Collagens are integral structural proteins in animal tissues and play key functional roles in cellular modulation. We sought to discover collagen model peptides (CMPs) that would form triple helices and self-assemble into supramolecular fibrils exhibiting collagen-like biological activity without preorganizing the peptide chains by covalent linkages. This challenging objective was accomplished by placing aromatic groups on the ends of a representative 30-mer CMP, (GPO)10, as with L-phenylalanine and L-pentafluorophenylalanine in 32-mer 1a. Computational studies on homologous 29-mers 1a-d (one less GPO), as pairs of triple helices interacting head-to-tail, yielded stabilization energies in the order 1a > 1b > 1c > 1d, supporting the hypothesis that hydrophobic aromatic groups can drive CMP self-assembly. Peptides 1a-d were studied comparatively relative to structural properties and ability to stimulate human platelets. Although each 32-mer formed stable triple helices (CD) spectroscopy, only 1a and 1b self-assembled into micrometer-scale fibrils. Light microscopy images for 1a depicted long collagen-like fibrils, whereas images for 1d did not. Atomic force microscopy topographical images indicated that 1a and 1b self-organize into microfibrillar species, whereas 1c and 1d do not. Peptides 1a and 1b induced the aggregation of human blood platelets with a potency similar to type I collagen, whereas 1c was much less effective, and 1d was inactive (EC50 potency: 1a/1b Ͼ Ͼ 1c > 1d). Thus, 1a and 1b spontaneously self-assemble into thrombogenic collagen-mimetic materials because of hydrophobic aromatic interactions provided by the special end-groups. These findings have important implications for the design of biofunctional CMPs.biomaterial ͉ platelets ͉ structure-function ͉ supramolecular triplex T he self-association of peptides and proteins into well ordered supramolecular structures is of pivotal importance in normal physiology and pathophysiology, such as in the assembly of collagen fibrils (1), actin filaments (2), and amyloid fibrils (3, 4). Collagens, which constitute a ubiquitous protein family in animals, contribute an essential matrix component to soft tissues and bones (5, 6). A structural hallmark of many collagens is a rope-like triple helix, the architecture of which derives from the interplay of three proline-rich polypeptide strands (e.g., two ␣1 and one ␣2 for type I collagen) (6-8). In the core domain of the triple helix, the amino acid sequence G-X-Y is repeated multiple times, and each glycine amide NH forms a hydrogen bond with the X-position amide carbonyl on an adjacent strand. The X-and Y-positions are often populated by L-proline and 4(R)-hydroxy-L-proline (O; Hyp), respectively, with the latter stabilizing the triple helix by stereoelectronic effects (9) and water-bridged hydrogen bonds (10).To investigate collagen's structure and function, researchers have resorted to using synthetic collagen model peptides (CMPs)

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The Multi-Attribute Method (MAM) Consortium was initially formed as a venue to harmonize best practices, share experiences, and generate innovative methodologies to facilitate widespread integration of the MAM platform, which is an emerging ultra-high-performance liquid chromatography–mass spectrometry application. Successful implementation of MAM as a purity-indicating assay requires new peak detection (NPD) of potential process- and/or product-related impurities. The NPD interlaboratory study described herein was carried out by the MAM Consortium to report on the industry-wide performance of NPD using predigested samples of the NISTmAb Reference Material 8671. Results from 28 participating laboratories show that the NPD parameters being utilized across the industry are representative of high-resolution MS performance capabilities. Certain elements of NPD, including common sources of variability in the number of new peaks detected, that are critical to the performance of the purity function of MAM were identified in this study and are reported here as a means to further refine the methodology and accelerate adoption into manufacturer-specific protein therapeutic product life cycles.