such as the following:
Neurotransmitters and receptors
Neuropharmaceuticals and therapeutics
Neural development—Plasticity, and degeneration
Chemical, physical, and computational methods in neuroscience
Neuronal diseases—basis, detection, and treatment
Mechanism of aging, learning, memory and behavior
Pain and sensory processing
Neurotoxins
Neuroscience-inspired bioengineering
Development of methods in chemical neurobiology
Neuroimaging agents and technologies
Animal models for central nervous system diseases
Behavioral research