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.