Abstract
Immune-checkpoint receptors are a set of signal transduction proteins that can stimulate or inhibit specific anti-tumor responses. It is well established that cancer cells interact with different immune checkpoints to shut down T-cell response, thereby enabling cancer proliferation. Given the importance of immune checkpoint receptors, a structure-function analysis of these systems is imperative. However, recombinant expression and purification of these membrane originated proteins is still a challenge. Therefore, many attempts are being made to improve their expression and solubility while preserving their biological relevance. For this purpose, we designed an E. coli-based optimization system that enables the acquisition of mutations that increases protein solubility and affinity towards its native ligand, while maintaining biological activity. Here we focused on the well-characterized extracellular domain of the 'programmed cell death protein 1' (PD1), an immune checkpoint receptor known to inhibit T-cell proliferation by interacting with its ligands PD-L1 and PD-L2. The simple ELISA-based screening system shown here enabled the identification of high-affinity, highly soluble, functional variants derived from the extracellular domain of human PD1. The system was based on the expression of a GST-tagged variants library in E. coli, which enabled the selection of improved PD1 variants after a single optimization round. Within only two screening rounds, the most active variant showed a 5-fold higher affinity and 2.4-fold enhanced cellular activity as compared to the wild type protein. This scheme can be translated toward other types of challenging receptors toward development of research tools or alternative therapeutics.
| Original language | English |
|---|---|
| Pages (from-to) | 731-738 |
| Number of pages | 8 |
| Journal | Biochemical and Biophysical Research Communications |
| Volume | 506 |
| Issue number | 3 |
| DOIs | |
| State | Published - 30 Nov 2018 |
| Externally published | Yes |
Keywords
- Directed evolution
- E. coli-based ELISA
- PD1:PD-L1 interaction
- Protein optimization
- Soluble receptors
All Science Journal Classification (ASJC) codes
- Biophysics
- Biochemistry
- Molecular Biology
- Cell Biology