Bibliographic Details
| Title: |
Identification of a potent PCNA‐p15‐interaction inhibitor by autodisplay‐based peptide library screening |
| Authors: |
Sarah Hardebeck, Natalie Jácobo Goebbels, Caroline Michalski, Sebastian Schreiber, Joachim Jose |
| Source: |
Microbial Biotechnology, Vol 17, Iss 4, Pp n/a-n/a (2024) |
| Publisher Information: |
Wiley, 2024. |
| Publication Year: |
2024 |
| Collection: |
LCC:Biotechnology |
| Subject Terms: |
Biotechnology, TP248.13-248.65 |
| More Details: |
Abstract Proliferating cell nuclear antigen (PCNA) is an essential factor for DNA metabolism. The influence of PCNA on DNA replication and repair, combined with the high expression rate of PCNA in various tumours renders PCNA a promising target for cancer therapy. In this context, an autodisplay‐based screening method was developed to identify peptidic PCNA interaction inhibitors. A 12‐mer randomized peptide library consisting of 2.54 × 106 colony‐forming units was constructed and displayed at the surface of Escherichia coli BL21 (DE3) cells by autodisplay. Cells exhibiting an enhanced binding to fluorescent mScarlet‐I‐PCNA were enriched in four sorting rounds by flow cytometry. This led to the discovery of five peptide variants with affinity to mScarlet‐I‐PCNA. Among these, P3 (TCPLRWITHDHP) exhibited the highest binding signal. Subsequent flow cytometric analysis revealed a dissociation constant of 0.62 μM for PCNA‐P3 interaction. Furthermore, the inhibition of PCNA interactions was investigated using p15, a PIP‐box containing protein involved in DNA replication and repair. P3 inhibited the PCNA‐p1551‐70 interaction with a half maximal inhibitory activity of 16.2 μM, characterizing P3 as a potent inhibitor of the PCNA‐p15 interaction. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
1751-7915 |
| Relation: |
https://doaj.org/toc/1751-7915 |
| DOI: |
10.1111/1751-7915.14471 |
| Access URL: |
https://doaj.org/article/751b1cc78de646c393f0c5afc8348859 |
| Accession Number: |
edsdoj.751b1cc78de646c393f0c5afc8348859 |
| Database: |
Directory of Open Access Journals |
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