Directing evolution of novel ligands by mRNA display

mRNA Display Pipeline for Protein Biosensor Construction

Despite the significant potential of protein biosensors, their construction remains a trial-and-error process. The most obvious approach for addressing this is to utilize modular biosensor architectures where specificity-conferring modalities can be readily generated to recognize new targets. Toward this goal, we established a workflow that uses mRNA display-based selection of hyper-stable monobody domains for the target of choice or ribosome display to select equally stable DARPins. These binders were integrated into a two-component allosteric biosensor architecture based on a calmodulin-reporter chimera. This workflow was tested by developing biosensors for liver toxicity markers such as cytosolic aspartate aminotransferase, mitochondrial aspartate aminotransferase, and alanine aminotransferase 1. We demonstrate that our pipeline consistently produced >103 unique binders for each target within a week. Our analysis revealed that the affinity of the binders for their targets was not a direct predictor of the binder's performance in a biosensor context. The interactions between the binding domains and the reporter module affect the biosensor activity and the dynamic range. We conclude that following binding domain selection, the multiplexed biosensor assembly and prototyping appear to be the most promising approach for identifying biosensors with the desired properties.

Strategies for the Construction of Multicyclic Phage Display Libraries

Peptide therapeutics have gained great interest due to their multiple advantages over small molecule and antibody-based drugs. Peptide drugs are easier to synthesize, have the potential for oral bioavailability, and are large enough to target protein-protein interactions that are undruggable by small molecules. However, two major limitations have made it difficult to develop novel peptide therapeutics not derived from natural products, including the metabolic instability of peptides and the difficulty of reaching antibody-like potencies and specificities. Compared to linear and disulfide-monocyclized peptides, multicyclic peptides can provide increased conformational rigidity, enhanced metabolic stability, and higher potency in inhibiting protein-protein interactions. The identification of novel multicyclic peptide binders can be difficult, however, recent advancements in the construction of multicyclic phage libraries have greatly advanced the process of identifying novel multicyclic peptide binders for therapeutically relevant protein targets. This review will describe the current approaches used to create multicyclic peptide libraries, highlighting the novel chemistries developed and the proof-of-concept work done on validating these libraries against different protein targets.

Intelligent Biomaterialomics: Molecular Design, Manufacturing, and Biomedical Applications

Materialomics integrates experiment, theory, and computation in a high-throughput manner, and has changed the paradigm for the research and development of new functional materials. Recently, with the rapid development of high-throughput characterization and machine-learning technologies, the establishment of biomaterialomics that tackles complex physiological behaviors has become accessible. Breakthroughs in the clinical translation of nanoparticle-based therapeutics and vaccines have been observed. Herein, recent advances in biomaterials, including polymers, lipid-like materials, and peptides/proteins, discovered through high-throughput screening or machine learning-assisted methods, are summarized. The molecular design of structure-diversified libraries; high-throughput characterization, screening, and preparation; and, their applications in drug delivery and clinical translation are discussed in detail. Furthermore, the prospects and main challenges in future biomaterialomics and high-throughput screening development are highlighted.

Protein Grafting Techniques: From Peptide Epitopes to Lasso-Grafted Neobiologics

Protein engineering techniques have vastly expanded their domain of impact, notably following the success of antibodies. Likewise, smaller peptide therapeutics have carved an increasingly significant niche for themselves in the pharmaceutical landscape. The concept of grafting such peptides onto larger protein scaffolds, thus harvesting the advantages of both, has given rise to a variety of protein engineering strategies that are reviewed herein. We also describe our own "Lasso-Grafting" approach, which combines traditional grafting concepts with mRNA display to streamline the production of multiple grafted drug candidates for virtually any target.

Inhibition of protein-protein interactions using biodegradable depsipeptide nanoassemblies

Although peptides notoriously have poor intrinsic pharmacokinetic properties, it is well-known that nanostructures with excellent pharmacokinetic properties can be designed. Noticing that peptide inhibitors are generally nonpolar, here, we consolidate the peptide inhibitor targeting intracellular protein-protein interactions (PPIs) as an integral part of biodegradable self-assembled depsipeptide nanostructures (SdPNs). Because the peptide inhibitor has the dual role of PPI inhibition and self-assembly in this design, problems associated with the poor pharmacokinetics of peptides and encapsulation/entrapment processes can be overcome. Optimized SdPNs displayed better tumor targeting and PPI inhibition properties than the comparable small molecule inhibitor in vivo. Kinetics of PPI inhibition for SdPNs were gradual and controllable in contrast to the rapid inhibition kinetics of the small molecule. Because SdPN is modular, any appropriate peptide inhibitor can be incorporated into the platform without concern for the poor pharmacokinetic properties of the peptide.

Advances in screening, synthesis, modification, and biomedical applications of peptides and peptide aptamers

Peptides and peptide aptamers have emerged as promising molecules for a wide range of biomedical applications due to their unique properties and versatile functionalities. The screening strategies for identifying peptides and peptide aptamers with desired properties are discussed, including high-throughput screening, display screening technology, and in silico design approaches. The synthesis methods for the efficient production of peptides and peptide aptamers, such as solid-phase peptide synthesis and biosynthesis technology, are described, along with their advantages and limitations. Moreover, various modification techniques are explored to enhance the stability, specificity, and pharmacokinetic properties of peptides and peptide aptamers. This includes chemical modifications, enzymatic modifications, biomodifications, genetic engineering modifications, and physical modifications. Furthermore, the review highlights the diverse biomedical applications of peptides and peptide aptamers, including targeted drug delivery, diagnostics, and therapeutic. This review provides valuable insights into the advancements in screening, synthesis, modification, and biomedical applications of peptides and peptide aptamers. A comprehensive understanding of these aspects will aid researchers in the development of novel peptide-based therapeutics and diagnostic tools for various biomedical challenges.

Backbone N-methylation of peptides: Advances in synthesis and applications in pharmaceutical drug development

Peptide-based drugs have garnered considerable attention in recent years owing to their increasingly crucial role in the treatment of diverse diseases. However, the limited pharmacokinetic properties of peptides have hindered their full potential. One prominent strategy for enhancing the druggability of peptides is N-methylation, which involves the addition of a methyl group to the nitrogen atom of the peptide backbone. This modification significantly improves the stability, bioavailability, receptor binding affinity and selectivity of peptide drug candidates. In this review, we provide a comprehensive overview of the advancements in synthetic methods for N-methylated peptide synthesis, as well as the associated limitations. Moreover, we explore the versatile effects of N-methylation on various aspects of peptide properties. Furthermore, we emphasize the efforts dedicated to N-methylated peptide pharmaceuticals that have successfully obtained marketing approval.

A novel cyclic peptide library immobilized on gel-type beads focusing on rapid construction and characterization for comprehensive drug discovery

Medium sized molecules such as peptides and macrocycles have recently drawn much attention as potent sources of medicinal lead compounds, whereas the possibility of obtaining a practical drug from them remains limited. The present paper describes a concept of discovering novel medicinal targets or binding modes as well as lead compounds by the one-peptide-on-one-bead (OPOB) technology for comprehensive screening. The difficulty and problems in conventional drug discovery methods that generally deal with one predetermined target are considered. The building blocks used for the present libraries were selected based on previous results in development of peptidic drugs. Each constituent has the common structure of cyclic form prepared by disulfide of cysteinyl residues or thioether linkages, additionally a methionine residue was inserted for the site-specific rapid cleavage by cyanogen bromide to liberate the immobilized peptides allowing reliable characterization by MALDI-TOF-MS/MS without LC-purification. Thus, a high throughput construction method for cyclic peptide libraries as well as characterization of single bead are proposed for drug discovery.

Deep Learning-Driven Library Design for the De Novo Discovery of Bioactive Thiopeptides

Broad substrate tolerance of ribosomally synthesized and post-translationally modified peptide (RiPP) biosynthetic enzymes has allowed numerous strategies for RiPP engineering. However, despite relaxed specificities, exact substrate preferences of RiPP enzymes are often difficult to pinpoint. Thus, when designing combinatorial libraries of RiPP precursors, balancing the compound diversity with the substrate fitness can be challenging. Here, we employed a deep learning model to streamline the design of mRNA display libraries. Using an in vitro reconstituted thiopeptide biosynthesis platform, we performed mRNA display-based profiling of substrate fitness for the biosynthetic pathway involving five enzymes to train an accurate deep learning model. We then utilized the model to design optimal mRNA libraries and demonstrated their utility in affinity selections against IRAK4 kinase and the TLR10 cell surface receptor. The selections led to the discovery of potent thiopeptide ligands against both target proteins (KD up to 1.3 nM for the best compound against IRAK4 and 300 nM for TLR10). The IRAK4-targeting compounds also inhibited the kinase at single-digit μM concentrations in vitro, exhibited efficient internalization into HEK293H cells, and suppressed NF-kB-mediated signaling in cells. Altogether, the developed approach streamlines the discovery of pseudonatural RiPPs with de novo designed biological activities and favorable pharmacological properties.

Genetic Code Expansion and a Photo-Cross-Linking Reaction Facilitate Ribosome Display Selections for Identifying a Wide Range of Affinity Peptides

Cell-free molecular display techniques have been utilized to select various affinity peptides from peptide libraries. However, conventional techniques have difficulties associated with the translational termination through in-frame UAG stop codons and the amplification of non-specific peptides, which hinders the desirable selection of low-affinity peptides. To overcome these problems, we established a scheme for ribosome display selection of peptide epitopes bound to monoclonal antibodies and then applied genetic code expansion with synthetic X-tRNAUAG reprogramming of the UAG codons (X = Tyr, Trp, or p-benzoyl-l-phenylalanine (pBzo-Phe)) to the scheme. Based on the assessment of the efficiency of in vitro translation with X-tRNAUAG, we carried out ribosome display selection with genetic code expansion using Trp-tRNAUAG, and we verified that affinity peptides could be identified efficiently regardless of the presence of UAG codons in the peptide coding sequences. Additionally, after evaluating the photo-cross-linking reactions of pBzo-Phe-incorporated peptides, we performed ribosome display selection of low-affinity peptides in combination with genetic code expansion using pBzo-Phe-tRNAUAG and photo-irradiation. The results demonstrated that sub-micromolar low-affinity peptide epitopes could be identified through the formation of photo-induced covalent bonds with monoclonal antibodies. Thus, the developed ribosome display techniques could contribute to the promotion of diverse peptide-based research.

mRNA-activated DNAzyme nanoprobe for tumor cell precise imaging and gene therapy

A novel Au-nucleic acid nanoprobe, catalyzed by mRNA, has been developed for live cell imaging and precise treatment of tumor cells. This nanoprobe exhibits the remarkable ability to differentiate between tumor cells and normal cells through live cell mRNA imaging, while selectively inducing apoptosis in tumor cells.

Large-scale analysis of mRNA sequences localized near the start and amber codons and their impact on the diversity of mRNA display libraries

Extremely diverse libraries are essential for effectively selecting functional peptides or proteins, and mRNA display technology is a powerful tool for generating such libraries with over 1012-1013 diversity. Particularly, the protein-puromycin linker (PuL)/mRNA complex formation yield is determining for preparing the libraries. However, how mRNA sequences affect the complex formation yield remains unclear. To study the effects of N-terminal and C-terminal coding sequences on the complex formation yield, puromycin-attached mRNAs containing three random codons after the start codon (32768 sequences) or seven random bases next to the amber codon (6480 sequences) were translated. Enrichment scores were calculated by dividing the appearance rate of every sequence in protein-PuL/mRNA complexes by that in total mRNAs. The wide range of enrichment scores (0.09-2.10 for N-terminal and 0.30-4.23 for C-terminal coding sequences) indicated that the N-terminal and C-terminal coding sequences strongly affected the complex formation yield. Using C-terminal GGC-CGA-UAG-U sequences, which resulted in the highest enrichment scores, we constructed highly diverse libraries of monobodies and macrocyclic peptides. The present study provides insights into how mRNA sequences affect the protein/mRNA complex formation yield and will accelerate the identification of functional peptides and proteins involved in various biological processes and having therapeutic applications.

Synthesis of a Complex and Highly Potent PCSK9 Inhibitor

The solution-based gram-scale synthesis of complex and highly potent proprotein convertase subtilisin-like/kexin type 9 (PCSK9) inhibitor 1 is presented. Construction of Northern fragment 2, followed by stepwise installation of Eastern 3, Southern 4, and Western 5 fragments, provided macrocyclic precursor 19. This intermediate was cross-linked via an intramolecular azide-alkyne click reaction, which preceded macrolactamization to afford the core framework of compound 1. Finally, coupling with poly(ethylene glycol) side-chain-based 6 gave the PCSK9 inhibitor 1.

p-Chloropropynyl Phenylalanine, a Versatile Non-Canonical Amino Acid for Co-Translational Peptide Macrocyclization and Side Chain Diversification

Macrocyclization has proven to be a beneficial strategy to improve upon some of the disadvantages of peptides as therapeutics. Nevertheless, many peptide cyclization strategies are not compatible with in vitro display technologies like mRNA display. Here we describe the novel amino acid p-chloropropynyl phenylalanine (pCPF). pCPF is a substrate for a mutant phenylalanyl-tRNA synthetase and its introduction into peptides via in vitro translation leads to spontaneous peptide macrocyclization in the presence of peptides containing cysteine. Macrocyclization occurs efficiently with a wide variety of ring sizes. Moreover, pCPF can be reacted with thiols after charging onto tRNA, enabling the testing of diverse ncAAs in translation. The versatility of pCPF should facilitate downstream studies of translation and enable the creation of novel macrocyclic peptide libraries.

Using display technologies to identify macrocyclic peptide antibiotics

Antibiotic resistant bacterial infections are now a leading cause of global mortality. While drug resistance continues to spread, the clinical antibiotic pipeline has become bare. This discord has focused attention on developing new strategies for antimicrobial discovery. Natural macrocyclic peptide-based products have provided novel antibiotics and antibiotic scaffolds targeting several essential bacterial cell envelope processes, but discovery of such natural products remains a slow and inefficient process. Synthetic strategies employing peptide display technologies can quickly screen large libraries of macrocyclic sequences for specific target binding and general antibacterial potential providing alternative approaches for new antibiotic discovery. Here we review cell envelope processes that can be targeted with macrocyclic peptide therapeutics, outline important macrocyclic peptide display technologies, and discuss future strategies for both library design and screening.

Selection of target-binding proteins from the information of weakly enriched phage display libraries by deep sequencing and machine learning

Despite the advances in surface-display systems for directed evolution, variants with high affinity are not always enriched due to undesirable biases that increase target-unrelated variants during biopanning. Here, our goal was to design a library containing improved variants from the information of the "weakly enriched" library where functional variants were weakly enriched. Deep sequencing for the previous biopanning result, where no functional antibody mimetics were experimentally identified, revealed that weak enrichment was partly due to undesirable biases during phage infection and amplification steps. The clustering analysis of the deep sequencing data from appropriate steps revealed no distinct sequence patterns, but a Bayesian machine learning model trained with the selected deep sequencing data supplied nine clusters with distinct sequence patterns. Phage libraries were designed on the basis of the sequence patterns identified, and four improved variants with target-specific affinity (EC₅₀ = 80-277 nM) were identified by biopanning. The selection and use of deep sequencing data without undesirable bias enabled us to extract the information on prospective variants. In summary, the use of appropriate deep sequencing data and machine learning with the sequence data has the possibility of finding sequence space where functional variants are enriched.

Natural and Man-Made Cyclic Peptide-Based Antibiotics

In recent years, an increasing number of drug-resistant bacterial strains have been identified due to the abuse of antibiotics, which seriously threatens human and animal health. Antimicrobial peptides (AMPs) have become one of the most effective weapons to solve this problem. AMPs have little tendency to induce drug resistance and have outstanding antimicrobial effects. The study of AMPs, especially cyclic peptides, has become a hot topic. Among them, macrocyclic AMPs have received extensive attention. This mini-review discusses the structures and functions of the dominant cyclic natural and synthetic AMPs and provides a little outlook on the future direction of cyclic AMPs.

Thiophene-2,3-Dialdehyde Enables Chemoselective Cyclization on Unprotected Peptides, Proteins, and Phage Displayed Peptides

Ortho-phthalaldehyde has recently found wide potentials for protein bioconjugation and peptide cyclization. Herein, the second-generation dialdehyde-based peptide cyclization method is reported. The thiophene-2,3-dialdehyde (TDA) reacts specifically with the primary amine (from Lys side chain or peptide N-terminus) and thiol (from Cys side chain) within unprotected peptides to generate a highly stable thieno[2,3-c]pyrrole-bridged cyclic structure, while it does not react with primary amine alone. This reaction is carried out in the aqueous buffer and features tolerance of diverse functionalities, rapid and clean transformation, and operational simplicity. The features allow TDA to be used for protein stapling and phage displayed peptide cyclization.

Biomanufacturing Biotinylated Magnetic Nanomaterial via Construction and Fermentation of Genetically Engineered Magnetotactic Bacteria

Biosynthesis provides a critical way to deal with global sustainability issues and has recently drawn increased attention. However, modifying biosynthesized magnetic nanoparticles by extraction is challenging, limiting its applications. Magnetotactic bacteria (MTB) synthesize single-domain magnetite nanocrystals in their organelles, magnetosomes (BMPs), which are excellent biomaterials that can be biologically modified by genetic engineering. Therefore, this study successfully constructed in vivo biotinylated BMPs in the MTB Magnetospirillum gryphiswaldense by fusing biotin carboxyl carrier protein (BCCP) with membrane protein MamF of BMPs. The engineered strain (MSR−∆F−BF) grew well and synthesized small-sized (20 ± 4.5 nm) BMPs and were cultured in a 42 L fermenter; the yield (dry weight) of cells and BMPs reached 8.14 g/L and 134.44 mg/L, respectively, approximately three-fold more than previously reported engineered strains and BMPs. The genetically engineered BMPs (BMP−∆F−BF) were successfully linked with streptavidin or streptavidin-labelled horseradish peroxidase and displayed better storage stability compared with chemically constructed biotinylated BMPs. This study systematically demonstrated the biosynthesis of engineered magnetic nanoparticles, including its construction, characterization, and production and detection based on MTB. Our findings provide insights into biomanufacturing multiple functional magnetic nanomaterials.

Accurate Models of Substrate Preferences of Post-Translational Modification Enzymes from a Combination of mRNA Display and Deep Learning

Promiscuous post-translational modification (PTM) enzymes often display nonobvious substrate preferences by acting on diverse yet well-defined sets of peptides and/or proteins. Understanding of substrate fitness landscapes for PTM enzymes is important in many areas of contemporary science, including natural product biosynthesis, molecular biology, and biotechnology. Here, we report an integrated platform for accurate profiling of substrate preferences for PTM enzymes. The platform features (i) a combination of mRNA display with next-generation sequencing as an ultrahigh throughput technique for data acquisition and (ii) deep learning for data analysis. The high accuracy (>0.99 in each of two studies) of the resulting deep learning models enables comprehensive analysis of enzymatic substrate preferences. The models can quantify fitness across sequence space, map modification sites, and identify important amino acids in the substrate. To benchmark the platform, we performed profiling of a Ser dehydratase (LazBF) and a Cys/Ser cyclodehydratase (LazDEF), two enzymes from the lactazole biosynthesis pathway. In both studies, our results point to complex enzymatic preferences, which, particularly for LazBF, cannot be reduced to a set of simple rules. The ability of the constructed models to dissect such complexity suggests that the developed platform can facilitate a wider study of PTM enzymes.

Directed Evolution of PD-L1-Targeted Affibodies by mRNA Display

Therapeutic monoclonal antibodies directed against PD-L1 (e.g., atezolizumab) disrupt PD-L1:PD-1 signaling and reactivate exhausted cytotoxic T-cells in the tumor compartment. Although anti-PD-L1 antibodies are successful as immune checkpoint inhibitor (ICI) therapeutics, there is still a pressing need to develop high-affinity, low-molecular-weight ligands for molecular imaging and diagnostic applications. Affibodies are small polypeptides (∼60 amino acids) that provide a stable molecular scaffold from which to evolve high-affinity ligands. Despite its proven utility in the development of imaging probes, this scaffold has never been optimized for use in mRNA display, a powerful in vitro selection platform incorporating high library diversity, unnatural amino acids, and chemical modification. In this manuscript, we describe the selection of a PD-L1-binding affibody by mRNA display. Following randomization of the 13 amino acids that define the binding interface of the well-described Her2 affibody, the resulting library was selected against recombinant human PD-L1 (hPD-L1). After four rounds, the enriched library was split and selected against either hPD-L1 or the mouse ortholog (mPD-L1). The dual target selection resulted in the identification of a human/mouse cross-reactive PD-L1 affibody (M1) with low nanomolar affinity for both targets. The M1 affibody bound with similar affinity to mPD-L1 and hPD-L1 expressed on the cell surface and inhibited signaling through the PD-L1:PD-1 axis at low micromolar concentrations in a cell-based functional assay. In vivo optical imaging with M1-Cy5 in an immune-competent mouse model of lymphoma revealed significant tumor uptake relative to a Cy5-conjugated Her2 affibody.

mRNA-based therapeutics: powerful and versatile tools to combat diseases

The therapeutic use of messenger RNA (mRNA) has fueled great hope to combat a wide range of incurable diseases. Recent rapid advances in biotechnology and molecular medicine have enabled the production of almost any functional protein/peptide in the human body by introducing mRNA as a vaccine or therapeutic agent. This represents a rising precision medicine field with great promise for preventing and treating many intractable or genetic diseases. In addition, in vitro transcribed mRNA has achieved programmed production, which is more effective, faster in design and production, as well as more flexible and cost-effective than conventional approaches that may offer. Based on these extraordinary advantages, mRNA vaccines have the characteristics of the swiftest response to large-scale outbreaks of infectious diseases, such as the currently devastating pandemic COVID-19. It has always been the scientists’ desire to improve the stability, immunogenicity, translation efficiency, and delivery system to achieve efficient and safe delivery of mRNA. Excitingly, these scientific dreams have gradually been realized with the rapid, amazing achievements of molecular biology, RNA technology, vaccinology, and nanotechnology. In this review, we comprehensively describe mRNA-based therapeutics, including their principles, manufacture, application, effects, and shortcomings. We also highlight the importance of mRNA optimization and delivery systems in successful mRNA therapeutics and discuss the key challenges and opportunities in developing these tools into powerful and versatile tools to combat many genetic, infectious, cancer, and other refractory diseases.

Methods for the directed evolution of biomolecular interactions

Noncovalent interactions between biomolecules such as proteins and nucleic acids coordinate all cellular processes through changes in proximity. Tools that perturb these interactions are and will continue to be highly valuable for basic and translational scientific endeavors. By taking cues from natural systems, such as the adaptive immune system, we can design directed evolution platforms that can generate proteins that bind to biomolecules of interest. In recent years, the platforms used to direct the evolution of biomolecular binders have greatly expanded the range of types of interactions one can evolve. Herein, we review recent advances in methods to evolve protein-protein, protein-RNA, and protein-DNA interactions.

Next-Generation Molecular Discovery: From Bottom-Up In Vivo and In Vitro Approaches to In Silico Top-Down Approaches for Therapeutics Neogenesis

Protein and drug engineering comprises a major part of the medical and research industries, and yet approaches to discovering and understanding therapeutic molecular interactions in biological systems rely on trial and error. The general approach to molecular discovery involves screening large libraries of compounds, proteins, or antibodies, or in vivo antibody generation, which could be considered “bottom-up” approaches to therapeutic discovery. In these bottom-up approaches, a minimal amount is known about the therapeutics at the start of the process, but through meticulous and exhaustive laboratory work, the molecule is characterised in detail. In contrast, the advent of “big data” and access to extensive online databases and machine learning technologies offers promising new avenues to understanding molecular interactions. Artificial intelligence (AI) now has the potential to predict protein structure at an unprecedented accuracy using only the genetic sequence. This predictive approach to characterising molecular structure—when accompanied by high-quality experimental data for model training—has the capacity to invert the process of molecular discovery and characterisation. The process has potential to be transformed into a top-down approach, where new molecules can be designed directly based on the structure of a target and the desired function, rather than performing screening of large libraries of molecular variants. This paper will provide a brief evaluation of bottom-up approaches to discovering and characterising biological molecules and will discuss recent advances towards developing top-down approaches and the prospects of this.

Opportunities for expanding encoded chemical diversification and improving hit enrichment in mRNA-displayed peptide libraries

DNA‐encoded small‐molecule libraries and mRNA displayed peptide libraries both use numerically large pools of oligonucleotide‐tagged molecules to identify potential hits for protein targets. They differ dramatically, however, in the ‘drug‐likeness’ of the molecules that each can be used to discover. We give here an overview of the two techniques, comparing some advantages and disadvantages of each, and suggest areas where particularly mRNA display can benefit from adopting advances developed with DNA‐encoded small molecule libraries. We outline cases where chemical modification of the peptide library has already been used in mRNA display, and survey opportunities to expand this using examples from DNA‐encoded small molecule libraries. We also propose potential opportunities for encoding such reactions within the mRNA/cDNA tag of an mRNA‐displayed peptide library to allow a more diversity‐oriented approach to library modification. Finally, we outline alternate approaches for enriching target‐binding hits from a pooled and tagged library, and close by detailing several examples of how an adjusted mRNA‐display based approach could be used to discover new ‘drug‐like’ modified small peptides.

Protein Engineering: Advances in Phage Display for Basic Science and Medical Research

Functional Protein Engineering became the hallmark in biomolecule manipulation in the new millennium, building on and surpassing the underlying structural DNA manipulation and recombination techniques developed and employed in the last decades of 20th century. Because of their prominence in almost all biological processes, proteins represent extremely important targets for engineering enhanced or altered properties that can lead to improvements exploitable in healthcare, medicine, research, biotechnology, and industry. Synthetic protein structures and functions can now be designed on a computer and/or evolved using molecular display or directed evolution methods in the laboratory. This review will focus on the recent trends in protein engineering and the impact of this technology on recent progress in science, cancer- and immunotherapies, with the emphasis on the current achievements in basic protein research using synthetic antibody (sABs) produced by phage display pipeline in the Kossiakoff laboratory at the University of Chicago (KossLab). Finally, engineering of the highly specific binding modules, such as variants of Streptococcal protein G with ultra-high orthogonal affinity for natural and engineered antibody scaffolds, and their possible applications as a plug-and-play platform for research and immunotherapy will be described.