1. Exploiting the Features of Short Peptides to Recognize Specific Cell Surface Markers
- Author
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Michela Buonocore, Manuela Grimaldi, Angelo Santoro, Verdiana Covelli, Carmen Marino, Enza Napolitano, Sara Novi, Mario Felice Tecce, Elena Ciaglia, Francesco Montella, Valentina Lopardo, Valeria Perugini, Matteo Santin, and Anna Maria D’Ursi
- Subjects
peptides ,mesenchymal stromal cells ,molecular docking ,molecular dynamics ,FACS ,confocal microscopy ,Biology (General) ,QH301-705.5 ,Chemistry ,QD1-999 - Abstract
Antibodies are the macromolecules of choice to ensure specific recognition of biomarkers in biological assays. However, they present a range of shortfalls including a relatively high production cost and limited tissue penetration. Peptides are relatively small molecules able to reproduce sequences of highly specific paratopes and, although they have less biospecificity than antibodies, they offer advantages like ease of synthesis, modifications of their amino acid sequences and tagging with fluorophores and other molecules required for detection. This work presents a strategy to design peptide sequences able to recognize the CD44 hyaluronic acid receptor present in the plasmalemma of a range of cells including human bone marrow stromal mesenchymal cells. The protocol of identification of the optimal amino acid sequence was based on the combination of rational design and in silico methodologies. This protocol led to the identification of two peptide sequences which were synthesized and tested on human bone marrow mesenchymal stromal cells (hBM-MSCs) for their ability to ensure specific binding to the CD44 receptor. Of the two peptides, one binds CD44 with sensitivity and selectivity, thus proving its potential to be used as a suitable alternative to this antibody in conventional immunostaining. In the context of regenerative medicine, the availability of this peptide could be harnessed to functionalize tissue engineering scaffolds to anchor stem cells as well as to be integrated into systems such as cell sorters to efficiently isolate MSCs from biological samples including various cell subpopulations. The data here reported can represent a model for developing peptide sequences able to recognize hBM-MSCs and other types of cells and for their integration in a range of biomedical applications.
- Published
- 2023
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