Abstract
Background: The selection of a suitable signal peptide that can direct recombinant proteins from the cytoplasm to the extracellular space is an important criterion affecting the production of recombinant proteins in Escherichia coli, a widely used host. Nanobodies are currently attracting the attention of scientists as antibody alternatives due to their specific properties and feasibility of production in E. coli.
Objective: CD44 nanobodies constitute a potent therapeutic agent that can block CD44/HA interaction in cancer and inflammatory diseases. This molecule may also function as a drug against cancer cells and has been produced previously in E. coli without a signal peptide sequence. The goal of this project was to find a suitable signal peptide to direct CD44 nanobody extracellular secretion in E. coli that will potentially lead to optimization of experimental methods and facilitate downstream steps such as purification.
Methods: We analyzed 40 E. coli derived signal peptides retrieved from the Signal Peptide database and selected the best candidate signal peptides according to relevant criteria including signal peptide probability, stability, and physicochemical features, which were evaluated using signalP software version 4.1 and the ProtParam tool, respectively.
Results: In this in silico study, suitable candidate signal peptide(s) for CD44 nanobody secretory expression were identified. CSGA, TRBC, YTFQ, NIKA, and DGAL were selected as appropriate signal peptides with acceptable D-scores, and appropriate physicochemical and structural properties. Following further analysis, TRBC was selected as the best signal peptide to direct CD44 nanobody expression to the extracellular space of E. coli.
Conclusion: The selected signal peptide, TRBC is the most suitable to promote high-level secretory production of CD44 nanobodies in E. coli and potentially will be useful for scaling up CD44 nanobody production in experimental research as well as in other CD44 nanobody applications. However, experimental work is needed to confirm the data.
Keywords: CD44, E. coli, in silico cloning, physicochemical properties, secretory production, SignalP software.
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