Directed evolution of anti-HER2 DARPins by SNAP display reveals stability/function trade-offs in the selection process

Cell-Free Gene Expression: Methods and Applications

Cell-free gene expression (CFE) systems empower synthetic biologists to build biological molecules and processes outside of living intact cells. The foundational principle is that precise, complex biomolecular transformations can be conducted in purified enzyme or crude cell lysate systems. This concept circumvents mechanisms that have evolved to facilitate species survival, bypasses limitations on molecular transport across the cell wall, and provides a significant departure from traditional, cell-based processes that rely on microscopic cellular "reactors." In addition, cell-free systems are inherently distributable through freeze-drying, which allows simple distribution before rehydration at the point-of-use. Furthermore, as cell-free systems are nonliving, they provide built-in safeguards for biocontainment without the constraints attendant on genetically modified organisms. These features have led to a significant increase in the development and use of CFE systems over the past two decades. Here, we discuss recent advances in CFE systems and highlight how they are transforming efforts to build cells, control genetic networks, and manufacture biobased products.

Computational design of newly engineered DARPins as HER2 receptor inhibitors for breast cancer treatment

Background and purpose

Human epidermal growth factor receptor 2 (HER2) is overexpressed in approximately 25% of breast cancer patients; therefore, its inhibition is a therapeutic target in cancer treatment.

Experimental approach

In this study, two new variants of designed ankyrin repeat proteins (DARPins), designated EG3-1 and EG3-2, were designed to increase their affinity for HER2 receptors. To this end, DARPin G3 was selected as a template, and six-point mutations comprising Q26E, I32V, T49A, L53H, K101R, and G124V were created on its structure. Furthermore, the 3D structures were formed through homology modeling and evaluated using molecular dynamic simulation. Then, both structures were docked to the HER2 receptor using the HADDOCK web tool, followed by 100 ns of molecular dynamics simulation for both DARPins / HER2 complexes.

Findings/Results

The theoretical result confirmed both structures' stability. Molecular dynamics simulations reveal that the applied mutations on DARPin EG3-2 significantly improve the receptor binding affinity of DARPin.

Conclusion and implications

The computationally engineered DARPin EG3-2 in this study could provide a hit compound for the design of promising anticancer agents targeting HER2 receptors.

Engineering of conserved residues near antibody heavy chain complementary determining region 3 (HCDR3) improves both affinity and stability

Affinity and stability are crucial parameters in antibody development and engineering approaches. Although improvement in both metrics is desirable, trade-offs are almost unavoidable. Heavy chain complementarity determining region 3 (HCDR3) is the best-known region for antibody affinity but its impact on stability is often neglected. Here, we present a mutagenesis study of conserved residues near HCDR3 to elicit the role of this region in the affinity-stability trade-off. These key residues are positioned around the conserved salt bridge between VH-K94 and VH-D101 which is crucial for HCDR3 integrity. We show that the additional salt bridge at the stem of HCDR3 (VH-K94:VH-D101:VH-D102) has an extensive impact on this loop's conformation, therefore simultaneous improvement in both affinity and stability. We find that the disruption of π-π stacking near HCDR3 (VH-Y100E:VL-Y49) at the VH-VL interface cause an irrecoverable loss in stability even if it improves the affinity. Molecular simulations of putative rescue mutants exhibit complex and often non-additive effects. We confirm that our experimental measurements agree with the molecular dynamic simulations providing detailed insights for the spatial orientation of HCDR3. VH-V102 right next to HCDR3 salt bridge might be an ideal candidate to overcome affinity-stability trade-off.

Engineered fast-dissociating antibody fragments for multiplexed super-resolution microscopy

Image reconstruction by integrating exchangeable single-molecule localization (IRIS) achieves multiplexed super-resolution imaging by high-density labeling with fast exchangeable fluorescent probes. However, previous methods to develop probes for individual targets required a great amount of time and effort. Here, we introduce a method for generating recombinant IRIS probes with a new mutagenesis strategy that can be widely applied to existing antibody sequences. Several conserved tyrosine residues at the base of complementarity-determining regions were identified as candidate sites for site-directed mutagenesis. With a high probability, mutations at candidate sites accelerated the off rate of recombinant antibody-based probes without compromising specific binding. We were able to develop IRIS probes from five monoclonal antibodies and three single-domain antibodies. We demonstrate multiplexed localization of endogenous proteins in primary neurons that visualizes small synaptic connections with high binding density. It is now practically feasible to generate fast-dissociating fluorescent probes for multitarget super-resolution imaging.

The production of the first functional antibody mimetic in higher plants: the chloroplast makes the DARPin G3 for HER2 imaging in oncology

Background

Designed mimetic molecules are attractive tools in biopharmaceuticals and synthetic biology. They require mass and functional production for the assessment of upcoming challenges in the near future. The DARPin family is considered a mimetic pharmaceutical peptide group with high affinity binding to specific targets. DARPin G3 is designed to bind to the HER2 (human epidermal growth factor receptor 2) tyrosine kinase receptor. Overexpression of HER2 is common in some cancers, including breast cancer, and can be used as a prognostic and predictive tool for cancer. The chloroplasts are cost-effective alternatives, equal to, and sometimes better than, bacterial, yeast, or mammalian expression systems. This research examined the possibility of the production of the first antibody mimetic, DARPin G3, in tobacco chloroplasts for HER2 imaging in oncology.

Results

The chloroplast specific DARPin G3 expression cassette was constructed and transformed into N. tabacum chloroplasts. PCR and Southern blot analysis confirmed integration of transgenes as well as chloroplastic and cellular homoplasmy. The Western blot analysis and ELISA confirmed the production of DARPin G3 at the commercial scale and high dose with the rate of 20.2% in leaf TSP and 33.7% in chloroplast TSP. The functional analysis by ELISA confirmed the binding of IMAC purified chloroplast-made DARPin G3 to the extracellular domain of the HER2 receptor with highly effective picomolar affinities. The carcinoma cellular studies by flow cytometry and immunofluorescence microscopy confirmed the correct functioning by the specific binding of the chloroplast-made DARPin G3 to the HER2 receptor on the surface of HER2-positive cancer cell lines.

Conclusion

The efficient functional bioactive production of DARPin G3 in chloroplasts led us to introduce plant chloroplasts as the site of efficient production of the first antibody mimetic molecules. This report, as the first case of the cost-effective production of mimetic molecules, enables researchers in pharmaceuticals, synthetic biology, and bio-molecular engineering to develop tool boxes by producing new molecular substitutes for diverse purposes.

Co-optimization of therapeutic antibody affinity and specificity using machine learning models that generalize to novel mutational space

Therapeutic antibody development requires selection and engineering of molecules with high affinity and other drug-like biophysical properties. Co-optimization of multiple antibody properties remains a difficult and time-consuming process that impedes drug development. Here we evaluate the use of machine learning to simplify antibody co-optimization for a clinical-stage antibody (emibetuzumab) that displays high levels of both on-target (antigen) and off-target (non-specific) binding. We mutate sites in the antibody complementarity-determining regions, sort the antibody libraries for high and low levels of affinity and non-specific binding, and deep sequence the enriched libraries. Interestingly, machine learning models trained on datasets with binary labels enable predictions of continuous metrics that are strongly correlated with antibody affinity and non-specific binding. These models illustrate strong tradeoffs between these two properties, as increases in affinity along the co-optimal (Pareto) frontier require progressive reductions in specificity. Notably, models trained with deep learning features enable prediction of novel antibody mutations that co-optimize affinity and specificity beyond what is possible for the original antibody library. These findings demonstrate the power of machine learning models to greatly expand the exploration of novel antibody sequence space and accelerate the development of highly potent, drug-like antibodies.

The Effect of Mutations in the TPR and Ankyrin Families of Alpha Solenoid Repeat Proteins

Protein repeats are short, highly similar peptide motifs that occur several times within a single protein, for example the TPR and Ankyrin repeats. Understanding the role of mutation in these proteins is complicated by the competing facts that 1) the repeats are much more restricted to a set sequence than non-repeat proteins, so mutations should be harmful much more often because there are more residues that are heavily restricted due to the need of the sequence to repeat and 2) the symmetry of the repeats in allows the distribution of functional contributions over a number of residues so that sometimes no specific site is singularly responsible for function (unlike enzymatic active site catalytic residues). To address this issue, we review the effects of mutations in a number of natural repeat proteins from the tetratricopeptide and Ankyrin repeat families. We find that mutations are context dependent. Some mutations are indeed highly disruptive to the function of the protein repeats while mutations in identical positions in other repeats in the same protein have little to no effect on structure or function.

Recent developments in engineering protein-protein interactions using phage display

Targeted inhibition of misregulated protein-protein interactions (PPIs) has been a promising area of investigation in drug discovery and development for human diseases. However, many constraints remain, including shallow binding surfaces and dynamic conformation changes upon interaction. A particularly challenging aspect is the undesirable off-target effects caused by inherent structural similarity among the protein families. To tackle this problem, phage display has been used to engineer PPIs for high-specificity binders with improved binding affinity and greatly reduced undesirable interactions with closely related proteins. Although general steps of phage display are standardized, library design is highly variable depending on experimental contexts. Here in this review, we examined recent advances in the structure-based combinatorial library design and the advantages and limitations of different approaches. The strategies described here can be explored for other protein-protein interactions and aid in designing new libraries or improving on previous libraries.

Discovery-stage identification of drug-like antibodies using emerging experimental and computational methods

There is intense and widespread interest in developing monoclonal antibodies as therapeutic agents to treat diverse human disorders. During early-stage antibody discovery, hundreds to thousands of lead candidates are identified, and those that lack optimal physical and chemical properties must be deselected as early as possible to avoid problems later in drug development. It is particularly challenging to characterize such properties for large numbers of candidates with the low antibody quantities, concentrations, and purities that are available at the discovery stage, and to predict concentrated antibody properties (e.g., solubility, viscosity) required for efficient formulation, delivery, and efficacy. Here we review key recent advances in developing and implementing high-throughput methods for identifying antibodies with desirable in vitro and in vivo properties, including favorable antibody stability, specificity, solubility, pharmacokinetics, and immunogenicity profiles, that together encompass overall drug developability. In particular, we highlight impressive recent progress in developing computational methods for improving rational antibody design and prediction of drug-like behaviors that hold great promise for reducing the amount of required experimentation. We also discuss outstanding challenges that will need to be addressed in the future to fully realize the great potential of using such analysis for minimizing development times and improving the success rate of antibody candidates in the clinic.

Magnetic particles used in a new approach for designed protein crystallization

Designed protein crystallization using magnetic particles as additives in the crystallization of model case studies.

In vitro evolution of antibody affinity via insertional scanning mutagenesis of an entire antibody variable region

We report a systematic combinatorial exploration of affinity enhancement of antibodies by insertions and deletions (InDels). Transposon-based introduction of InDels via the method TRIAD (transposition-based random insertion and deletion mutagenesis) was used to generate large libraries with random in-frame InDels across the entire single-chain variable fragment gene that were further recombined and screened by ribosome display. Knowledge of potential insertion points from TRIAD libraries formed the basis of exploration of length and sequence diversity of novel insertions by insertional-scanning mutagenesis (InScaM). An overall 256-fold affinity improvement of an anti-IL-13 antibody BAK1 as a result of InDel mutagenesis and combination with known point mutations validates this approach, and suggests that the results of this InDel mutagenesis and conventional exploration of point mutations can synergize to generate antibodies with higher affinity.

Split & mix assembly of DNA libraries for ultrahigh throughput on-bead screening of functional proteins

Site-saturation libraries reduce protein screening effort in directed evolution campaigns by focusing on a limited number of rationally chosen residues. However, uneven library synthesis efficiency leads to amino acid bias, remedied at high cost by expensive custom synthesis of oligonucleotides, or through use of proprietary library synthesis platforms. To address these shortcomings, we have devised a method where DNA libraries are constructed on the surface of microbeads by ligating dsDNA fragments onto growing, surface-immobilised DNA, in iterative split-and-mix cycles. This method-termed SpliMLiB for Split-and-Mix Library on Beads-was applied towards the directed evolution of an anti-IgE Affibody (ZIgE), generating a 160,000-membered, 4-site, saturation library on the surface of 8 million monoclonal beads. Deep sequencing confirmed excellent library balance (5.1% ± 0.77 per amino acid) and coverage (99.3%). As SpliMLiB beads are monoclonal, they were amenable to direct functional screening in water-in-oil emulsion droplets with cell-free expression. A FACS-based sorting of the library beads allowed recovery of hits improved in Kd over wild-type ZIgE by up to 3.5-fold, while a consensus mutant of the best hits provided a 10-fold improvement. With SpliMLiB, directed evolution workflows are accelerated by integrating high-quality DNA library generation with an ultra-high throughput protein screening platform.

Directed evolution methods for overcoming trade-offs between protein activity and stability

Engineered proteins are being widely developed and employed in applications ranging from enzyme catalysts to therapeutic antibodies. Directed evolution, an iterative experimental process composed of mutagenesis and library screening, is a powerful technique for enhancing existing protein activities and generating entirely new ones not observed in nature. However, the process of accumulating mutations for enhanced protein activity requires chemical and structural changes that are often destabilizing, and low protein stability is a significant barrier to achieving large enhancements in activity during multiple rounds of directed evolution. Here we highlight advances in understanding the origins of protein activity/stability trade-offs for two important classes of proteins (enzymes and antibodies) as well as innovative experimental and computational methods for overcoming such trade-offs. These advances hold great potential for improving the generation of highly active and stable proteins that are needed to address key challenges related to human health, energy and the environment.

Engineering repeat proteins of the immune system

Limitations associated with immunoglobulins have motivated the search for novel binding scaffolds. Repeat proteins have emerged as one promising class of scaffolds, but often are limited to binding protein and peptide targets. An exception is the repeat proteins of the immune system, which have in recent years served as an inspiration for binding scaffolds which can bind glycans and other classes of biomolecule. Like other repeat proteins, these proteins can be very stable and have a monomeric mode of binding, with elongated and highly variable binding surfaces. The ability to target glycans and glycoproteins fill an important gap in current tools for research and biomedical applications.

Alternative scaffolds in radionuclide diagnosis of malignancies

This review discusses a relatively new class of targeted molecules that is being actively studied for radionuclide diagnosis and treatment of malignancies. The full-size antibodies used so far have non-optimal pharmacological properties, slow distribution in the body, poor penetration into the tissue and kidney excretion, and high immunogenicity, which significantly complicates their use in clinical practice. Over the past decade, a new class of targeted molecules, called “non-immunoglobulin scaffolds” have become popular; they have all the requirements for optimal delivery of a radionuclide to tumor cells. Scaffolds usually are smaller in size in comparison with antibodies, but they are larger than peptides, and are characterized by high affinity and optimal biochemical, biophysical, biological, and economic features. The advantages of such proteins are their stable structure, good penetration into tissues, the possibility of additional functionalization and expression in the bacterial system, which ensures low production costs.

The results of preclinical and clinical studies for diagnosis of malignancies using such proteins as affibody, adnectin, DARPins, etc., have demonstrated their high specificity, affinity, good tolerance and low immunogenicity. 

Data-driven engineering of protein therapeutics

Protein therapeutics requires a series of properties beyond biochemical activity, including serum stability, low immunogenicity, and manufacturability. Mutations that improve one property often decrease one or more of the other essential requirements for therapeutic efficacy, making the protein engineering challenge difficult. The past decade has seen an explosion of new techniques centered around cheaply reading and writing DNA. This review highlights the recent use of such high throughput technologies for engineering protein therapeutics. Examples include the use of human antibody repertoire sequence data to pair antibody heavy and light chains, comprehensive mutational analysis for engineering antibody specificity, and the use of ancestral and inter-species sequence data to engineer simultaneous improvements in enzyme catalytic efficiency and stability. We conclude with a perspective on further ways to integrate mature protein engineering pipelines with the exponential increases in the volume of sequencing data expected in the forthcoming decade.

High-throughput screening of biomolecules using cell-free gene expression systems

The incorporation of cell-free transcription and translation systems into high-throughput screening applications enables the in situ and on-demand expression of peptides and proteins. Coupled with modern microfluidic technology, the cell-free methods allow the screening, directed evolution and selection of desired biomolecules in minimal volumes within a short timescale. Cell-free high-throughput screening applications are classified broadly into in vitro display and on-chip technologies. In this review, we outline the development of cell-free high-throughput screening methods. We further discuss operating principles and representative applications of each screening method. The cell-free high-throughput screening methods may be advanced by the future development of new cell-free systems, miniaturization approaches, and automation technologies.

Understanding and overcoming trade-offs between antibody affinity, specificity, stability and solubility

The widespread use of monoclonal antibodies for therapeutic applications has led to intense interest in optimizing several of their natural properties (affinity, specificity, stability, solubility and effector functions) as well as introducing non-natural activities (bispecificity and cytotoxicity mediated by conjugated drugs). A common challenge during antibody optimization is that improvements in one property (e.g., affinity) can lead to deficits in other properties (e.g., stability). Here we review recent advances in understanding trade-offs between different antibody properties, including affinity, specificity, stability and solubility. We also review new approaches for co-optimizing multiple antibody properties and discuss how these methods can be used to rapidly and systematically generate antibodies for a wide range of applications.

Advances in the Application of Designed Ankyrin Repeat Proteins (DARPins) as Research Tools and Protein Therapeutics

Nonimmunoglobulin scaffolds have been developed to overcome the limitations of monoclonal antibodies with regard to stability and size. Of these scaffolds, the class of designed ankyrin repeat proteins (DARPins) has advanced the most in biochemical and biomedical applications. This review focuses on the recent progress in DARPin technology, highlighting the scaffold's potential and possibilities.

Arginine mutations in antibody complementarity-determining regions display context-dependent affinity/specificity trade-offs

Antibodies commonly accumulate charged mutations in their complementarity-determining regions (CDRs) during affinity maturation to enhance electrostatic interactions. However, charged mutations can mediate non-specific interactions, and it is unclear to what extent CDRs can accumulate charged residues to increase antibody affinity without compromising specificity. This is especially concerning for positively charged CDR mutations that are linked to antibody polyspecificity. To better understand antibody affinity/specificity trade-offs, we have selected single-chain antibody fragments specific for the negatively charged and hydrophobic Alzheimer's amyloid β peptide using weak and stringent selections for antibody specificity. Antibody variants isolated using weak selections for specificity were enriched in arginine CDR mutations and displayed low specificity. Alanine-scanning mutagenesis revealed that the affinities of these antibodies were strongly dependent on their arginine mutations. Antibody variants isolated using stringent selections for specificity were also enriched in arginine CDR mutations, but these antibodies possessed significant improvements in specificity. Importantly, the affinities of the most specific antibodies were much less dependent on their arginine mutations, suggesting that over-reliance on arginine for affinity leads to reduced specificity. Structural modeling and molecular simulations reveal unique hydrophobic environments near the arginine CDR mutations. The more specific antibodies contained arginine mutations in the most hydrophobic portions of the CDRs, whereas the less specific antibodies contained arginine mutations in more hydrophilic regions. These findings demonstrate that arginine mutations in antibody CDRs display context-dependent impacts on specificity and that affinity/specificity trade-offs are governed by the relative contribution of arginine CDR residues to the overall antibody affinity.

Efficient affinity maturation of antibody variable domains requires co-selection of compensatory mutations to maintain thermodynamic stability

The ability of antibodies to accumulate affinity-enhancing mutations in their complementarity-determining regions (CDRs) without compromising thermodynamic stability is critical to their natural function. However, it is unclear if affinity mutations in the hypervariable CDRs generally impact antibody stability and to what extent additional compensatory mutations are required to maintain stability during affinity maturation. Here we have experimentally and computationally evaluated the functional contributions of mutations acquired by a human variable (V_H) domain that was evolved using strong selections for enhanced stability and affinity for the Alzheimer’s Aβ42 peptide. Interestingly, half of the key affinity mutations in the CDRs were destabilizing. Moreover, the destabilizing effects of these mutations were compensated for by a subset of the affinity mutations that were also stabilizing. Our findings demonstrate that the accumulation of both affinity and stability mutations is necessary to maintain thermodynamic stability during extensive mutagenesis and affinity maturation in vitro, which is similar to findings for natural antibodies that are subjected to somatic hypermutation in vivo. These findings for diverse antibodies and antibody fragments specific for unrelated antigens suggest that the formation of the antigen-binding site is generally a destabilizing process and that co-enrichment for compensatory mutations is critical for maintaining thermodynamic stability.

A Shorter Route to Antibody Binders via Quantitative in vitro Bead-Display Screening and Consensus Analysis

Affinity panning of large libraries is a powerful tool to identify protein binders. However, panning rounds are followed by the tedious re-screening of the clones obtained to evaluate binders precisely. In a first application of Bead Surface Display (BeSD) we show successful in vitro affinity selections based on flow cytometric analysis that allows fine quantitative discrimination between binders. Subsequent consensus analysis of the resulting sequences enables identification of clones that bind tighter than those arising directly from the experimental selection output. This is demonstrated by evolution of an anti-Fas receptor single-chain variable fragment (scFv) that was improved 98-fold vs the parental clone. Four rounds of quantitative screening by fluorescence-activated cell sorting of an error-prone library based on fine discrimination between binders in BeSD were followed by analysis of 200 full-length output sequences that suggested a new consensus design with a K_d ∼140 pM. This approach shortens the time and effort to obtain high affinity reagents and its cell-free nature transcends limitations inherent in previous in vivo display systems.

Co-evolution of affinity and stability of grafted amyloid-motif domain antibodies

An attractive approach for designing lead antibody candidates is to mimic natural protein interactions by grafting peptide recognition motifs into the complementarity-determining regions (CDRs). We are using this approach to generate single-domain (VH) antibodies specific for amyloid-forming proteins such as the Alzheimer's Aβ peptide. Here, we use random mutagenesis and yeast surface display to improve the binding affinity of a lead VH domain grafted with Aβ residues 33-42 in CDR3. Interestingly, co-selection for improved Aβ binding and VH display on the surface of yeast yields antibody domains with improved affinity and reduced stability. The highest affinity VH domains were strongly destabilized on the surface of yeast as well as unfolded when isolated as autonomous domains. In contrast, stable VH domains with improved affinity were reliably identified using yeast surface display by replacing the display antibody that recognizes a linear epitope tag at the terminus of both folded and unfolded VH domains with a conformational ligand (Protein A) that recognizes a discontinuous epitope on the framework of folded VH domains. Importantly, we find that selection for improved stability using Protein A without simultaneous co-selection for improved Aβ binding leads to strong enrichment for stabilizing mutations that reduce antigen binding. Our findings highlight the importance of simultaneously optimizing affinity and stability to improve the rapid isolation of well-folded and specific antibody fragments.