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Nonspecific Amyloid Aggregation of Chicken Smooth-Muscle Titin: In Vitro Investigations.

Alexander G BobylevElmira I YakupovaLiya G BobylevaNikolay V MolochkovAlexander A TimchenkoMaria A TimchenkoHiroshi KiharaAlexey D NikulinAzat G GabdulkhakovTatjana N MelnikNikita V PenkovMichail Y LobanovAlexey S KazakovMiklós S Z KellermayerZsolt MártonfalviOxana V GalzitskayaIvan M Vikhlyantsev
Published in: International journal of molecular sciences (2023)
A giant multidomain protein of striated and smooth vertebrate muscles, titin, consists of tandems of immunoglobulin (Ig)- and fibronectin type III (FnIII)-like domains representing β-sandwiches, as well as of disordered segments. Chicken smooth muscles express several titin isoforms of ~500-1500 kDa. Using various structural-analysis methods, we investigated in vitro nonspecific amyloid aggregation of the high-molecular-weight isoform of chicken smooth-muscle titin (SMT HMW , ~1500 kDa). As confirmed by X-ray diffraction analysis, under near-physiological conditions, the protein formed amorphous amyloid aggregates with a quaternary cross-β structure within a relatively short time (~60 min). As shown by circular dichroism and Fourier-transform infrared spectroscopy, the quaternary cross-β structure-unlike other amyloidogenic proteins-formed without changes in the SMT HMW secondary structure. SMT HMW aggregates partially disaggregated upon increasing the ionic strength above the physiological level. Based on the data obtained, it is not the complete protein but its particular domains/segments that are likely involved in the formation of intermolecular interactions during SMT HMW amyloid aggregation. The discovered properties of titin position this protein as an object of interest for studying amyloid aggregation in vitro and expanding our views of the fundamentals of amyloidogenesis.
Keyphrases
  • smooth muscle
  • type iii
  • protein protein
  • amino acid
  • binding protein
  • high resolution
  • magnetic resonance imaging
  • magnetic resonance
  • working memory
  • mass spectrometry
  • deep learning