Global Protein Stability
Rx Biosciences offers global protein stability services using yeast surface display technology. This advanced method enables researchers to efficiently analyze and enhance the stability of large protein sets. To begin, scientists design peptide sequences in silico. Then, they synthesize the genes, clone them into the pRxYD 3.0 yeast display vector, and finally express them on the surface of yeast cells.
Next, the peptides face exposure to various instability agents, including trypsin, chymotrypsin, temperature fluctuations, pH shifts, and chemicals like urea and guanidinium hydrochloride. Through this process, high-throughput screening effectively identifies protein variants that show enhanced stability across a wide protein range in a single experiment.
Using yeast display, our team actively identifies stable variants and engineers them for improved performance. As a result, these proteins exhibit superior functional properties, making them ideal for therapeutic antibody development, industrial enzyme production, and other advanced biotechnological applications.
Service Highlights
- Optimized yeast display vector.
- High-throughput screening.
- Eukaryotic environment.
- Direct analysis on cell surface.
- Highly applicable in protein engineering.
- All services under one roof.
Experimental Steps
(A) Each yeast cell displays multiple copies of a test protein fused to Aga2. A fluorescent antibody labels the C-terminal c-Myc tag. When a protease or another agent cleaves the protein, the tag detaches, which causes a drop in fluorescence.
(B) Libraries containing 10⁴ unique sequences undergo sorting through flow cytometry. Before proteolysis, most cells exhibit high fluorescence, indicating strong protein expression (blue). However, after treatment, only a few cells retain fluorescence. Therefore, cells that remain above the fluorescence threshold (shaded green area) are selected for deep sequencing.
(C) Sequential sorting at increasing protease concentrations helps separate proteins based on their stability. Each sequence from a library of 19,726 proteins appears as a gray line that tracks how its population fraction (enrichment) changes, normalized to its starting level in the pre-selection library. Additionally, the enrichment patterns of seven proteins with varying stability are highlighted in color.
(D) Next, EC50 values for the seven highlighted proteins in (C) are plotted alongside the full distribution of the 46,187 highest-confidence EC50 measurements from design rounds 1 to 4.
(E) Finally, the same data is shown again, but now it compares corrected stability scores (EC50 values adjusted for intrinsic proteolysis rates). These corrected scores demonstrate a stronger correlation between proteases than the raw EC50 values.
(F–I) High-throughput stability scores correspond well with individual folding stability measurements for mutants of four small proteins. In each case, the wild-type sequence is marked by a red circle. Specifically,
(F) shows Pin1 ΔG_unf measured at 40°C using thermal denaturation,
(G) presents hYAP65 melting temperature (Tm) data,
(H) displays Villin HP35 ΔG_unf at 25°C from urea denaturation, and
(I) illustrates BBL ΔG_unf at 10°C via thermal denaturation (Science, 2017, 357(6347):168–175).
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