A glial hyaluronate-binding protein (GHAP) was isolated from human brain white matter by affinity chromatography on immobilized hyaluronate. The 60 kDa protein appeared remarkably homogeneous by reversed-phase high pressure liquid chromatography analysis. Four cyanogen bromide peptides and 10 tryptic peptides were characterized by amino acid sequence, a total of 12 sequences since overlaps were found between 2 cyanogen bromide and 2 tryptic peptide sequences. Two sequences of brain GHAP had similarity with rat link protein, a hyaluronate binding protein in cartilage. The region of similarity was contained in the evolutionary conserved COOH-terminal half of link protein which is involved in the binding of hyaluronate. The remaining 10 amino acid sequences of brain GHAP had no similarity with link protein, nor with previously reported protein sequences. The findings suggest that the hyaluronate binding domains of such diverse proteins as brain GHAP and cartilage link protein are similar, probably due to the fact that hyaluronic acid is highly conserved in evolution.
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http://dx.doi.org/10.1016/0361-9230(89)90129-9 | DOI Listing |
Biomolecules
November 2024
Department of Surgical and Interventional Sciences, Faculty of Medicine and Health Sciences, McGill University, Montreal, QC H3G 2M1, Canada.
Neuropharmacology
January 2025
Department of Anesthesiology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China. Electronic address:
Biomolecules
October 2024
Department of Surgical and Interventional Sciences, McGill University, Montreal, QC H3T 1E2, Canada.
Bone
January 2025
Julius Wolff Institute, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Germany. Electronic address:
Treatment of bone fractures are standardized according to the AO classification, which mainly refers to the mechanical stabilization required in a given situation but neglect individual differences due to patient's healing potential or accompanying diseases. Specially in elderly or immune-compromised patients, the complexity of individual constrains on a biological as well as mechanical level are hard to account for. Here, we introduce a novel framework that allows to predict bone regeneration outcome using combined proteomic and mechanical analyses in a computer model.
View Article and Find Full Text PDFBiochem J
October 2024
Centre de recherche du Centre Hospitalier Universitaire (CHU) de Québec-Université Laval, Division Oncologie, Québec, QC, Canada.
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