Section 10 of 11
Challenge and future prospective
Zhafira Fauziah, Robeth Viktoria Manurung, Yuspian Nur, Dika Apriliana Wulandari, Salma Nur Zakiyyah, Irkham, and Yeni Wahyuni Hartati · about 3 minutes
Although significant progress has been made in developing electrochemical biosensors based on affibody molecules, several fundamental challenges remain before this technology can be widely implemented in clinical settings. Affibody has lower production efficiency than other synthetic bioreceptors. Processes such as SPPS and expression engineering in conventional E. coli systems still require specialized chemicals, multistep processing and lengthy optimization times. Furthermore, phage display methods require large, complex phage libraries and the selection of highly hydrophobic affibodies can compromise stability and specificity. Another limitation is that affibodies displayed on the phage surface do not always retain the same properties as recombinant proteins, leading to differences in affinity and specificity in practical assays. Therefore, strategies are needed to make affibody synthesis more affordable, efficient and scalable.
One promising solution is the use of low-cost microbial expression systems such as E. coli strain BL21(DE3) or Lactococcus lactis combined with auto-induction medium techniques. This technique eliminates the need for manual induction control and reduces production costs by up to 40 %. Furthermore, the application of cell-free protein synthesis (CFPS) is a promising new trend because it enables rapid affibody production (within hours), without the need for cell culture. This technology is well-suited for on-demand or custom-made affibody production, for example, to detect rapidly emerging new targets such as new virus variants. Research by Lindgren et al. [77] showed that optimizing SPPS using microwave-assisted synthesis can reduce synthesis time by up to 60 % without compromising yield. Meanwhile, Wagner et al. [92] reported the efficient and economical production of affibody through an E. coli lysate-based cell-free synthesis system, yielding functional protein in less than 2 hours. However, the affibody synthesis process had some drawbacks. The phage display method required a large and complex phage library. In addition, selecting highly hydrophobic affibodies could affect stability and specificity. Another limitation was that the affibody displayed on the phage surface did not always retain the same properties as the recombinant protein, potentially leading to differences in affinity and specificity in practical assays.
From a molecular design perspective, miniaturizing binding domains is also an important strategy. By performing in silico design and molecular docking simulations, the binding time of affibodies can be optimized for shorter periods, thus reducing raw material costs and synthesis time.
Furthermore, integration with automated bioconjugation and synthetic microreactors enables parallel synthesis at a microscale (microfluidics-assisted peptide synthesis). This approach can accelerate the synthesis process, avoid wasting time and save expensive solvents and reagents, such as coupling agents (e.g. HATU or DIC).
Green chemistry approaches are also beginning to be implemented, for example, replacing toxic organic solvents (DMF, DCM) with environmentally friendly solvents such as deep eutectic solvents (DES) or water-ethanol, thus not only reducing waste costs but also increasing the downtime of the synthesis process.
The integration of affibody into microfluidic chips and portable biosensors is also an important direction for developing rapid, user-friendly POC systems. This combination also enables the integration of multiple functions in a single device, such as sample processing, separation, target recognition and signal reading, simultaneously, forming an integrated diagnostic system based on a lab-on-a-chip.
Meanwhile, in real-world applications, affibody often suffers from nonspecific binding to other proteins or matrices, which reduces the signal-to-noise ratio. Therefore, improving specificity is challenging. Computational approaches, including in silico protein design and structural simulations, can accelerate the selection of mutations that improve the constellation of interactions at the binding site without compromising molecular stability.