Optimizing the affinity and specificity of proteins with molecular display

Engineering TNA polymerases through iterative cycles of directed evolution

DNA polymerases are important tools for biotechnology, synthetic biology, and chemical biology as they are routinely used to amplify and edit genetic information. However, natural polymerases do not recognize artificial genetic polymers (also known as xeno-nucleic acids or XNAs) with unique sugar-phosphate backbone structures. Directed evolution offers a possible solution to this problem by facilitating the discovery of engineered versions of natural polymerases that can copy genetic information back and forth between DNA and XNA. Here we report a directed evolution strategy for discovering polymerases that can synthesize threose nucleic acid (TNA) on DNA templates. The workflow involves library generation and expression in E. coli, high-throughput microfluidics-based screening of uniform water-in-oil droplets, plasmid recovery, secondary screening, and library regeneration. This technique is sufficiently general that it could be applied to a wide range of problems involving DNA modifying enzymes.

Intragenic compensation through the lens of deep mutational scanning

A significant fraction of mutations in proteins are deleterious and result in adverse consequences for protein function, stability, or interaction with other molecules. Intragenic compensation is a specific case of positive epistasis when a neutral missense mutation cancels effect of a deleterious mutation in the same protein. Permissive compensatory mutations facilitate protein evolution, since without them all sequences would be extremely conserved. Understanding compensatory mechanisms is an important scientific challenge at the intersection of protein biophysics and evolution. In human genetics, intragenic compensatory interactions are important since they may result in variable penetrance of pathogenic mutations or fixation of pathogenic human alleles in orthologous proteins from related species. The latter phenomenon complicates computational and clinical inference of an allele's pathogenicity. Deep mutational scanning is a relatively new technique that enables experimental studies of functional effects of thousands of mutations in proteins. We review the important aspects of the field and discuss existing limitations of current datasets. We reviewed ten published DMS datasets with quantified functional effects of single and double mutations and described rates and patterns of intragenic compensation in eight of them.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12551-022-01005-w.

Modular peptide binders - development of a predictive technology as alternative for reagent antibodies

Current biomedical research and diagnostics critically depend on detection agents for specific recognition and quantification of protein molecules. Monoclonal antibodies have been used for this purpose over decades and facilitated numerous biological and biomedical investigations. Recently, however, it has become apparent that many commercial reagent antibodies lack specificity or do not recognize their target at all. Thus, synthetic alternatives are needed whose complex designs are facilitated by multidisciplinary approaches incorporating experimental protein engineering with computational modeling. Here, we review the status of such an engineering endeavor based on the modular armadillo repeat protein scaffold and discuss challenges in its implementation.

Generation of a Novel High-Affinity Antibody Binding to PCSK9 Catalytic Domain with Slow Dissociation Rate by CDR-Grafting, Alanine Scanning and Saturated Site-Directed Mutagenesis for Favorably Treating Hypercholesterolemia

Inhibition of proprotein convertase subtilisin/kexin type 9 (PCSK9) has become an attractive therapeutic strategy for lowering low-density lipoprotein cholesterol (LDL-C). In this study, a novel high affinity humanized IgG1 mAb (named h5E12-L230G) targeting the catalytic domain of human PCSK9 (hPCSK9) was generated by using CDR-grafting, alanine-scanning mutagenesis, and saturated site-directed mutagenesis. The heavy-chain constant region of h5E12-L230G was modified to eliminate the cytotoxic effector functions and mitigate the heterogeneity. The biolayer interferometry (BLI) binding assay and molecular docking study revealed that h5E12-L230G binds to the catalytic domain of hPCSK9 with nanomolar affinity (K_D = 1.72 nM) and an extremely slow dissociation rate (k_off, 4.84 × 10⁻⁵ s⁻¹), which interprets its quite low binding energy (−54.97 kcal/mol) with hPCSK9. Additionally, h5E12-L230G elevated the levels of LDLR and enhanced the LDL-C uptake in HepG2 cells, as well as reducing the serum LDL-C and total cholesterol (TC) levels in hyperlipidemic mouse model with high potency comparable to the positive control alirocumab. Our data indicate that h5E12-L230G is a high-affinity anti-PCSK9 antibody candidate with an extremely slow dissociation rate for favorably treating hypercholesterolemia and relevant cardiovascular diseases.

Antibody display technologies: selecting the cream of the crop

Antibody display technologies enable the successful isolation of antigen-specific antibodies with therapeutic potential. The key feature that facilitates the selection of an antibody with prescribed properties is the coupling of the protein variant to its genetic information and is referred to as genotype phenotype coupling. There are several different platform technologies based on prokaryotic organisms as well as strategies employing higher eukaryotes. Among those, phage display is the most established system with more than a dozen of therapeutic antibodies approved for therapy that have been discovered or engineered using this approach. In recent years several other technologies gained a certain level of maturity, most strikingly mammalian display. In this review, we delineate the most important selection systems with respect to antibody generation with an emphasis on recent developments.

Ribosome Display Technology: Applications in Disease Diagnosis and Control

Antibody ribosome display remains one of the most successful in vitro selection technologies for antibodies fifteen years after it was developed. The unique possibility of direct generation of whole proteins, particularly single-chain antibody fragments (scFvs), has facilitated the establishment of this technology as one of the foremost antibody production methods. Ribosome display has become a vital tool for efficient and low-cost production of antibodies for diagnostics due to its advantageous ability to screen large libraries and generate binders of high affinity. The remarkable flexibility of this method enables its applicability to various platforms. This review focuses on the applications of ribosome display technology in biomedical and agricultural fields in the generation of recombinant scFvs for disease diagnostics and control.

Directed evolution of custom polymerases using droplet microfluidics

DNA polymerases are critical tools for a large number of emerging applications in biotechnology, but oftentimes polymerases with desired functions are not readily available. Directed evolution provides a possible solution to this problem by enabling the creation of engineered polymerases that are better equipped to recognize a given unnatural substrate. Here we report a microfluidic-based method for evolving new polymerase functions that involves ultrahigh throughput sorting of fluorescent water-in-oil (w/o) microdroplets. The workflow entails the expression of a diverse population of polymerase variants in E. coli, production of microfluidic droplets containing one or less E. coli, bacteria lysis to release the polymerase and encoding plasmid into the surrounding droplet, a fluorescence-based activity assay to identify variants with a desired activity, isolation of fluorescent droplets using a fluorescence activated droplet sorting (FADS) device, and plasmid recovery with DNA sequencing to determine the identity of the functional variants. This technique is amenable to any type of unnatural nucleic acid and/or polymerase function, including DNA-templated synthesis, reverse transcription, and replication.

Parsimonious evolutionary scenario for the origin of allostery and coevolution patterns in proteins

Proteins display generic properties that are challenging to explain by direct selection, notably allostery, the capacity to be regulated through long-range effects, and evolvability, the capacity to adapt to new selective pressures. An evolutionary scenario is proposed where proteins acquire these two features indirectly as a by-product of their selection for a more fundamental property, exquisite discrimination, the capacity to bind discriminatively very similar ligands. Achieving this task is shown to typically require proteins to undergo a conformational change. We argue that physical and evolutionary constraints impel this change to be controlled by a group of sites extending from the binding site. Proteins can thus acquire a latent potential for allosteric regulation and evolutionary adaptation because of long-range effects that initially arise as evolutionary spandrels. This scenario accounts for the groups of conserved and coevolving residues observed in multiple sequence alignments. However, we propose that most pairs of coevolving and contacting residues inferred from such alignments have a different origin, related to thermal stability. A physical model is presented that illustrates this evolutionary scenario and its implications. The scenario can be implemented in experiments of protein evolution to directly test its predictions.

Recent insights into the genotype-phenotype relationship from massively parallel genetic assays

With the molecular revolution in Biology, a mechanistic understanding of the genotype-phenotype relationship became possible. Recently, advances in DNA synthesis and sequencing have enabled the development of deep mutational scanning assays, capable of scoring comprehensive libraries of genotypes for fitness and a variety of phenotypes in massively parallel fashion. The resulting empirical genotype-fitness maps pave the way to predictive models, potentially accelerating our ability to anticipate the behaviour of pathogen and cancerous cell populations from sequencing data. Besides from cellular fitness, phenotypes of direct application in industry (e.g. enzyme activity) and medicine (e.g. antibody binding) can be quantified and even selected directly by these assays. This review discusses the technological basis of and recent developments in massively parallel genetics, along with the trends it is uncovering in the genotype-phenotype relationship (distribution of mutation effects, epistasis), their possible mechanistic bases and future directions for advancing towards the goal of predictive genetics.

Phage Display in the Quest for New Selective Recognition Elements for Biosensors

Phages are bacterial viruses that have gained a significant role in biotechnology owing to their widely studied biology and many advantageous characteristics. Perhaps the best-known application of phages is phage display that refers to the expression of foreign peptides or proteins outside the phage virion as a fusion with one of the phage coat proteins. In 2018, one half of the Nobel prize in chemistry was awarded jointly to George P. Smith and Sir Gregory P. Winter "for the phage display of peptides and antibodies." The outstanding technology has evolved and developed considerably since its first description in 1985, and today phage display is commonly used in a wide variety of disciplines, including drug discovery, enzyme optimization, biomolecular interaction studies, as well as biosensor development. A cornerstone of all biosensors, regardless of the sensor platform or transduction scheme used, is a sensitive and selective bioreceptor, or a recognition element, that can provide specific binding to the target analyte. Many environmentally or pharmacologically interesting target analytes might not have naturally appropriate binding partners for biosensor development, but phage display can facilitate the production of novel receptors beyond known biomolecular interactions, or against toxic or nonimmunogenic targets, making the technology a valuable tool in the quest of new recognition elements for biosensor development.

Large-Scale, Quantitative Protein Assays on a High-Throughput DNA Sequencing Chip

High-throughput DNA sequencing techniques have enabled diverse approaches for linking DNA sequence to biochemical function. In contrast, assays of protein function have substantial limitations in terms of throughput, automation, and widespread availability. We have adapted an Illumina high-throughput sequencing chip to display an immense diversity of ribosomally translated proteins and peptides and then carried out fluorescence-based functional assays directly on this flow cell, demonstrating that a single, widely available high-throughput platform can perform both sequencing-by-synthesis and protein assays. We quantified the binding of the M2 anti-FLAG antibody to a library of 1.3 × 10⁴ variant FLAG peptides, exploring non-additive effects of combinations of mutations and discovering a "superFLAG" epitope variant. We also measured the enzymatic activity of 1.56 × 10⁵ molecular variants of full-length human O⁶-alkylguanine-DNA alkyltransferase (SNAP-tag). This comprehensive corpus of catalytic rates revealed amino acid interaction networks and cooperativity, linked positive cooperativity to structural proximity, and revealed ubiquitous positively cooperative interactions with histidine residues.

Immune repertoire mining for rapid affinity optimization of mouse monoclonal antibodies

Traditional hybridoma and B cell cloning antibody discovery platforms have inherent limits in immune repertoire sampling depth. One consequence is that monoclonal antibody (mAb) leads often lack the necessary affinity for therapeutic applications, thus requiring labor-intensive and time-consuming affinity in vitro engineering optimization steps. Here, we show that high-affinity variants of mouse-derived mAbs can be rapidly obtained by testing of somatic sequence variants obtained by deep sequencing of antibody variable regions in immune repertories from immunized mice, even with a relatively sparse sampling of sequence variants from large sequence datasets. Affinity improvements can be achieved for mAbs with a wide range of affinities. The optimized antibody variants derived from immune repertoire mining have no detectable in vitro off-target binding and have in vivo clearance comparable to the parental mAbs, essential properties in therapeutic antibody leads. As generation of antibody variants in vitro is replaced by mining of variants generated in vivo, the procedure can be applied to rapidly identify affinity-optimized mAb variants.

Dimerization of a ubiquitin variant leads to high affinity interactions with a ubiquitin interacting motif

We previously described structural and functional characterization of the first ubiquitin variant (UbV), UbV.v27.1, engineered by phage display to bind with high affinity to a specific ubiquitin interacting motif (UIM). We identified two substitutions relative to ubiquitin (Gly10Val/His68Tyr) that were critical for enhancing binding affinity but could only rationalize the mechanism of action of the Tyr68 substitution. Here, we extend our characterization and uncover the mechanism by which the Val10 substitution enhances binding affinity. We show that Val10 in UbV.v27.1 drives UbV dimerization through an intermolecular β-strand exchange. Dimerization serves to increase the contact surface between the UIM and UbV and also affords direct contacts between two UIMs through an overall 2:2 binding stoichiometry. Our identification of the role of Val10 in UbV dimerization suggests a general means for the development of dimeric UbVs with improved affinity and specificity relative to their monomeric UbV counterparts. Statement: Previously, we used phage display to engineer a UbV that bound tightly and specifically to a UIM. Here, we discovered that tight binding is partly due to the dimerization of the UbV, which increases the contact surface between the UbV and UIM. We show that UbV dimerization is dependent on the Gly10Val substitution, and posit that dimerization may provide a general means for engineering UbVs with improved binding properties.

Round optimization for improved discovery of native bispecific antibodies

The assembly of bispecific antibodies (bsAb) that retain the structure of a standard IgG can be challenging as the correct pairing of the different heavy and light chains has to be ensured while unwanted side products kept to a minimum. The use of antibodies sharing a common chain facilitates assembly of such bsAb formats but requires additional efforts during the initial discovery phase. We have developed a native bsAb format called κλ body based on antibodies that, while being specific for different antigens, share the same heavy chain. Such antibodies can readily be isolated from antibody libraries incorporating a single VH combined with light chain diversity. However, in order to improve the discovery process of such fixed VH antibodies, we developed a method to optimize populations of light chains by recovering and shuffling CDRL3 sequences that have been enriched for antigen binding by phage display selection. This approach allowed for the isolation of a more diverse and potent panel of antibodies blocking the interaction between PD-1 and PD-L1 when compared to our standard in vitro selection approach, thus providing better building blocks for subsequent bsAb generation.

Selectivity Conversion of Protease Inhibitory Antibodies

Background: Proteases are one of the largest pharmaceutical targets for drug developments. Their dysregulations result in a wide variety of diseases. Because proteolytic networks usually consist of protease family members that share high structural and catalytic homology, distinguishing them using small molecule inhibitors is often challenging. To achieve specific inhibition, this study described a novel approach for the generation of protease inhibitory antibodies. As a proof of concept, we aimed to convert a matrix metalloproteinase (MMP)-14 specific inhibitor to MMP-9 specific inhibitory antibodies with high selectivity. Methods: An error-prone single-chain Fv (scFv) library of an MMP-14 inhibitor 3A2 was generated for yeast surface display. A dual-color competitive FACS was developed for selection on MMP-9 catalytic domain (cdMMP-9) and counter-selection on cdMMP-14 simultaneously, which were fused/conjugated with different fluorophores. Isolated MMP-9 inhibitory scFvs were biochemically characterized by inhibition assays on MMP-2/-9/-12/-14, proteolytic stability tests, inhibition mode determination, competitive ELISA with TIMP-2 (a native inhibitor of MMPs), and paratope mutagenesis assays. Results: We converted an MMP-14 specific inhibitor 3A2 into a panel of MMP-9 specific inhibitory antibodies with dramatic selectivity shifts of 690-4,500 folds. Isolated scFvs inhibited cdMMP-9 at nM potency with high selectivity over MMP-2/-12/-14 and exhibited decent proteolytic stability. Biochemical characterizations revealed that these scFvs were competitive inhibitors binding to cdMMP-9 near its reaction cleft via their CDR-H3s. Conclusions: This study developed a novel approach able to convert the selectivity of inhibitory antibodies among closely related protease family members. This methodology can be directly applied for mAbs inhibiting many proteases of biomedical importance.

Enriching Peptide Libraries for Binding Affinity and Specificity Through Computationally Directed Library Design

Peptide reagents with high affinity or specificity for their target protein interaction partner are of utility for many important applications. Optimization of peptide binding by screening large libraries is a proven and powerful approach. Libraries designed to be enriched in peptide sequences that are predicted to have desired affinity or specificity characteristics are more likely to yield success than random mutagenesis. We present a library optimization method in which the choice of amino acids to encode at each peptide position can be guided by available experimental data or structure-based predictions. We discuss how to use analysis of predicted library performance to inform rounds of library design. Finally, we include protocols for more complex library design procedures that consider the chemical diversity of the amino acids at each peptide position and optimize a library score based on a user-specified input model.

Biophysical and Sequence-Based Methods for Identifying Monovalent and Bivalent Antibodies with High Colloidal Stability

In vitro antibody discovery and/or affinity maturation are often performed using antibody fragments (Fabs), but most monovalent Fabs are reformatted as bivalent IgGs (monoclonal antibodies, mAbs) for therapeutic applications. One problem related to reformatting antibodies is that the bivalency of mAbs can lead to increased antibody self-association and poor biophysical properties (e.g., reduced antibody solubility and increased viscosity). Therefore, it is important to identify monovalent Fabs early in the discovery and/or optimization process that will display favorable biophysical properties when reformatted as bivalent mAbs. Here we demonstrate a facile approach for evaluating Fab self-association in a multivalent assay format that is capable of identifying antibodies with low self-association and favorable colloidal properties when reformatted as bivalent mAbs. Our approach (self-interaction nanoparticle spectroscopy, SINS) involves immobilizing Fabs on gold nanoparticles in a multivalent format (multiple Fabs per nanoparticle) and evaluating their self-association behavior via shifts in the plasmon wavelength or changes in the absorbance values. Importantly, we find that SINS measurements of Fab self-association are correlated with self-interaction measurements of bivalent mAbs and are useful for identifying antibodies with favorable biophysical properties. Moreover, the significant differences in the levels of self-association detected for Fabs and mAbs with similar frameworks can be largely explained by the physicochemical properties of the complementarity-determining regions (CDRs). Comparison of the properties of the CDRs in this study relative to those of approved therapeutic antibodies reveals several key factors (net charge, fraction of charged residues, and presence of self-interaction motifs) that strongly influence antibody self-association behavior. Increased positive charge in the CDRs was observed to correlate with increased risk of high self-association for the mAbs in this study and clinical-stage antibodies. We expect that these findings will be useful for improving the development of therapeutic antibodies that are well suited for high concentration applications.

Bioinspired recognition elements for mycotoxin sensors

Mycotoxins are low molecular weight molecules produced as secondary metabolites by filamentous fungi that can be found as natural contaminants in many foods and feeds. These toxins have been shown to have adverse effects on both human and animal health, and are the cause of significant economic losses worldwide. Sensors for mycotoxin analysis have traditionally applied elements of biological origin for the selective recognition purposes. However, since the 1970s there has been an exponential growth in the use of genetically engineered or synthetic biomimetic recognition elements that allow some of the limitations associated with the use of natural receptors for the analyses of these toxins to be circumvented. This review provides an overview of recent advances in the application of bioinspired recognition elements, including recombinant antibodies, peptides, aptamers, and molecularly imprinted polymers, to the development of sensors for mycotoxins based on different transduction elements. Graphical abstract Novel analytical methods based on bioinspired recognition elements, such as recombinant antibodies, peptides, aptamers, and molecularly imprinted polymers, can improve the detection of mycotoxins and provide better tools than their natural counterparts to ensure food safety.

A statistical framework for analyzing deep mutational scanning data

Deep mutational scanning is a widely used method for multiplex measurement of functional consequences of protein variants. We developed a new deep mutational scanning statistical model that generates error estimates for each measurement, capturing both sampling error and consistency between replicates. We apply our model to one novel and five published datasets comprising 243,732 variants and demonstrate its superiority in removing noisy variants and conducting hypothesis testing. Simulations show our model applies to scans based on cell growth or binding and handles common experimental errors. We implemented our model in Enrich2, software that can empower researchers analyzing deep mutational scanning data.

Chemically Modifying Viruses for Diverse Applications

Long fascinating to biologists, viruses offer nanometer-scale benchtops for building molecular-scale devices and materials. Viruses tolerate a wide range of chemical modifications including reaction conditions, pH values, and temperatures. Recent examples of nongenetic manipulation of viral surfaces have extended viruses into applications ranging from biomedical imaging, drug delivery, tissue regeneration, and biosensors to materials for catalysis and energy generation. Chemical reactions on the phage surface include both covalent and noncovalent modifications, including some applied in conjunction with genetic modifications. Here, we survey viruses chemically augmented with capabilities limited only by imagination.

Modeling and fitting protein-protein complexes to predict change of binding energy

It is possible to accurately and economically predict change in protein-protein interaction energy upon mutation (ΔΔG), when a high-resolution structure of the complex is available. This is of growing usefulness for design of high-affinity or otherwise modified binding proteins for therapeutic, diagnostic, industrial, and basic science applications. Recently the field has begun to pursue ΔΔG prediction for homology modeled complexes, but so far this has worked mostly for cases of high sequence identity. If the interacting proteins have been crystallized in free (uncomplexed) form, in a majority of cases it is possible to find a structurally similar complex which can be used as the basis for template-based modeling. We describe how to use MMB to create such models, and then use them to predict ΔΔG, using a dataset consisting of free target structures, co-crystallized template complexes with sequence identify with respect to the targets as low as 44%, and experimental ΔΔG measurements. We obtain similar results by fitting to a low-resolution Cryo-EM density map. Results suggest that other structural constraints may lead to a similar outcome, making the method even more broadly applicable.

Engineering growth factors for regenerative medicine applications

Growth factors are important morphogenetic proteins that instruct cell behavior and guide tissue repair and renewal. Although their therapeutic potential holds great promise in regenerative medicine applications, translation of growth factors into clinical treatments has been hindered by limitations including poor protein stability, low recombinant expression yield, and suboptimal efficacy. This review highlights current tools, technologies, and approaches to design integrated and effective growth factor-based therapies for regenerative medicine applications. The first section describes rational and combinatorial protein engineering approaches that have been utilized to improve growth factor stability, expression yield, biodistribution, and serum half-life, or alter their cell trafficking behavior or receptor binding affinity. The second section highlights elegant biomaterial-based systems, inspired by the natural extracellular matrix milieu, that have been developed for effective spatial and temporal delivery of growth factors to cell surface receptors. Although appearing distinct, these two approaches are highly complementary and involve principles of molecular design and engineering to be considered in parallel when developing optimal materials for clinical applications.

STATEMENT OF SIGNIFICANCE

Growth factors are promising therapeutic proteins that have the ability to modulate morphogenetic behaviors, including cell survival, proliferation, migration and differentiation. However, the translation of growth factors into clinical therapies has been hindered by properties such as poor protein stability, low recombinant expression yield, and non-physiological delivery, which lead to suboptimal efficacy and adverse side effects. To address these needs, researchers are employing clever molecular and material engineering and design strategies to both improve the intrinsic properties of growth factors and effectively control their delivery into tissue. This review highlights examples of interdisciplinary tools and technologies used to augment the therapeutic potential of growth factors for clinical applications in regenerative medicine.

Recent Advances Toward the Discovery of Drug-Like Peptides De novo

Peptides are important natural molecules that possess functions as diverse as antibiotics, toxins, venoms and hormones, for example. However, whilst these peptides have useful properties, there are many targets and pathways that are not addressed through the activities of natural peptidic compounds. In these circumstances, directed evolution techniques, such as phage display, have been developed to sample the diverse chemical and structural repertoire of small peptides for useful means. In this review, we consider recent concepts that relate peptide structure to drug-like attributes and how these are incorporated within display technologies to deliver peptides de novo with valuable pharmaceutical properties.

Streamlining the Pipeline for Generation of Recombinant Affinity Reagents by Integrating the Affinity Maturation Step

Often when generating recombinant affinity reagents to a target, one singles out an individual binder, constructs a secondary library of variants, and affinity selects a tighter or more specific binder. To enhance the throughput of this general approach, we have developed a more integrated strategy where the "affinity maturation" step is part of the phage-display pipeline, rather than a follow-on process. In our new schema, we perform two rounds of affinity selection, followed by error-prone PCR on the pools of recovered clones, generation of secondary libraries, and three additional rounds of affinity selection, under conditions of off-rate competition. We demonstrate the utility of this approach by generating low nanomolar fibronectin type III (FN3) monobodies to five human proteins: ubiquitin-conjugating enzyme E2 R1 (CDC34), COP9 signalosome complex subunit 5 (COPS5), mitogen-activated protein kinase kinase 5 (MAP2K5), Splicing factor 3A subunit 1 (SF3A1) and ubiquitin carboxyl-terminal hydrolase 11 (USP11). The affinities of the resulting monobodies are typically in the single-digit nanomolar range. We demonstrate the utility of two binders by pulling down the targets from a spiked lysate of HeLa cells. This integrated approach should be applicable to directed evolution of any phage-displayed affinity reagent scaffold.

Biosensing with Virus Electrode Hybrids

Virus electrodes address two major challenges associated with biosensing. First, the surface of the viruses can be readily tailored for specific, high affinity binding to targeted biomarkers. Second, the viruses are entrapped in a conducting polymer for electrical resistance-based, quantitative measurement of biomarker concentration. To further enhance device sensitivity, two different ligands can be attached to the virus surface, and increase the apparent affinity for the biomarker. In the example presented here, the two ligands bind to the analyte in a bidentate binding mode with a chelate-based avidity effect, and result in a 100 pM experimentally observed limit of detection for the cancer biomarker prostate-specific membrane antigen. The approach does not require enzymatic amplification, and allows reagent-free, real-time measurements. This article presents general protocols for the development of such biosensors with modified viruses for the enhanced detection of arbitrary target proteins.

Engineering Novel and Improved Biocatalysts by Cell Surface Display

Biocatalysts, especially enzymes, have the ability to catalyze reactions with high product selectivity, utilize a broad range of substrates, and maintain activity at low temperature and pressure. Therefore, they represent a renewable, environmentally friendly alternative to conventional catalysts. Most current industrial-scale chemical production processes using biocatalysts employ soluble enzymes or whole cells expressing intracellular enzymes. Cell surface display systems differ by presenting heterologous enzymes extracellularly, overcoming some of the limitations associated with enzyme purification and substrate transport. Additionally, coupled with directed evolution, cell surface display is a powerful platform for engineering enzymes with enhanced properties. In this review, we will introduce the molecular and cellular principles of cell surface display and discuss how it has been applied to engineer enzymes with improved properties as well as to develop surface-engineered microbes as whole-cell biocatalysts.

Advances in phage display technology for drug discovery

INTRODUCTION

Over the past decade, several library-based methods have been developed to discover ligands with strong binding affinities for their targets. These methods mimic the natural evolution for screening and identifying ligand-target interactions with specific functional properties. Phage display technology is a well-established method that has been applied to many technological challenges including novel drug discovery.

AREAS COVERED

This review describes the recent advances in the use of phage display technology for discovering novel bioactive compounds. Furthermore, it discusses the application of this technology to produce proteins and peptides as well as minimize the use of antibodies, such as antigen-binding fragment, single-chain fragment variable or single-domain antibody fragments like VHHs.

EXPERT OPINION

Advances in screening, manufacturing and humanization technologies demonstrate that phage display derived products can play a significant role in the diagnosis and treatment of disease. The effects of this technology are inevitable in the development pipeline for bringing therapeutics into the market, and this number is expected to rise significantly in the future as new advances continue to take place in display methods. Furthermore, a widespread application of this methodology is predicted in different medical technological areas, including biosensing, monitoring, molecular imaging, gene therapy, vaccine development and nanotechnology.

Insights into cytokine-receptor interactions from cytokine engineering

Cytokines exert a vast array of immunoregulatory actions critical to human biology and disease. However, the desired immunotherapeutic effects of native cytokines are often mitigated by toxicity or lack of efficacy, either of which results from cytokine receptor pleiotropy and/or undesired activation of off-target cells. As our understanding of the structural principles of cytokine-receptor interactions has advanced, mechanism-based manipulation of cytokine signaling through protein engineering has become an increasingly feasible and powerful approach. Modified cytokines, both agonists and antagonists, have been engineered with narrowed target cell specificities, and they have also yielded important mechanistic insights into cytokine biology and signaling. Here we review the theory and practice of cytokine engineering and rationalize the mechanisms of several engineered cytokines in the context of structure. We discuss specific examples of how structure-based cytokine engineering has opened new opportunities for cytokines as drugs, with a focus on the immunotherapeutic cytokines interferon, interleukin-2, and interleukin-4.

Desired alteration of protein affinities: competitive selection of protein variants using yeast signal transduction machinery

Molecules that can control protein-protein interactions (PPIs) have recently drawn attention as new drug pipeline compounds. Here, we report a technique to screen desirable affinity-altered (affinity-enhanced and affinity-attenuated) protein variants. We previously constructed a screening system based on a target protein fused to a mutated G-protein γ subunit (Gγcyto) lacking membrane localization ability. This ability, required for signal transmission, is restored by recruiting Gγcyto into the membrane only when the target protein interacts with an artificially membrane-anchored candidate protein, thereby allowing interacting partners (Gγ recruitment system) to be searched and identified. In the present study, the Gγ recruitment system was altered by integrating the cytosolic expression of a third protein as a competitor to set a desirable affinity threshold. This enabled the reliable selection of both affinity-enhanced and affinity-attenuated protein variants. The presented approach may facilitate the development of therapeutic proteins that allow the control of PPIs.

Measuring the activity of protein variants on a large scale using deep mutational scanning

Deep mutational scanning marries selection for protein function to high-throughput DNA sequencing in order to quantify the activity of variants of a protein on a massive scale. First, an appropriate selection system for the protein function of interest is identified and validated. Second, a library of variants is created, introduced into the selection system and subjected to selection. Third, library DNA is recovered throughout the selection and deep-sequenced. Finally, a functional score for each variant is calculated on the basis of the change in the frequency of the variant during the selection. This protocol describes the steps that must be carried out to generate a large-scale mutagenesis data set consisting of functional scores for up to hundreds of thousands of variants of a protein of interest. Establishing an assay, generating a library of variants and carrying out a selection and its accompanying sequencing takes on the order of 4-6 weeks; the initial data analysis can be completed in 1 week.

Dual genetically encoded phage-displayed ligands

M13 bacteriophage display presents polypeptides as fusions to phage coat proteins. Such phage-displayed ligands offer useful reagents for biosensors. Here, we report a modified phage propagation protocol for the consistent and robust display of two different genetically encoded ligands on the major coat protein, P8. The results demonstrate that the phage surface reaches a saturation point for maximum peptide display.

A non-heme cationic Fe(iii)-complex intercalated in montmorillonite K-10: synthesis, characterization and catalytic alkane hydroxylation with H2O2 at room temperature

An efficient catalyst for highly selective hydroxylation of alkanes with environmentally benign H₂O₂ at room temperature has been designed by the intercalation of a non-heme iron(iii) complex into smectite montmorillonite K-10.

Improvement of biocatalysts for industrial and environmental purposes by saturation mutagenesis

Laboratory evolution techniques are becoming increasingly widespread among protein engineers for the development of novel and designed biocatalysts. The palette of different approaches ranges from complete randomized strategies to rational and structure-guided mutagenesis, with a wide variety of costs, impacts, drawbacks and relevance to biotechnology. A technique that convincingly compromises the extremes of fully randomized vs. rational mutagenesis, with a high benefit/cost ratio, is saturation mutagenesis. Here we will present and discuss this approach in its many facets, also tackling the issue of randomization, statistical evaluation of library completeness and throughput efficiency of screening methods. Successful recent applications covering different classes of enzymes will be presented referring to the literature and to research lines pursued in our group. The focus is put on saturation mutagenesis as a tool for designing novel biocatalysts specifically relevant to production of fine chemicals for improving bulk enzymes for industry and engineering technical enzymes involved in treatment of waste, detoxification and production of clean energy from renewable sources.

Sub-nanomolar detection of prostate-specific membrane antigen in synthetic urine by synergistic, dual-ligand phage

The sensitive detection of cancer biomarkers in urine could revolutionize cancer diagnosis and treatment. Such detectors must be inexpensive, easy to interpret, and sensitive. This report describes a bioaffinity matrix of viruses integrated into PEDOT films for electrochemical sensing of prostate-specific membrane antigen (PSMA), a prostate cancer biomarker. High sensitivity to PSMA resulted from synergistic action by two different ligands to PSMA on the same phage particle. One ligand was genetically encoded, and the secondary recognition ligand was chemically synthesized to wrap around the phage. The dual ligands result in a bidentate binder with high-copy, dense ligand display for enhanced PSMA detection through a chelate-based avidity effect. Biosensing with virus-PEDOT films provides a 100 pM limit of detection for PSMA in synthetic urine without requiring enzymatic or other amplification.

Evolution in microfluidic droplet

High-throughput screening (HTS) of enzymatic activity is important for directed evolution-based enzyme engineering. However, substrate and product diffusion can severely compromise these HTS assays. In this issue of Chemistry & Biology, Kintses and coworkers describe a microfluidic platform for the directed evolution of enzymes in droplets that allows for the screening of 10(7) mutants per round of evolution.

Engineering protein therapeutics: predictive performances of a structure-based virtual affinity maturation protocol

The implementation of a structure based virtual affinity maturation protocol and evaluation of its predictivity are presented. The in silico protocol is based on conformational sampling of the interface residues (using the Dead End Elimination/A* algorithm), followed by the estimation of the change of free energy of binding due to a point mutation, applying MM/PBSA calculations. Several implementations of the protocol have been evaluated for 173 mutations in 7 different protein complexes for which experimental data were available: the use of the Boltzamnn averaged predictor based on the free energy of binding (ΔΔG(*)) combined with the one based on its polar component only (ΔΔE(pol*)) led to the proposal of a subset of mutations out of which 45% would have successfully enhanced the binding. When focusing on those mutations that are less likely to be introduced by natural in vivo maturation methods (99 mutations with at least two base changes in the codon), the success rate is increased to 63%. In another evaluation, focusing on 56 alanine scanning mutations, the in silico protocol was able to detect 89% of the hot-spots.

Designing specific protein-protein interactions using computation, experimental library screening, or integrated methods

Given the importance of protein-protein interactions for nearly all biological processes, the design of protein affinity reagents for use in research, diagnosis or therapy is an important endeavor. Engineered proteins would ideally have high specificities for their intended targets, but achieving interaction specificity by design can be challenging. There are two major approaches to protein design or redesign. Most commonly, proteins and peptides are engineered using experimental library screening and/or in vitro evolution. An alternative approach involves using protein structure and computational modeling to rationally choose sequences predicted to have desirable properties. Computational design has successfully produced novel proteins with enhanced stability, desired interactions and enzymatic function. Here we review the strengths and limitations of experimental library screening and computational structure-based design, giving examples where these methods have been applied to designing protein interaction specificity. We highlight recent studies that demonstrate strategies for combining computational modeling with library screening. The computational methods provide focused libraries predicted to be enriched in sequences with the properties of interest. Such integrated approaches represent a promising way to increase the efficiency of protein design and to engineer complex functionality such as interaction specificity.

Peptide discovery using bacterial display and flow cytometry

Peptides are increasingly used as therapeutic and diagnostic agents. The combination of bacterial cell-surface display peptide libraries with magnetic- and fluorescence-activated cell sorting technologies provides an efficient and highly effective methodology to identify and engineer peptides for a growing number of molecular recognition applications. Here, detailed protocols for both the generation and screening of bacterial display peptide libraries are presented. The methods described enable the discovery and evolutionary optimization of protein-binding peptides, cell-specific peptides, and enzyme substrates for diverse biotechnology applications.

Ribosome display: a perspective

Ribosome display is an in vitro evolution technology for proteins. It is based on in vitro translation, but prevents the newly synthesized protein and the mRNA encoding it from leaving the ribosome. It thereby couples phenotype and genotype. Since no cells need to be transformed, very large libraries can be used directly in selections, and the in vitro amplification provides a very convenient integration of random mutagenesis that can be incorporated into the procedure. This review highlights concepts, mechanisms, and different variations of ribosome display and compares it to related methods. Applications of ribosome display are summarized, e.g., the directed evolution of proteins for higher binding affinity, for higher stability or other improved biophysical parameters and enzymatic properties. Ribosome display has developed into a robust technology used in academia and industry alike, and it has made the cell-free Darwinian evolution of proteins over multiple generations a reality.

Screening of peptide libraries against protective antigen of Bacillus anthracis in a disposable microfluidic cartridge

Bacterial surface peptide display has gained popularity as a method of affinity reagent generation for a wide variety of applications ranging from drug discovery to pathogen detection. In order to isolate the bacterial clones that express peptides with high affinities to the target molecule, multiple rounds of manual magnetic activated cell sorting (MACS) followed by multiple rounds of fluorescence activated cell sorting (FACS) are conventionally used. Although such manual methods are effective, alternative means of library screening which improve the reproducibility, reduce the cost, reduce cross contamination, and minimize exposure to hazardous target materials are highly desired for practical application. Toward this end, we report the first semi-automated system demonstrating the potential for screening bacterially displayed peptides using disposable microfluidic cartridges. The Micro-Magnetic Separation platform (MMS) is capable of screening a bacterial library containing 3 × 10¹⁰ members in 15 minutes and requires minimal operator training. Using this system, we report the isolation of twenty-four distinct peptide ligands that bind to the protective antigen (PA) of Bacilus anthracis in three rounds of selection. A consensus motif WXCFTC was found using the MMS and was also found in one of the PA binders isolated by the conventional MACS/FACS approach. We compared MMS and MACS rare cell recovery over cell populations ranging from 0.1% to 0.0000001% and found that both magnetic sorting methods could recover cells down to 0.0000001% initial cell population, with the MMS having overall lower standard deviation of cell recovery. We believe the MMS system offers a compelling approach towards highly efficient, semi-automated screening of molecular libraries that is at least equal to manual magnetic sorting methods and produced, for the first time, 15-mer peptide binders to PA protein that exhibit better affinity and specificity than peptides isolated using conventional MACS/FACS.