High-Throughput Ligand Discovery Reveals a Sitewise Gradient of Diversity in Broadly Evolved Hydrophilic Fibronectin Domains

Engineering Affibody Binders to Death Receptor 5 and Tumor Necrosis Factor Receptor 1 With Improved Stability

Protein developability is an important, yet often overlooked, aspect of protein discovery campaigns that is a key driver of utility. Recent advances have improved developability screening capacity, making it an increasingly viable option in early-stage discovery. Here, we engineered one component of developability, stability, of two affibody proteins-one that targets death receptor 5 and another that targets tumor necrosis factor receptor 1-previously evolved to bind receptor and non-competitively inhibit signaling via conformational modulation. Starting from an error-prone PCR library of each affibody, variants were screened via yeast surface display binder selections, including depletion of non-specific binders, followed by developability assessment using the on-yeast protease and yeast display level assays. Multiplex deep sequencing identified variants for further evaluation. Purified variants exhibited elevated stability-8°C to 14°C increase in Tm,app-with maintained 1-2 nM affinity for the TNFR1 affibody and 30-fold improvement in the DR5 affibody affinity to 0.8 nM.

Design, Construction, and Validation of a Yeast-Displayed Chemically Expanded Antibody Library

In vitro display technologies, exemplified by phage and yeast display, have emerged as powerful platforms for antibody discovery and engineering. However, the identification of antibodies that disrupt target functions beyond binding remains a challenge. In particular, there are very few strategies that support identification and engineering of either protein-based irreversible binders or inhibitory enzyme binders. Expanding the range of chemistries in antibody libraries has the potential to lead to efficient discovery of function-disrupting antibodies. In this work, we describe a yeast display-based platform for the discovery of chemically diversified antibodies. We constructed a billion-member antibody library, called the "Clickable CDR-H3 Library", that supports the presentation of a range of chemistries within antibody variable domains via noncanonical amino acid (ncAA) incorporation and subsequent bioorthogonal click chemistry conjugations. Use of a polyspecific orthogonal translation system enables introduction of chemical groups with various properties, including photoreactive, proximity-reactive, and click chemistry-enabled functional groups for library screening. We established conjugation conditions that facilitate modification of the full library, demonstrating the feasibility of sorting the full billion-member library in "protein-small molecule hybrid" format in future work. Here, we conducted initial library screens after introducing O-(2-bromoethyl)tyrosine (OBeY), a weakly electrophilic ncAA capable of undergoing proximity-induced crosslinking to a target. Enrichments against donkey IgG and protein tyrosine phosphatase 1B (PTP1B) each led to the identification of several OBeY-substituted clones that bind to the targets of interest. Flow cytometry analysis on the yeast surface confirmed higher retention of binding for OBeY-substituted clones compared to clones substituted with ncAAs lacking electrophilic side chains after denaturation. However, subsequent crosslinking experiments in solution with ncAA-substituted clones yielded inconclusive results, suggesting that weakly reactive OBeY side chain is not sufficient to drive robust crosslinking in the clones isolated here. Nonetheless, this work establishes a multimodal, chemically expanded antibody library and demonstrates the feasibility of conducting discovery campaigns in chemically expanded format. This versatile platform offers new opportunities for identifying and characterizing antibodies with properties beyond what is accessible with the canonical amino acids, potentially enabling discovery of new classes of reagents, diagnostics, and even therapeutic leads.

Molecular Determinants of Affinity and Isoform Selectivity in Protein─Small Molecule Hybrid Inhibitors of Carbonic Anhydrase

Multiple studies have demonstrated the benefit of engineering hybrid ligands that combine the unique benefits of small molecules and proteins or peptides. However, the molecular complexity of hybrid ligands generates a parameter space so large it cannot be exhaustively explored. We systematically evaluated the impact of one molecular design element, conjugation site, on the discovery of functional protein-small molecule hybrids (PriSMs). We utilized a library of yeast-displayed fibronectin domain variants with amino acid and loop length diversity in the paratope and a single cysteine at one of 18 possible conjugation sites. The protein variants were coupled with maleimide-functionalized acetazolamide and sorted via competitive flow cytometry to discover potent and selective inhibitors of three isoforms of carbonic anhydrase. Deep sequencing of the resultant populations of functional PriSMs revealed an isoform-dependent distribution of conjugation site preferences. The top PriSMs showed potency and selectivity gains up to 23- and 100-fold (in this case, for CA-II vs CA-XII, with a 43-fold selectivity gain for CA-II vs CA-IX) relative to PEG2-acetazolamide alone. The presented study expands our fundamental understanding of the role of conjugation site in PriSM function and informs future PriSM engineering efforts by highlighting the benefit of conjugation site diversity in PriSM libraries.

Design, Construction, and Validation of a Yeast-Displayed Chemically Expanded Antibody Library

In vitro display technologies, exemplified by phage and yeast display, have emerged as powerful platforms for antibody discovery and engineering. However, the identification of antibodies that disrupt target functions beyond binding remains a challenge. In particular, there are very few strategies that support identification and engineering of either protein-based irreversible binders or inhibitory enzyme binders. Expanding the range of chemistries in antibody libraries has the potential to lead to efficient discovery of function-disrupting antibodies. In this work, we describe a yeast display-based platform for the discovery of chemically diversified antibodies. We constructed a billion-member antibody library that supports the presentation of a range of chemistries within antibody variable domains via noncanonical amino acid (ncAA) incorporation and subsequent bioorthogonal click chemistry conjugations. Use of a polyspecific orthogonal translation system enables introduction of chemical groups with various properties, including photo-reactive, proximity-reactive, and click chemistry-enabled functional groups for library screening. We established conjugation conditions that facilitate modification of the full library, demonstrating the feasibility of sorting the full billion-member library in "protein-small molecule hybrid" format in future work. Here, we conducted initial library screens after introducing O-(2-bromoethyl)tyrosine (OBeY), a weakly electrophilic ncAA capable of undergoing proximity-induced crosslinking to a target. Enrichments against donkey IgG and protein tyrosine phosphatase 1B (PTP1B) each led to the identification of several OBeY-substituted clones that bind to the targets of interest. Flow cytometry analysis on the yeast surface confirmed higher retention of binding for OBeY-substituted clones compared to clones substituted with ncAAs lacking electrophilic side chains after denaturation. However, subsequent crosslinking experiments in solution with ncAA-substituted clones yielded inconclusive results, suggesting that weakly reactive OBeY side chain is not sufficient to drive robust crosslinking in the clones isolated here. Nonetheless, this work establishes a multi-modal, chemically expanded antibody library and demonstrates the feasibility of conducting discovery campaigns in chemically expanded format. This versatile platform offers new opportunities for identifying and characterizing antibodies with properties beyond what is accessible with the canonical amino acids, potentially enabling discovery of new classes of reagents, diagnostics, and even therapeutic leads.

Sequence-developability mapping of affibody and fibronectin paratopes via library-scale variant characterization

Protein developability is requisite for use in therapeutic, diagnostic, or industrial applications. Many developability assays are low throughput, which limits their utility to the later stages of protein discovery and evolution. Recent approaches enable experimental or computational assessment of many more variants, yet the breadth of applicability across protein families and developability metrics is uncertain. Here, three library-scale assays-on-yeast protease, split green fluorescent protein (GFP), and non-specific binding-were evaluated for their ability to predict two key developability outcomes (thermal stability and recombinant expression) for the small protein scaffolds affibody and fibronectin. The assays' predictive capabilities were assessed via both linear correlation and machine learning models trained on the library-scale assay data. The on-yeast protease assay is highly predictive of thermal stability for both scaffolds, and the split-GFP assay is informative of affibody thermal stability and expression. The library-scale data was used to map sequence-developability landscapes for affibody and fibronectin binding paratopes, which guides future design of variants and libraries.

Hyperstable Synthetic Mini-Proteins as Effective Ligand Scaffolds

Small, single-domain protein scaffolds are compelling sources of molecular binding ligands with the potential for efficient physiological transport, modularity, and manufacturing. Yet, mini-proteins require a balance between biophysical robustness and diversity to enable new functions. We tested the developability and evolvability of millions of variants of 43 designed libraries of synthetic 40-amino acid βαββ proteins with diversified sheet, loop, or helix paratopes. We discovered a scaffold library that yielded hundreds of binders to seven targets while exhibiting high stability and soluble expression. Binder discovery yielded 6-122 nM affinities without affinity maturation and Tms averaging ≥78 °C. Broader βαββ libraries exhibited varied developability and evolvability. Sheet paratopes were the most consistently developable, and framework 1 was the most evolvable. Paratope evolvability was dependent on target, though several libraries were evolvable across many targets while exhibiting high stability and soluble expression. Select βαββ proteins are strong starting points for engineering performant binders.

Determinants of Developability and Evolvability of Synthetic Miniproteins as Ligand Scaffolds

Binding ligands empower molecular therapeutics and diagnostics. Despite an array of protein scaffolds engineered for binding, the biophysical elements that drive developability and evolvability are not fully understood. In particular, engineering novel function while maintaining biophysical integrity within the context of small, single-domain proteins is challenged by integration of the structural framework and the evolved binding site. Miniproteins present a challenge to our limits of protein engineering capability and provide advantages in physiological targeting, modularity for multi-functional constructs, and unique binding modes. Herein, we evaluate the ability of hyperstable synthetic miniproteins, originally designed for foldedness, to function as binding scaffolds. We synthesized 45 combinatorial libraries, with 109 variants, systematically varied across two topologies, each with five starting frameworks and four or five diverse, structurally distinct paratopes, to elucidate their impact on evolvability and developability. We evaluated evolvability with yeast display binding selections against four targets. High-throughput assays -stability via yeast display and soluble expression via split-GFP in E. coli - measured developability. The comprehensive, robust dataset demonstrates how protein topology, parental framework, and paratope structure and location all impact scaffold performance. A hyperstable framework and localized diversity are not sufficient for an effective scaffold, but several designs of these elements within synthetic miniproteins designed solely for stability result in scaffold libraries with effective evolvability and developability. Engineered variants were well-folded, thermally stable, and bound target with single-digit nanomolar affinity. Thus, hyperstable synthetic miniproteins can serve as precursors to developable, evolvable mini-scaffolds with unique potential for physiological transport, modularity, and binding modes.

Protein Engineering and High-Throughput Screening by Yeast Surface Display: Survey of Current Methods

Yeast surface display (YSD) is a powerful tool in biotechnology that links genotype to phenotype. In this review, the latest advancements in protein engineering and high-throughput screening based on YSD are covered. The focus is on innovative methods for overcoming challenges in YSD in the context of biotherapeutic drug discovery and diagnostics. Topics ranging from titrating avidity in YSD using transcriptional control to the development of serological diagnostic assays relying on serum biopanning and mitigation of unspecific binding are covered. Screening techniques against nontraditional cellular antigens, such as cell lysates, membrane proteins, and extracellular matrices are summarized and techniques are further delved into for expansion of the chemical repertoire, considering protein-small molecule hybrids and noncanonical amino acid incorporation. Additionally, in vivo gene diversification and continuous evolution in yeast is discussed. Collectively, these techniques enhance the diversity and functionality of engineered proteins isolated via YSD, broadening the scope of applications that can be addressed. The review concludes with future perspectives and potential impact of these advancements on protein engineering. The goal is to provide a focused summary of recent progress in the field.

Position-Specific Enrichment Ratio Matrix scores predict antibody variant properties from deep sequencing data

MOTIVATION

Deep sequencing of antibody and related protein libraries after phage or yeast-surface display sorting is widely used to identify variants with increased affinity, specificity, and/or improvements in key biophysical properties. Conventional approaches for identifying optimal variants typically use the frequencies of observation in enriched libraries or the corresponding enrichment ratios. However, these approaches disregard the vast majority of deep sequencing data and often fail to identify the best variants in the libraries.

RESULTS

Here, we present a method, Position-Specific Enrichment Ratio Matrix (PSERM) scoring, that uses entire deep sequencing datasets from pre- and post-selections to score each observed protein variant. The PSERM scores are the sum of the site-specific enrichment ratios observed at each mutated position. We find that PSERM scores are much more reproducible and correlate more strongly with experimentally measured properties than frequencies or enrichment ratios, including for multiple antibody properties (affinity and non-specific binding) for a clinical-stage antibody (emibetuzumab). We expect that this method will be broadly applicable to diverse protein engineering campaigns.

AVAILABILITY AND IMPLEMENTATION

All deep sequencing datasets and code to perform the analyses presented within are available via https://github.com/Tessier-Lab-UMich/PSERM_paper.

Protein engineering via sequence-performance mapping

Discovery and evolution of new and improved proteins has empowered molecular therapeutics, diagnostics, and industrial biotechnology. Discovery and evolution both require efficient screens and effective libraries, although they differ in their challenges because of the absence or presence, respectively, of an initial protein variant with the desired function. A host of high-throughput technologies-experimental and computational-enable efficient screens to identify performant protein variants. In partnership, an informed search of sequence space is needed to overcome the immensity, sparsity, and complexity of the sequence-performance landscape. Early in the historical trajectory of protein engineering, these elements aligned with distinct approaches to identify the most performant sequence: selection from large, randomized combinatorial libraries versus rational computational design. Substantial advances have now emerged from the synergy of these perspectives. Rational design of combinatorial libraries aids the experimental search of sequence space, and high-throughput, high-integrity experimental data inform computational design. At the core of the collaborative interface, efficient protein characterization (rather than mere selection of optimal variants) maps sequence-performance landscapes. Such quantitative maps elucidate the complex relationships between protein sequence and performance-e.g., binding, catalytic efficiency, biological activity, and developability-thereby advancing fundamental protein science and facilitating protein discovery and evolution.

Position-Specific Enrichment Ratio Matrix scores predict antibody variant properties from deep sequencing data

Motivation

Deep sequencing of antibody and related protein libraries after phage or yeast-surface display sorting is widely used to identify variants with increased affinity, specificity and/or improvements in key biophysical properties. Conventional approaches for identifying optimal variants typically use the frequencies of observation in enriched libraries or the corresponding enrichment ratios. However, these approaches disregard the vast majority of deep sequencing data and often fail to identify the best variants in the libraries.

Results

Here, we present a method, Position-Specific Enrichment Ratio Matrix (PSERM) scoring, that uses entire deep sequencing datasets from pre- and post-selections to score each observed protein variant. The PSERM scores are the sum of the site-specific enrichment ratios observed at each mutated position. We find that PSERM scores are much more reproducible and correlate more strongly with experimentally measured properties than frequencies or enrichment ratios, including for multiple antibody properties (affinity and non-specific binding) for a clinical-stage antibody (emibetuzumab). We expect that this method will be broadly applicable to diverse protein engineering campaigns.

Availability

All deep sequencing datasets and code to do the analyses presented within are available via GitHub.

Contact

Peter Tessier, ptessier@umich.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Design of an artificial phage-display library based on a new scaffold improved for average stability of the randomized proteins

Scaffold-based protein libraries are designed to be both diverse and rich in functional/folded proteins. However, introducing an extended diversity while preserving stability of the initial scaffold remains a challenge. Here we developed an original approach to select the ensemble of folded proteins from an initial library. The thermostable CheY protein from Thermotoga maritima was chosen as scaffold. Four loops of CheY were diversified to create a new binding surface. The subset of the library giving rise to folded proteins was first selected using a natural protein partner of the template scaffold. Then, a gene shuffling approach based on a single restriction enzyme was used to recombine DNA sequences encoding these filtrated variants. Taken together, the filtration strategy and the shuffling of the filtrated sequences were shown to enrich the library in folded and stable sequences while maintaining a large diversity in the final library (Lib-Cheytins 2.1). Binders of the Oplophorus luciferase Kaz domain were then selected by phage display from the final library, showing affinities in the μM range. One of the best variants induced a loss of 92% of luminescent activity, suggesting that this Cheytin preferentially binds to the Kaz active site.

Engineering Proteins Containing Noncanonical Amino Acids on the Yeast Surface

Yeast display has been used to advance many critical research areas, including the discovery of unique protein binders and biological therapeutics. In parallel, noncanonical amino acids (ncAAs) have been used to tailor antibody-drug conjugates and enable discovery of therapeutic leads. Together, these two technologies have allowed for generation of synthetic antibody libraries, where the introduction of ncAAs in yeast-displayed proteins allows for library screening for therapeutically relevant targets. The combination of yeast display with genetically encoded ncAAs increases the available chemistry in proteins and advances applications that require high-throughput strategies. In this chapter, we discuss methods for displaying proteins containing ncAAs on the yeast surface, generating and screening libraries of proteins containing ncAAs, preparing bioconjugates on the yeast surface in large scale, generating and screening libraries of aminoacyl-tRNA synthetases (aaRSs) for encoding ncAAs by using reporter constructs, and characterizing ncAA-containing proteins secreted from yeast. The experimental designs laid out in this chapter are generalizable for discovery of protein binders to a variety of targets and aaRS evolution to continue expanding the genetic code beyond what is currently available in yeast.

Engineered protein-small molecule conjugates empower selective enzyme inhibition

Potent, specific ligands drive precision medicine and fundamental biology. Proteins, peptides, and small molecules constitute effective ligand classes. Yet greater molecular diversity would aid the pursuit of ligands to elicit precise biological activity against challenging targets. We demonstrate a platform to discover protein-small molecule (PriSM) hybrids to combine unique pharmacophore activities and shapes with constrained, efficiently engineerable proteins. In this platform, a fibronectin protein library is displayed on yeast with a single cysteine coupled to acetazolamide via a maleimide-poly(ethylene glycol) linker. Magnetic and flow cytometric sorts enrich specific binders to carbonic anhydrase isoforms. Isolated PriSMs exhibit potent, specific inhibition of carbonic anhydrase isoforms with efficacy superior to that of acetazolamide or protein alone, including an 80-fold specificity increase and 9-fold potency gain. PriSMs are engineered with multiple linker lengths, protein conjugation sites, and sequences against two different isoforms, which reveal platform flexibility and impacts of molecular designs. PriSMs advance the molecular diversity of efficiently engineerable ligands.

Design and Evaluation of Engineered Extracellular Vesicle (EV)-Based Targeting for EGFR-Overexpressing Tumor Cells Using Monobody Display

Background: Extracellular vesicles (EVs) are attracting interest as a new class of drug delivery vehicles due to their intrinsic nature of biomolecular transport in the body. We previously demonstrated that EV surface modification with tissue-specific molecules accomplished targeted EV-mediated DNA delivery. Methods: Here, we describe reliable methods for (i) generating EGFR tumor-targeting EVs via the display of high-affinity monobodies and (ii) in vitro measurement of EV binding using fluorescence and bioluminescence labeling. Monobodies are a well-suited class of small (10 kDa) non-antibody scaffolds derived from the human fibronectin type III (FN3) domain. Results: The recombinant protein consists of the EGFR-targeting monobody fused to the EV-binding domain of lactadherin (C1C2), enabling the monobody displayed on the surface of the EVs. In addition, the use of bioluminescence or fluorescence molecules on the EV surface allows for the assessment of EV binding to the target cells. Conclusions: In this paper, we describe methods of EV engineering to generate targeted delivery vehicles using monobodies that will have diverse applications to furnish future EV therapeutic development, including qualitative and quantitative in vitro evaluation for their binding capacity.

Machine Learning-driven Protein Library Design: A Path Toward Smarter Libraries

Proteins are small yet valuable biomolecules that play a versatile role in therapeutics and diagnostics. The intricate sequence-structure-function paradigm in the realm of proteins opens the possibility for directly mapping amino acid sequence to function. However, the rugged nature of the protein fitness landscape and an astronomical number of possible mutations even for small proteins make navigating this system a daunting task. Moreover, the scarcity of functional proteins and the ease with which deleterious mutations are introduced, due to complex epistatic relationships, compound the existing challenges. This highlights the need for auxiliary tools in current techniques such as rational design and directed evolution. To that end, the state-of-the-art machine learning can offer time and cost efficiency in finding high fitness proteins, circumventing unnecessary wet-lab experiments. In the context of improving library design, machine learning provides valuable insights via its unique features such as high adaptation to complex systems, multi-tasking, and parallelism, and the ability to capture hidden trends in input data. Finally, both the advancements in computational resources and the rapidly increasing number of sequences in protein databases will allow more promising and detailed insights delivered from machine learning to protein library design. In this chapter, fundamental concepts and a method for machine learning-driven library design leveraging deep sequencing datasets will be discussed. We elaborate on (1) basic knowledge about machine learning algorithms, (2) the benefit of machine learning in library design, and (3) methodology for implementing machine learning in library design.

Ancestral Sequence Reconstruction and Alternate Amino Acid States Guide Protein Library Design for Directed Evolution

Engineered proteins possess nearly limitless possibilities in medical and industrial applications but finding a precise amino acid sequence for these applications is challenging. A robust approach for discovering protein sequences with a desired functionality uses a library design method in which combinations of mutations are applied to a robust starting point. Determining useful mutations can be tortuous, yet rewarding; in this chapter, we present a novel library design method that uses information provided by ancestral sequence reconstruction (ASR) to create a library likely to have stable proteins with diverse function. ASR computational tools use a multi-sequence alignment of homologous proteins and an evolutionary model to estimate the protein sequences of the numerous common ancestors. For all ancestors, these tools calculate the probability of every amino acid occurring at each position within the sequence alignment. The alternate amino acid states at individual positions corelate to a region of stability in sequence space around the ancestral sequence which can inform site-wise diversification within a combinatorial library. The method presented in this chapter balances the quality of results, the computational resources needed, and ease of use.

Site-wise Diversification of Combinatorial Libraries Using Insights from Structure-guided Stability Calculations

Many auspicious clinical and industrial accomplishments have improved the human condition by means of protein engineering. Despite these achievements, our incomplete understanding of the sequence-structure-function relationship prevents rapid innovation. To tackle this problem, we must develop and integrate new and existing technologies. To date, directed evolution and rational design have dominated as protein engineering principles. Even so, prior to screening for novel or improved functions, a large collection of variants, within a protein library, exist along an ambiguous mutational terrain. Complicating things further, the choice of where to initialize investigation along a vast sequence space becomes even more difficult given that the majority of any sequence lacks function entirely. Unfortunately, even when considering functionally relevant positions, random substitutions can prove to be destabilizing, causing a hindrance to an otherwise function-inducing, stability-reliant folding process. To enhance productivity in the field, we seek to address this issue of destabilization, and subsequent disfunction, at protein-protein and protein-ligand interacting regions. Herein, the process of choosing amenable positions - and amino acids at those positions - allows for a refined, knowledge-based approach to combinatorial library design. Using structural data, we perform computational stability prediction with FoldX's PositionScan and Rosetta's ddG_monomer in tandem, allowing for the refinement of our thermodynamic stability data through the comparison of results. In turn, we provide a process for selecting in silico predicted mutually stabilizing positions and avoiding overly destabilizing ones that guides the site-wise diversification of combinatorial libraries.

A novel framework for engineering protein loops exploring length and compositional variation

Insertions and deletions (indels) are known to affect function, biophysical properties and substrate specificity of enzymes, and they play a central role in evolution. Despite such clear significance, this class of mutation remains an underexploited tool in protein engineering with few available platforms capable of systematically generating and analysing libraries of varying sequence composition and length. We present a novel DNA assembly platform (InDel assembly), based on cycles of endonuclease restriction digestion and ligation of standardised dsDNA building blocks, that can generate libraries exploring both composition and sequence length variation. In addition, we developed a framework to analyse the output of selection from InDel-generated libraries, combining next generation sequencing and alignment-free strategies for sequence analysis. We demonstrate the approach by engineering the well-characterized TEM-1 β-lactamase Ω-loop, involved in substrate specificity, identifying multiple novel extended spectrum β-lactamases with loops of modified length and composition-areas of the sequence space not previously explored. Together, the InDel assembly and analysis platforms provide an efficient route to engineer protein loops or linkers where sequence length and composition are both essential functional parameters.

Chemical Diversification of Simple Synthetic Antibodies

Antibodies possess properties that make them valuable as therapeutics, diagnostics, and basic research tools. However, antibody chemical reactivity and covalent antigen binding are constrained, or even prevented, by the narrow range of chemistries encoded in canonical amino acids. In this work, we investigate strategies for leveraging an expanded range of chemical functionality using yeast displayed antibodies containing noncanonical amino acids (ncAAs) in or near antibody complementarity determining regions (CDRs). To enable systematic characterization of the effects of ncAA incorporation on antibody function, we first investigated whether diversification of a single antibody loop would support the isolation of binding clones against immunoglobulins from three species. We constructed and screened a billion-member library containing canonical amino acid diversity and loop length diversity only within the third complementarity determining region of the heavy chain (CDR-H3). Isolated clones exhibited moderate affinities (double- to triple-digit nanomolar affinities) and, in several cases, single-species specificity, confirming that antibody specificity can be mediated by a single CDR. This constrained diversity enabled the utilization of additional CDRs for the installation of chemically reactive and photo-cross-linkable ncAAs. Binding studies of ncAA-substituted antibodies revealed that ncAA incorporation is reasonably well tolerated, with observed changes in affinity occurring as a function of ncAA side chain identity, substitution site, and the ncAA incorporation machinery used. Multiple azide-containing ncAAs supported copper-catalyzed azide-alkyne cycloaddition (CuAAC) and strain-promoted azide-alkyne cycloaddition (SPAAC) without the abrogation of binding function. Similarly, several alkyne substitutions facilitated CuAAC without the apparent disruption of binding. Finally, antibodies substituted with a photo-cross-linkable ncAA were evaluated for ultraviolet-mediated cross-linking on the yeast surface. Competition-based assays revealed position-dependent covalent linkages, strongly suggesting successful cross-linking. Key findings regarding CuAAC reactions and photo-cross-linking on the yeast surface were confirmed using soluble forms of ncAA-substituted clones. The consistency of findings on the yeast surface and in solution suggest that chemical diversification can be incorporated into yeast display screening approaches. Taken together, our results highlight the power of integrating the use of yeast display and ncAAs in search of proteins with "chemically augmented" binding functions. This includes strategies for systematically introducing small molecule functionality within binding protein structures and evaluating protein-based covalent target binding. The efficient preparation and chemical diversification of antibodies on the yeast surface open up new possibilities for discovering "drug-like" protein leads in high throughput.

Extended yeast surface display linkers enhance the enrichment of ligands in direct mammalian cell selections

Selections of yeast-displayed ligands on mammalian cell monolayers benefit from high target expression and nanomolar affinity, which are not always available. Prior work extending the yeast-protein linker from 40 to 80 amino acids improved yield and enrichment but is hypothesized to be below the optimal length, prompting evaluation of an extended amino acid linker. A 641-residue linker provided enhanced enrichment with a 2-nM affinity fibronectin ligand and 105 epidermal growth factor receptors (EGFR) per cell (14 ± 2 vs. 8 ± 1, P = 0.008) and a >600-nM affinity ligand, 106 EGFR per cell system (23 ± 7 vs. 0.8 ± 0.2, P = 0.004). Enhanced enrichment was also observed with a 310-nM affinity affibody ligand and 104 CD276 per cell, suggesting a generalizable benefit to other scaffolds and targets. Spatial modeling of the linker suggests that improved extracellular accessibility of ligand enables the observed enrichment under conditions not previously possible.

Structure- and sequence-based design of synthetic single-domain antibody libraries

Single-domain antibody fragments known as VHH have emerged in the pharmaceutical industry as useful biotherapeutics. These molecules, which are naturally produced by camelids, share the characteristics of high affinity and specificity with traditional human immunoglobulins, while consisting of only a single heavy chain. Currently, the most common method for generating VHH is via animal immunization, which can be costly and time-consuming. Here we describe the development of a synthetic VHH library for in vitro selection of single domain binders. We combine structure-based design and next-generation sequencing analysis to build a library with characteristics that closely mimic the natural repertoire. To validate the performance of our synthetic library, we isolated VHH against three model antigens (soluble mouse PD-1 ectodomain, amyloid-β peptide, and MrgX1 GPCR) of different sizes and characteristics. We were able to isolate diverse binders targeting different epitopes with high affinity (as high as 5 nM) against all three targets. We then show that anti-mPD-1 binders have functional activity in a receptor blocking assay.

Magnetic Bead-Immobilized Mammalian Cells Are Effective Targets to Enrich Ligand-Displaying Yeast

Yeast surface display empowers selection of protein binding ligands, typically using recombinant soluble antigens. However, ectodomain fragments of transmembrane targets may fail to recapitulate their true, membrane-bound form. Direct selections against adhered mammalian cells empower enrichment of genuine binders yet benefit from high target expression, robustly adherent mammalian cells, and nanomolar affinity ligands. This study evaluates a modified format with mammalian cells immobilized to magnetic beads; yeast-displayed fibronectin domain and affibody ligands of known affinities and cells with expression ranges of epidermal growth factor receptor (EGFR) and CD276 elucidate important parameters to ligand enrichment and yield in cell suspension panning with comparison to adherent panning. Cell suspension panning is hindered by significant background of nondisplaying yeast but exhibits yield advantages in model EGFR systems for a high affinity (K_D = 2 nM) binder on cells with both high (10⁶ per cell) target expression (9.6 ± 0.6% vs 3.2 ± 0.4%, p < 0.0001) and mid (10⁵) target expression (2.3 ± 0.5% vs 0.41 ± 0.09%, p = 0.0008), as well as for a low affinity (K_D > 600 nM) binder on high target expression cells (2.0 ± 0.5% vs 0.017 ± 0.005%; p = 0.001). Significant enrichment was observed for all EGFR systems except the low-affinity, high expression system. The CD276 system failed to provide significant enrichment, indicating that this technique may not be suitable for all targets. Collectively, this study highlights new approaches that yield successful enrichment of yeast-displayed ligands via panning on immobilized mammalian cells.

Fine Epitope Mapping of the CD19 Extracellular Domain Promotes Design

The B-cell surface protein CD19 is present throughout the cell life cycle and is uniformly expressed in leukemias, making it a target for chimeric antigen receptor engineered immune cell therapy. Identifying the sequence dependence of the binding of CD19 to antibodies empowers fundamental study and more tailored development of CD19-targeted therapeutics. To identify the antibody-binding epitopes on CD19, we screened a comprehensive single-site saturation mutation library of the human CD19 extracellular domain to identify mutations detrimental to binding FMC63-the dominant CD19 antibody used in chimeric antigen receptor development-as well as 4G7-2E3 and 3B10, which have been used in various types of CD19 research and development. All three antibodies had partially overlapping, yet distinct, epitopes near the published epitope of antibody B43. The FMC63 conformational epitope spans spatially adjacent, but genetically distant, loops in exons 3 and 4. The 3B10 epitope is a linear peptide sequence that binds CD19 with 440 pM affinity. Along with their primary goal of epitope mapping, the mutational tolerance data also empowered additional CD19 variant design and analysis. A designed CD19 variant with all N-linked glycosylation sites removed successfully bound antibody in the yeast display context, which provides a lead for aglycosylated applications. Screening for thermally stable variants identified mutations to guide further CD19 stabilization for fusion protein applications and revealed evolutionary affinity-stability trade-offs. These fundamental insights into CD19 sequence-function relationships enhance our understanding of antibody-mediated CD19-targeted therapeutics.

Engineered Fn3 protein has targeted therapeutic effect on mesothelin-expressing cancer cells and increases tumor cell sensitivity to chemotherapy

Mesothelin is a protein expressed at high levels on the cell surface in a variety of cancers, with limited expression in healthy tissues. The presence of mesothelin on tumor tissue correlates with increased invasion and metastasis, and resistance to traditional chemotherapies, through mechanisms that remain poorly understood. Molecules that specifically recognize mesothelin and interrupt its contribution to tumor progression have significant potential for targeted therapy and targeted drug delivery applications. A number of mesothelin-targeting therapies are in preclinical and clinical development, although none are currently approved for routine clinical use. In this work, we report the development of a mesothelin-targeting protein based on the fibronectin type-III non-antibody protein scaffold, which offers opportunities for applications where antibodies have limitations. We engineered protein variants that bind mesothelin with high affinity and selectively initiate apoptosis in tumor cells expressing mesothelin. Interestingly, apoptosis does not occur through a caspase-mediated pathway and does not require downregulation of cell-surface mesothelin, suggesting a currently unknown pathway through which mesothelin contributes to cancer progression. Importantly, simultaneous treatment with mesothelin-binding protein and chemotherapeutic mitomycin C had a greater cytotoxic effect on mesothelin-positive cells compared to either molecule alone, underscoring the potential for combination therapy including biologics targeting mesothelin.

De Novo Isolation & Affinity Maturation of yeast-displayed Virion-binding human fibronectin domains by flow cytometric screening against Virions

BACKGROUND

The promise of biopharmaceuticals comprising one or more binding domains motivates the development of novel methods for de novo isolation and affinity maturation of virion-binding domains. Identifying avenues for overcoming the challenges associated with using virions as screening reagents is paramount given the difficulties associated with obtaining high-purity virus-associated proteins that retain the conformation exhibited on the virion surface.

RESULTS

Fluorescence activated cell sorting (FACS) of 1.5 × 107 clones taken from a naïve yeast surface-displayed human fibronectin domain (Fn3) against whole virions yielded two unique binders to Zika virions. Construction and FACS of site-directed binding loop mutant libraries based on one of these binders yielded multiple progeny clones with enhanced Zika-binding affinities. These affinity-matured clones bound Zika virions with low double- or single-digit nanomolar affinity in ELISA assays, and expressed well as soluble proteins in E. coli shake flask culture, with post-purification yields exceeding 10 mg/L.

CONCLUSIONS

FACS of a yeast-displayed binding domain library is an efficient method for de novo isolation of virion-binding domains. Affinities of isolated virion-binding clones are readily enhanced via FACS screening of mutant progeny libraries. Given that most binding domains are compatible with yeast display, the approach taken in this work may be broadly utilized for generating virion-binding domains against many different viruses for use in passive immunotherapy and the prevention of viral infection.

Validation and Stabilization of a Prophage Lysin of Clostridium perfringens by Using Yeast Surface Display and Coevolutionary Models

Bacteriophage lysins are compelling antimicrobial proteins whose biotechnological utility and evolvability would be aided by elevated stability. Lysin catalytic domains, which evolved as modular entities distinct from cell wall binding domains, can be classified into one of several families with highly conserved structure and function, many of which contain thousands of annotated homologous sequences. Motivated by the quality of these evolutionary data, the performance of generative protein models incorporating coevolutionary information was analyzed to predict the stability of variants in a collection of 9,749 multimutants across 10 libraries diversified at different regions of a putative lysin from a prophage region of a Clostridium perfringens genome. Protein stability was assessed via a yeast surface display assay with accompanying high-throughput sequencing. Statistical fitness of mutant sequences, derived from second-order Potts models inferred with different levels of sequence homolog information, was predictive of experimental stability with areas under the curve (AUCs) ranging from 0.78 to 0.85. To extract an experimentally derived model of stability, a logistic model with site-wise score contributions was regressed on the collection of multimutants. This achieved a cross-validated classification performance of 0.95. Using this experimentally derived model, 5 designs incorporating 5 or 6 mutations from multiple libraries were constructed. All designs retained enzymatic activity, with 4 of 5 increasing the melting temperature and with the highest-performing design achieving an improvement of +4°C.IMPORTANCE Bacteriophage lysins exhibit high specificity and activity toward host bacteria with which the phage coevolved. These properties of lysins make them attractive for use as antimicrobials. Although there has been significant effort to develop platforms for rapid lysin engineering, there have been numerous shortcomings when pursuing the ultrahigh throughput necessary for the discovery of rare combinations of mutations to improve performance. In addition to validation of a putative lysin and stabilization thereof, the experimental and computational methods presented here offer a new avenue for improving protein stability and are easily scalable to analysis of tens of millions of mutations in single experiments.

Biophysical Characterization Platform Informs Protein Scaffold Evolvability

Evolving specific molecular recognition function of proteins requires strategic navigation of a complex mutational landscape. Protein scaffolds aid evolution via a conserved platform on which a modular paratope can be evolved to alter binding specificity. Although numerous protein scaffolds have been discovered, the underlying properties that permit binding evolution remain unknown. We present an algorithm to predict a protein scaffold's ability to evolve novel binding function based upon computationally calculated biophysical parameters. The ability of 17 small proteins to evolve binding functionality across seven discovery campaigns was determined via magnetic activated cell sorting of 10¹⁰ yeast-displayed protein variants. Twenty topological and biophysical properties were calculated for 787 small protein scaffolds and reduced into independent components. Regularization deduced which extracted features best predicted binding functionality, providing a 4/6 true positive rate, a 9/11 negative predictive value, and a 4/6 positive predictive value. Model analysis suggests a large, disconnected paratope will permit evolved binding function. Previous protein engineering endeavors have suggested that starting with a highly developable (high producibility, stability, solubility) protein will offer greater mutational tolerance. Our results support this connection between developability and evolvability by demonstrating a relationship between protein production in the soluble fraction of Escherichia coli and the ability to evolve binding function upon mutation. We further explain the necessity for initial developability by observing a decrease in proteolytic stability of protein mutants that possess binding functionality over nonfunctional mutants. Future iterations of protein scaffold discovery and evolution will benefit from a combination of computational prediction and knowledge of initial developability properties.

Cellular-Based Selections Aid Yeast-Display Discovery of Genuine Cell-Binding Ligands: Targeting Oncology Vascular Biomarker CD276

Yeast surface display is a proven tool for the selection and evolution of ligands with novel binding activity. Selections from yeast surface display libraries against transmembrane targets are generally carried out using recombinant soluble extracellular domains. Unfortunately, these molecules may not be good models of their true, membrane-bound form for a variety of reasons. Such selection campaigns often yield ligands that bind a recombinant target but not target-expressing cells or tissues. Advances in cell-based selections with yeast surface display may aid the frequency of evolving ligands that do bind true, membrane-bound antigens. This study aims to evaluate ligand selection strategies using both soluble target-driven and cellular selection techniques to determine which methods yield translatable ligands most efficiently and generate novel binders against CD276 (B7-H3) and Thy1, two promising tumor vasculature targets. Out of four ligand selection campaigns carried out using only soluble extracellular domains, only an affibody library sorted against CD276 yielded translatable binders. In contrast, fibronectin domains against CD276 and affibodies against CD276 were discovered in campaigns that either combined soluble target and cellular selection methods or used cellular selection methods alone. A high frequency of non target-specific ligands discovered from the use of cellular selection methods alone motivated the development of a depletion scheme using disadhered, antigen-negative mammalian cells as a blocking agent. Affinity maturation of CD276-binding affibodies by error-prone PCR and helix walking resulted in strong, specific cellular CD276 affinity ( Kd = 0.9 ± 0.6 nM). Collectively, these results motivate the use of cellular selections in tandem with recombinant selections and introduce promising affibody molecules specific to CD276 for further applications.

Constrained Combinatorial Libraries of Gp2 Proteins Enhance Discovery of PD-L1 Binders

Engineered protein ligands are used for molecular therapy, diagnostics, and industrial biotechnology. The Gp2 domain is a 45-amino acid scaffold that has been evolved for specific, high-affinity binding to multiple targets by diversification of two solvent-exposed loops. Inspired by sitewise enrichment of select amino acids, including cysteine pairs, in earlier Gp2 discovery campaigns, we hypothesized that the breadth and efficiency of de novo Gp2 discovery will be aided by sitewise amino acid constraint within combinatorial library design. We systematically constructed eight libraries and comparatively evaluated their efficacy for binder discovery via yeast display against a panel of targets. Conservation of a cysteine pair at the termini of the first diversified paratope loop increased binder discovery 16-fold ( p < 0.001). Yet two other libraries with conserved cysteine pairs, within the second loop or an interloop pair, did not aid discovery thereby indicating site-specific impact. Via a yeast display protease resistance assay, Gp2 variants from the loop one cysteine pair library were 3.3 ± 2.1-fold ( p = 0.005) more stable than nonconstrained variants. Sitewise constraint of noncysteine residues-guided by previously evolved binders, natural Gp2 homology, computed stability, and structural analysis-did not aid discovery. A panel of binders to programmed death ligand 1 (PD-L1), a key target in cancer immunotherapy, were discovered from the loop 1 cysteine constraint library. Affinity maturation via loop walking resulted in strong, specific cellular PD-L1 affinity ( K_d = 6-9 nM).

Fn3 proteins engineered to recognize tumor biomarker mesothelin internalize upon binding

Mesothelin is a cell surface protein that is overexpressed in numerous cancers, including breast, ovarian, lung, liver, and pancreatic tumors. Aberrant expression of mesothelin has been shown to promote tumor progression and metastasis through interaction with established tumor biomarker CA125. Therefore, molecules that specifically bind to mesothelin have potential therapeutic and diagnostic applications. However, no mesothelin-targeting molecules are currently approved for routine clinical use. While antibodies that target mesothelin are in development, some clinical applications may require a targeting molecule with an alternative protein fold. For example, non-antibody proteins are more suitable for molecular imaging and may facilitate diverse chemical conjugation strategies to create drug delivery complexes. In this work, we engineered variants of the fibronectin type III domain (Fn3) non-antibody protein scaffold to bind to mesothelin with high affinity, using directed evolution and yeast surface display. Lead engineered Fn3 variants were solubly produced and purified from bacterial culture at high yield. Upon specific binding to mesothelin on human cancer cell lines, the engineered Fn3 proteins internalized and co-localized to early endosomes. To our knowledge, this is the first report of non-antibody proteins engineered to bind mesothelin. The results validate that non-antibody proteins can be engineered to bind to tumor biomarker mesothelin, and encourage the continued development of engineered variants for applications such as targeted diagnostics and therapeutics.

Deep sequencing methods for protein engineering and design

The advent of next-generation sequencing (NGS) has revolutionized protein science, and the development of complementary methods enabling NGS-driven protein engineering have followed. In general, these experiments address the functional consequences of thousands of protein variants in a massively parallel manner using genotype-phenotype linked high-throughput functional screens followed by DNA counting via deep sequencing. We highlight the use of information rich datasets to engineer protein molecular recognition. Examples include the creation of multiple dual-affinity Fabs targeting structurally dissimilar epitopes and engineering of a broad germline-targeted anti-HIV-1 immunogen. Additionally, we highlight the generation of enzyme fitness landscapes for conducting fundamental studies of protein behavior and evolution. We conclude with discussion of technological advances.

Titratable Avidity Reduction Enhances Affinity Discrimination in Mammalian Cellular Selections of Yeast-Displayed Ligands

Yeast surface display selections against mammalian cell monolayers have proven effective in isolating proteins with novel binding activity. Recent advances in this technique allow for the recovery of clones with even micromolar binding affinities. However, no efficient method has been shown for affinity-based selection in this context. This study demonstrates the effectiveness of titratable avidity reduction using dithiothreitol to achieve this goal. A series of epidermal growth factor receptor binding fibronectin domains with a range of affinities are used to quantitatively identify the number of ligands per yeast cell that yield the strongest selectivity between strong, moderate, and weak affinities. Notably, reduction of ligand display to 3,000-6,000 ligands per yeast cell of a 2 nM binder yields 16-fold better selectivity than that to a 17 nM binder. These lessons are applied to affinity maturation of an EpCAM-binding fibronectin population, yielding an enriched pool of ligands with significantly stronger affinity than that of an analogous pool sorted by standard cellular selection methods. Collectively, this study offers a facile approach for affinity selection of yeast-displayed ligands against full-length cellular targets and demonstrates the effectiveness of this method by generating EpCAM-binding ligands that are promising for further applications.

A Gradient of Sitewise Diversity Promotes Evolutionary Fitness for Binder Discovery in a Three-Helix Bundle Protein Scaffold

Engineered proteins provide clinically and industrially impactful molecules and utility within fundamental research, yet inefficiencies in discovering lead variants with new desired functionality, while maintaining stability, hinder progress. Improved function, which can result from a few strategic mutations, is fundamentally separate from discovering novel function, which often requires large leaps in sequence space. While a highly diverse combinatorial library covering immense sequence space would empower protein discovery, the ability to sample only a minor subset of sequence space and the typical destabilization of random mutations preclude this strategy. A balance must be reached. At library scale, compounding several destabilizing mutations renders many variants unable to properly fold and devoid of function. Broadly searching sequence space while reducing the level of destabilization may enhance evolution. We exemplify this balance with affibody, a three-helix bundle protein scaffold. Using natural ligand data sets, stability and structural computations, and deep sequencing of thousands of binding variants, a protein library was designed on a sitewise basis with a gradient of mutational levels across 29% of the protein. In direct competition of biased and uniform libraries, both with 1 × 10⁹ variants, for discovery of 6 × 10⁴ ligands (5 × 10³ clusters) toward seven targets, biased amino acid frequency increased ligand discovery 13 ± 3-fold. Evolutionarily favorable amino acids, both globally and site-specifically, are further elucidated. The sitewise amino acid bias aids evolutionary discovery by reducing the level of mutant destabilization as evidenced by a midpoint of denaturation (62 ± 4 °C) 15 °C higher than that of unbiased mutants (47 ± 11 °C; p < 0.001). Sitewise diversification, identified by high-throughput evolution and rational library design, improves discovery efficiency.

ScaffoldSeq: Software for characterization of directed evolution populations

ScaffoldSeq is software designed for the numerous applications-including directed evolution analysis-in which a user generates a population of DNA sequences encoding for partially diverse proteins with related functions and would like to characterize the single site and pairwise amino acid frequencies across the population. A common scenario for enzyme maturation, antibody screening, and alternative scaffold engineering involves naïve and evolved populations that contain diversified regions, varying in both sequence and length, within a conserved framework. Analyzing the diversified regions of such populations is facilitated by high-throughput sequencing platforms; however, length variability within these regions (e.g., antibody CDRs) encumbers the alignment process. To overcome this challenge, the ScaffoldSeq algorithm takes advantage of conserved framework sequences to quickly identify diverse regions. Beyond this, unintended biases in sequence frequency are generated throughout the experimental workflow required to evolve and isolate clones of interest prior to DNA sequencing. ScaffoldSeq software uniquely handles this issue by providing tools to quantify and remove background sequences, cluster similar protein families, and dampen the impact of dominant clones. The software produces graphical and tabular summaries for each region of interest, allowing users to evaluate diversity in a site-specific manner as well as identify epistatic pairwise interactions. The code and detailed information are freely available at http://research.cems.umn.edu/hackel. Proteins 2016; 84:869-874. © 2016 Wiley Periodicals, Inc.