Fig. 5 Evolutionary and integrative perspective and definition of the scope of antibody mimetics
Notes: green, orange, and red ovals represent the assemblies of peptides, peptidomimetics, and ligands, respectively. Boxes are representatives of antibody-derived (deep green) and non-antibody derived (red) protein/peptides, nucleic acids and their mimics (cyan), as well as other components (purple) like ions, chemical molecules, and other developing structures. Antibody mimetics originally evolved from artificially manipulated antibodies, including antibody fragments and synthetic antibodies. Later, this term expanded and focused more on refining the existing parent structures from functional fragments to smaller, more stable, higher affinity, more reproducible and penetrable ones. For instance, natural peptides, peptidomimetics and ligands partially belong to the family of antibody mimetics. As antibody mimetic engineering evolved, different concepts and terminology emerged, but each may better reflect the state of research at that time. Retrospectively, some terms, such as synthetic antibody, are blurry. To certain extent, the term “antibody mimetics” also could not reflect the entire intension and extension of this dynamic concept as increasing non-antibody sourced and non-protein and peptide sourced structures have been introduced into this field. As highlighted by cyan and orange boxes in the figure, aptamer and other substances beyond the scope of biomolecules deserve consideration for inclusion in antibody mimetics repertoire. Therefore, further classification and definition of this field are urgently needed and expected. Here we propose the protein/peptide-based antibody mimetics as the core concept of this field.
Compared to traditional antibodies, the fourth generations of antibody engineering offer antibodies with a range of properties, providing much diverse formats such as small peptides, protein scaffolds, or synthetic polymers, for antibody design which allows for greater flexibility in their application. At the same time, they are smaller in size, which allows for better tissue penetration and target access (Jiang et al., 2009 ). They can be produced using simpler and more cost-effective methods, which enables mass production. Additionally, they have improved stability and can be engineered to have higher specificity and affinity for their target antigen. Through artificial modification and screening, antibody mimetics have demonstrated commendable attributes in comparison to traditional antibodies. These modifications may involve targeted alteration within antigen-binding sites or conjugation of specific proteins/peptides, thereby facilitating the development of more efficacious therapeutic or diagnostic reagents and expediting their market penetration. Such reagents were summarized in the Table 3, and here we only mentioned two compelling representatives. Qiu et al. , fused antibody mimetics with the bacterial toxin colicin Ia, resulting in the creation of “pheromonicins” that specifically inhibit tumor growth. it displayed superior tumor targeting and penetration capabilities surpassing those of their parent antibodies (Qiu et al., 2007 ). Similarly, Wold et al. synthesized antibody mimetics by site-specific binding of small molecules with high affinity and specificity for disease-associated antigens to Fc fragments, enabling to develope antibody-based drugs with enhanced efficacy (Wold et al., 2015 ). By harnessing the unique properties of antibody mimetics, such as their modifiability and specificity, they hold promise for bringing antibody-based drugs to the market. However, there are also some disadvantages to using mimetic antibodies. They may not have the same efficacy as traditional antibodies, particularly in complex biological systems. Additionally, their potential for off-target effects and toxicity may need to be carefully evaluated (Khatib & Salla, 2022 ). Moreover, the antibody mimetic engineering still requires sophisticated design and complicated biopanning process, which also lead to high cost and limits its application and commercialization. The potential for antibody mimetics to replace outdated or obsolete antibody drugs and revive their presence in the market is theoretically possible. However, it must be recognized that reintroducing an antibody taken from the market due to safety concerns entails multifaceted considerations. Safety issues may originate from various factors, encompassing adverse effects, lack of efficacy, or other complications. If the advancements of antibody mimetics could address the specific safety concerns or enable safer alternatives to withdrawn antibodies, it has the potential to usher in novel and improved therapeutic options. Nevertheless, each case requires an extensive reassessment of the safety profile, including careful evaluation, rigorous testing, and regulatory scrutiny to ensure the safety and efficacy of the developed antibody mimetic prior to its contemplation for reintroduction into the market. As depicted in Table 3, we present a summary of antibody mimetics drugs that have entered the clinic or are undergoing clinical validation.
Computational analysis has emerged as a promising strategy for accelerating the development of novel antibody mimetics, enhancing their capabilities while reducing the cost associated with traditional trial-and-error approaches (Kadonosono et al., 2020 ;Raybould et al., 2019 ). Notably, prominent computational methods such as RossettaAntibody and AntBo have been employed to achieve various purposes in this context. These methods enable to discern and characterize the crucial attributes of existing antibodies, including affinity, specificity, stability, and immunogenicity. Additionally, they facilitate the determination of key residues responsible for antigen binding. By harnessing computational analysis, it becomes possible to predict and propose modifications that can enhance binding affinity and specificity (Kuroda et al., 2012 ;Wang et al., 2021 ). Moreover, the integration of machine learning and deep sequencing techniques (Sloth et al., 2022 ) has proven to be efficient in the realm of biopanning and optimization of phage display technology (Fig. 6). These state-of-the-art methodologies provide valuable insights into the discovery and refinement of antibody mimetics.