{"title":"通过蛋白质聚集棱镜解码阿尔茨海默病和2型糖尿病之间的关系。","authors":"Vaishnavi Tammara, Atanu Das","doi":"10.1021/acschemneuro.5c00357","DOIUrl":null,"url":null,"abstract":"<p><p>Alzheimer's disease (AD) and type-2 diabetes (T2D) are two fatal human diseases and have been linked to the aberrant aggregation of two distinct peptides, amyloid-β (Aβ) and human islet amyloid polypeptide (hIAPP), respectively. These two peptide aggregates, even with distal deposition sites (brain and pancreas), act as mutual beneficiaries. We here unveiled the crosstalk in a self-consistent fashion using atomistic simulations by comparing the kinetics and thermodynamics of self- and cross-aggregations of Aβ<sub>42</sub> and hIAPP and their modulations by preformed fibrillar templates. Templates (specifically hIAPP) generally accelerate aggregation, alter the relative order of aggregation rates (cross-aggregation > Aβ self-aggregation > hIAPP self-aggregation for nontemplated and hIAPP self-aggregation > cross-aggregation > Aβ self-aggregation for templated), and flip the mutual impact (hIAPP aggravates Aβ aggregation in nontemplated and the reverse in templated). Higher instances of breaking larger aggregates and longer residence times of smaller aggregates decelerate aggregation, whereas interpeptide electrostatics (universal) and hydrogen bonds (templated) assist it. However, the equilibrium aggregability pattern contradicts kinetic rank-ordering, as Aβ displays a higher aggregability than hIAPP, templates increase aggregability for both peptides, and Aβ's self-aggregability supersedes cross-aggregability, which further surpasses hIAPP's self-aggregability. The equilibrium ensembles encompass polymorphic, nonfibrillar oligomers having substantially reduced α-helicity and slight β-propensity, with both parallel and antiparallel interpeptide orientations, primarily stabilized by electrostatics. A higher equilibrium aggregability means a greater helix-breaking capacity, a bias toward parallel orientation, and a lesser structural polymorphism. Water expulsion from peptide surroundings and distortion of water tetrahedrality prove that aggregation follows the liquid-liquid phase separation (LLPS) model.</p>","PeriodicalId":13,"journal":{"name":"ACS Chemical Neuroscience","volume":" ","pages":""},"PeriodicalIF":3.9000,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Decoding the Relationship between Alzheimer's Disease and Type-2 Diabetes via the Protein Aggregation Prism.\",\"authors\":\"Vaishnavi Tammara, Atanu Das\",\"doi\":\"10.1021/acschemneuro.5c00357\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Alzheimer's disease (AD) and type-2 diabetes (T2D) are two fatal human diseases and have been linked to the aberrant aggregation of two distinct peptides, amyloid-β (Aβ) and human islet amyloid polypeptide (hIAPP), respectively. These two peptide aggregates, even with distal deposition sites (brain and pancreas), act as mutual beneficiaries. We here unveiled the crosstalk in a self-consistent fashion using atomistic simulations by comparing the kinetics and thermodynamics of self- and cross-aggregations of Aβ<sub>42</sub> and hIAPP and their modulations by preformed fibrillar templates. Templates (specifically hIAPP) generally accelerate aggregation, alter the relative order of aggregation rates (cross-aggregation > Aβ self-aggregation > hIAPP self-aggregation for nontemplated and hIAPP self-aggregation > cross-aggregation > Aβ self-aggregation for templated), and flip the mutual impact (hIAPP aggravates Aβ aggregation in nontemplated and the reverse in templated). Higher instances of breaking larger aggregates and longer residence times of smaller aggregates decelerate aggregation, whereas interpeptide electrostatics (universal) and hydrogen bonds (templated) assist it. However, the equilibrium aggregability pattern contradicts kinetic rank-ordering, as Aβ displays a higher aggregability than hIAPP, templates increase aggregability for both peptides, and Aβ's self-aggregability supersedes cross-aggregability, which further surpasses hIAPP's self-aggregability. The equilibrium ensembles encompass polymorphic, nonfibrillar oligomers having substantially reduced α-helicity and slight β-propensity, with both parallel and antiparallel interpeptide orientations, primarily stabilized by electrostatics. A higher equilibrium aggregability means a greater helix-breaking capacity, a bias toward parallel orientation, and a lesser structural polymorphism. Water expulsion from peptide surroundings and distortion of water tetrahedrality prove that aggregation follows the liquid-liquid phase separation (LLPS) model.</p>\",\"PeriodicalId\":13,\"journal\":{\"name\":\"ACS Chemical Neuroscience\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2025-07-28\",\"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.5c00357\",\"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.5c00357","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
Decoding the Relationship between Alzheimer's Disease and Type-2 Diabetes via the Protein Aggregation Prism.
Alzheimer's disease (AD) and type-2 diabetes (T2D) are two fatal human diseases and have been linked to the aberrant aggregation of two distinct peptides, amyloid-β (Aβ) and human islet amyloid polypeptide (hIAPP), respectively. These two peptide aggregates, even with distal deposition sites (brain and pancreas), act as mutual beneficiaries. We here unveiled the crosstalk in a self-consistent fashion using atomistic simulations by comparing the kinetics and thermodynamics of self- and cross-aggregations of Aβ42 and hIAPP and their modulations by preformed fibrillar templates. Templates (specifically hIAPP) generally accelerate aggregation, alter the relative order of aggregation rates (cross-aggregation > Aβ self-aggregation > hIAPP self-aggregation for nontemplated and hIAPP self-aggregation > cross-aggregation > Aβ self-aggregation for templated), and flip the mutual impact (hIAPP aggravates Aβ aggregation in nontemplated and the reverse in templated). Higher instances of breaking larger aggregates and longer residence times of smaller aggregates decelerate aggregation, whereas interpeptide electrostatics (universal) and hydrogen bonds (templated) assist it. However, the equilibrium aggregability pattern contradicts kinetic rank-ordering, as Aβ displays a higher aggregability than hIAPP, templates increase aggregability for both peptides, and Aβ's self-aggregability supersedes cross-aggregability, which further surpasses hIAPP's self-aggregability. The equilibrium ensembles encompass polymorphic, nonfibrillar oligomers having substantially reduced α-helicity and slight β-propensity, with both parallel and antiparallel interpeptide orientations, primarily stabilized by electrostatics. A higher equilibrium aggregability means a greater helix-breaking capacity, a bias toward parallel orientation, and a lesser structural polymorphism. Water expulsion from peptide surroundings and distortion of water tetrahedrality prove that aggregation follows the liquid-liquid phase separation (LLPS) model.
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