The nature of target-unrelated peptides recovered in the screening of phage-displayed random peptide libraries with antibodies

Bioinformatics tools and experimental analysis combination for production of specific scFv against CD133

Prominin-1, or CD133, is a membrane-bound pentaspan protein that has been utilized recently to identify cancer stem cells (CSCs) in a variety of carcinomas. Today, bioinformatics offers a potent tool for studying the structural and functional relationships of fusion proteins. A structure-activity relationship model based on physicochemical characteristics, biological functions of single-chain antibodies, and molecular conformation can be developed by the integration of biomolecular computer models with biological experiments. In the present study, a mice library of single-chain variable fragment (scFv) antibodies was developed by mRNA extracted from mice immunized for the efficient and specific identification of the N-terminal domain of recombinant CD133 (D-EC1). First, a part of sequences of the scFvs library were cloned in the T.vector and sequenced. Then, bioinformatics was used to select the scFvs with high affinity by molecular dynamics simulations and docking. Based on bioinformatics analysis, three scFvs were cloned and expressed. Finally, the ability of the selected scFv was confirmed with the indirect enzyme-linked immunosorbent assay (ELISA) and immunocytochemistry (ICC). ELISA data showed that scFv3 had a greater affinity for the N-terminal of recombinant CD133, and it was selected for the immunocytochemistry (ICC) analysis. The immunocytochemistry experiments confirmed that the obtained scFv could bind to the CD133-expressing HT-29 cells. Our results suggest that using bioinformatics tools could be applied as a new, rapid, and valid method for the design and development of antibodies with improved properties. The selected scFv may be successfully applied in scFv-based diagnostics and therapeutics.

Microfluidics, an effective tool for supporting phage display-A review

Phage display is a vital tool for the discovery and development of affinity reagents such as antibodies and peptides, which have great potential in imaging, molecular recognition, biosensors, targeted delivery and other clinical applications. However, affinity reagents obtained by phage display are often subjected to a process called biopanning, which is considered time-consuming, labor-intensive and lacks accurate control, limiting the acquisition of high-quality affinity reagents. Over the last two decades, several microfluidic approaches have been designed to simplify the conventional biopanning process and to realize precise control. To better understand the advantages of microfluidics over traditional biopanning and the potential of microfluidics for other molecular screening strategies, we provided an overview of recent applications of microfluidics in phage display. Additionally, the next challenges and outlooks are discussed.

Using NGS to Uncover the Corruption of a Peptide Phage Display Selection

Phage display has been widely used to identify peptides binding to a variety of biological targets. In the current work, we planned to select novel peptides targeting CD4 through screening of a commercial phage display library (New England Biolabs Ph.D.TM-7). After three rounds of biopanning, 57 phage clones were Sanger-sequenced. These clones represented 30 unique peptide sequences, which were subjected to phage ELISA, resulting in the identification of two potential target binders. Following peptide synthesis, downstream characterization was conducted using fluorescence plate-based assay, flow cytometry, SPR, and confocal microscopy. The results revealed that neither of the peptides identified in the Sanger-based phage display selection exhibited specific binding toward CD4. The naïve library and the phage pool recovered from the third round of biopanning were then subjected to next-generation sequencing (NGS). The results of NGS indicated corruption of the selection output by a phage already known as a fast-propagating clone whose target-unrelated enrichment can shed light on the misidentification of target-binding peptides through phage display. This work provides an in-depth insight into some of the challenges encountered in peptide phage display selection. Furthermore, our data highlight that NGS, by exploring a broader sequence space and providing a more precise picture of the composition of biopanning output, can be used to refine the selection protocol and avoid misleading the process of ligand identification. We hope that these findings can describe some of the complexities of phage display selection and offer help to fellow researchers who have faced similar situations.

Principles of Affinity Selection

The most common application of phage-display technology is the discovery of peptides or proteins that specifically bind some molecule or other substance of interest-for example, antibodies that specifically bind an antigen. The discovery process starts with a library encompassing a very large array of proteins or peptides with a great diversity of binding specificities-for example, single-chain antibodies with a great diversity of antigen-binding sites. Each member of the array is displayed on the surface of hundreds to billions of identical virus particles (virions) belonging to a single-phage clone; the library as a whole comprises millions to billions of such clones, all mixed together in a single vessel. Affinity selection is the process by which a molecule or substance of interest-generically called the selector-is used to select very rare clones in the library displaying proteins or peptides that happen to bind the selector with high affinity and selectivity. Here, I explain general principles guiding a successful affinity-selection project-principles grounded in phage biology, kinetics of reversible binding, technological advances, and the practical experience of thousands of investigators around the globe.

In vivo phage display identifies novel peptides for cardiac targeting

Heart failure remains a leading cause of mortality. Therapeutic intervention for heart failure would benefit from targeted delivery to the damaged heart tissue. Here, we applied in vivo peptide phage display coupled with high-throughput Next-Generation Sequencing (NGS) and identified peptides specifically targeting damaged cardiac tissue. We established a bioinformatics pipeline for the identification of cardiac targeting peptides. Hit peptides demonstrated preferential uptake by human induced pluripotent stem cell (iPSC)-derived cardiomyocytes and immortalized mouse HL1 cardiomyocytes, without substantial uptake in human liver HepG2 cells. These novel peptides hold promise for use in targeted drug delivery and regenerative strategies and open new avenues in cardiovascular research and clinical practice.

Identification of yttrium oxide-specific peptides for future recycling of rare earth elements from electronic scrap

Yttrium is a heavy rare earth element (REE) that acquires remarkable characteristics when it is in oxide form and doped with other REEs. Owing to these characteristics Y2 O3 can be used in the manufacture of several products. However, a supply deficit of this mineral is expected in the coming years, contributing to its price fluctuation. Thus, developing an efficient, cost-effective, and eco-friendly process to recover Y2 O3 from secondary sources has become necessary. In this study, we used phage surface display to screen peptides with high specificity for Y2 O3 particles. After three rounds of enrichment, a phage expressing the peptide TRTGCHVPRCNTLS (DM39) from the random pVIII phage peptide library Cys4 was found to bind specifically to Y2 O3 , being 531.6-fold more efficient than the wild-type phage. The phage DM39 contains two arginines in the polar side chains, which may have contributed to the interaction between the mineral targets. Immunofluorescence assays identified that the peptide's affinity was strong for Y2 O3 and negligible to LaPO4 :Ce3+ ,Tb3+ . The identification of a peptide with high specificity and affinity for Y2 O3 provides a potentially new strategic approach to recycle this type of material from secondary sources, especially from electronic scrap.

Effects of the Magnetic Orientation of M13 Bacteriophage on Phage Display Selection

Although phage display selection using a library of M13 bacteriophage has become a powerful tool for finding peptides that bind to target materials on demand, a remaining concern of this method is the interference by the M13 main body, which is a huge filament >103  times larger than the displayed peptide, and therefore would nonspecifically adhere to the target or sterically inhibit the binding of the displayed peptide. Meanwhile, filamentous phages are known to be orientable by an external magnetic field. If M13 filaments are magnetically oriented during the library selection, their angular arrangement relative to the target surface would be changed, being expected to control the interference by the M13 main body. This study reports that the magnetic orientation of M13 filaments vertical to the target surface significantly affects the selection. When the target surface was affinitive to the M13 main body, this orientation notably suppressed the nonspecific adhesion. Furthermore, when the target surface was less affinitive to the M13 main body and intrinsically free from the nonspecific adhesion, this orientation drastically changed the population of M13 clones obtained through library selection. The method of using no chemicals but only a physical stimulus is simple, clean, and expected to expand the scope of phage display selection.

Gold nanoparticles-anchored peptides enable precise colorimetric estimation of microplastics

Microplastics (MPs, particle size < 5 mm) are an emerging contaminant in aquatic environment, which have attracted increasing attention worldwide. In this study, a colorimetric method for MPs detection was developed based on gold nanoparticles (AuNPs)-anchored peptides (LCI or TA2), which are able to specifically recognize and adhere to polypropylene (PP) or polystyrene (PS). The AuNPs-anchored peptides accumulated on the surface of MPs, rendering a color change from red to gray-blue and transforming the surface plasmon absorption intensity and wavelength. The designed method presented high selectivity, stability, and reproducibility, with a detection range of 2.5-15 μg/mL. The results demonstrated that the developed approach will be valuable in the precise, facile, and cost-effective estimation of MPs in different matrices, regulating the control over MPs pollution and its hazardous impact on health and ecosystems.

Sequence enrichment profiles enable target-agnostic antibody generation for a broad range of antigens

Phenotypic drug discovery (PDD) enables the target-agnostic generation of therapeutic drugs with novel mechanisms of action. However, realizing its full potential for biologics discovery requires new technologies to produce antibodies to all, a priori unknown, disease-associated biomolecules. We present a methodology that helps achieve this by integrating computational modeling, differential antibody display selection, and massive parallel sequencing. The method uses the law of mass action-based computational modeling to optimize antibody display selection and, by matching computationally modeled and experimentally selected sequence enrichment profiles, predict which antibody sequences encode specificity for disease-associated biomolecules. Applied to a phage display antibody library and cell-based antibody selection, ∼105 antibody sequences encoding specificity for tumor cell surface receptors expressed at 103-106 receptors/cell were discovered. We anticipate that this approach will be broadly applicable to molecular libraries coupling genotype to phenotype and to the screening of complex antigen populations for identification of antibodies to unknown disease-associated targets.

Recent Advances on Peptide-Based Biosensors and Electronic Noses for Foodborne Pathogen Detection

Foodborne pathogens present a serious issue around the world due to the remarkably high number of illnesses they cause every year. In an effort to narrow the gap between monitoring needs and currently implemented classical detection methodologies, the last decades have seen an increased development of highly accurate and reliable biosensors. Peptides as recognition biomolecules have been explored to develop biosensors that combine simple sample preparation and enhanced detection of bacterial pathogens in food. This review first focuses on the selection strategies for the design and screening of sensitive peptide bioreceptors, such as the isolation of natural antimicrobial peptides (AMPs) from living organisms, the screening of peptides by phage display and the use of in silico tools. Subsequently, an overview on the state-of-the-art techniques in the development of peptide-based biosensors for foodborne pathogen detection based on various transduction systems was given. Additionally, limitations in classical detection strategies have led to the development of innovative approaches for food monitoring, such as electronic noses, as promising alternatives. The use of peptide receptors in electronic noses is a growing field and the recent advances of such systems for foodborne pathogen detection are presented. All these biosensors and electronic noses are promising alternatives for the pathogen detection with high sensitivity, low cost and rapid response, and some of them are potential portable devices for on-site analyses.

Combination of Experimental and Bioinformatic Approaches for Identification of Immunologically Relevant Protein-Peptide Interactions

Protein-peptide interactions are an essential player in cellular processes and, thus, of great interest as potential therapeutic agents. However, identifying the protein's interacting surface has been shown to be a challenging task. Here, we present a methodology for protein-peptide interaction identification, implementing phage panning, next-generation sequencing and bioinformatic analysis. One of the uses of this methodology is identification of allergen epitopes, especially suitable for globular inhaled and venom allergens, where their binding capability is determined by the allergen's conformation, meaning their interaction cannot be properly studied when denatured. A Ph.D. commercial system based on the M13 phage vector was used for the panning process. Utilization of various bioinformatic tools, such as PuLSE, SAROTUP, MEME, Hammock and Pepitope, allowed us to evaluate a large amount of obtained data. Using the described methodology, we identified three peptide clusters representing potential epitopes on the major wasp venom allergen Ves v 5.

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

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

Identification of a novel colon adenocarcinoma cell targeting peptide using phage display library biopanning

Phage display is well recognized as a promising high-throughput screening tool for the discovery of novel cancer-targeting peptides. Here, we screened a phage display library of 7-mer random peptides through in vitro biopanning to isolate peptide ligands binding to SW480 human colon adenocarcinoma cells. Three rounds of negative and positive selection caused a remarkable enrichment of colon cancer cell-binding phage clones with a significant enhancement of phage recovery efficiency (about 157-fold). A number of phage clones were picked out from the eluted phages of last selection round and sequenced. According to the results of cell binding assay and phage cell-based ELISA, one of the isolated peptides denoted as CCBP1 (with the sequence HAMRAQP) was indicated to have the highest binding efficiency, selectivity, and specificity toward colon cancer cells with no significant binding to control cells. Peptide competitive inhibition assay revealed that binding of the phage-displayed CCBP1 is competitively inhibited by the same free peptide, suggesting that CCBP1 specific binding to the target cell is independent of the phage context. Taken together, our findings provide support for the notion that CCBP1 binds specifically to colon cancer cells and might be a potential lead candidate for targeted delivery of imaging agents or therapeutic genes/drugs to colon tumors.

Advances of research of Fc-fusion protein that activate NK cells for tumor immunotherapy

The rapid development of bioengineering technology has introduced Fc-fusion proteins, representing a novel kind of recombinant protein, as promising biopharmaceutical products in tumor therapy. Numerous related anti-tumor Fc-fusion proteins have been investigated and are in different stages of development. Fc-fusion proteins are constructed by fusing the Fc-region of the antibody with functional proteins or peptides. They retain the bioactivity of the latter and partial properties of the former. This structural and functional advantage makes Fc-fusion proteins an effective tool in tumor immunotherapy, especially for the recruitment and activation of natural killer (NK) cells, which play a critical role in tumor immunotherapy. Even though tumor cells have developed mechanisms to circumvent the cytotoxic effect of NK cells or induce defective NK cells, Fc-fusion proteins have been proven to effectively activate NK cells to kill tumor cells in different ways, such as antibody-dependent cell-mediated cytotoxicity (ADCC), activate NK cells in different ways in order to promote killing of tumor cells. In this review, we focus on NK cell-based immunity for cancers and current research progress of the Fc-fusion proteins for anti-tumor therapy by activating NK cells.

A White Plaque, Associated with Genomic Deletion, Derived from M13KE-Based Peptide Library Is Enriched in a Target-Unrelated Manner during Phage Display Biopanning Due to Propagation Advantage

The nonspecific enrichment of target-unrelated peptides during biopanning remains a major drawback for phage display technology. The commercial Ph.D.^TM-7 phage display library is used extensively for peptide discovery. This library is based on the M13KE vector, which carries the lacZα sequence, leading to the formation of blue plaques on IPTG-X-gal agar plates. In the current study, we report the isolation of a fast-propagating white clone (displaying WSLGYTG peptide) identified through screening against a recombinant protein. Sanger sequencing demonstrated that white plaques are not contamination from environmental M13-like phages, but derive from the library itself. Whole genome sequencing revealed that the white color of the plaques results from a large 827-nucleotide genomic deletion. The phenotypic characterization of propagation capacity through plaque count- and NGS-based competitive propagation assay supported the higher propagation rate of Ph-WSLGYTG clone compared with the library. According to our data, white plaques are likely to arise endogenously in Ph.D. libraries due to mutations in the M13KE genome and should not always be viewed as exogenous contamination. Our findings also led to the conclusion that the deletion observed here might be an ancestral mutation already present in the naïve library, which causes target-unrelated nonspecific enrichment of white clone during biopanning due to propagation advantage.

Parallel evaluation of cell‑based phage display panning strategies: Optimized selection and depletion steps result in AML blast‑binding consensus antibodies

Phage display technology (PD) is a powerful technique for the generation of tumor-targeting antibodies. However, there are a number of different selection methods established in different laboratories around the world. Cell-based PD panning methods using primary tumor cells are particularly heterogeneous between laboratories, which can lead to inconsistent results. Therefore, the present study evaluated different cell-based PD selection methods regarding their potential to generate acute myeloid leukemia (AML) blast-binding antibodies. In addition to this evaluation, the present study improved the PD procedure by optimizing selection as well as depletion strategies. To the best of our knowledge, the current study demonstrated for the first time that antigen diversity during the depletion step is of importance for the enrichment of tumor-targeting phage antibodies. It is demonstrated that medium levels of depletion antigen diversity led to the most promising antibody candidates. In addition, it was determined that purification of blast cells from patients with AML by immunomagnetic separation ameliorated the selection of AML-binding phages during panning. Furthermore, suggesting a common design-related mechanism using a ‘single-pot’ PD library, such as the well-known Tomlinson single-chain fragment variable (scFv) library, the present study identified specific binding consensus phage particles in independent panning procedures. By means of these optimized strategies, four promising AML blast-binding phage particles were isolated and soluble scFv-Fc (scFv cloned to a fragment crystallizable of an IgG2a mouse antibody) fusion proteins were produced. These scFv-Fc antibodies bound the surface of AML blasts and were successfully internalized into their cytoplasm, indicating that they are potential immunoconjugate candidates for AML immunotherapy.

Streamlined phage display library protocols for identification of insect gut binding peptides highlight peptide specificity

Phage display libraries have been used to isolate insect gut binding peptides for use as pathogen transmission blocking agents, and to provide artificial anchors for increased toxicity of bacteria-derived pesticidal proteins. Previously, phage clones displaying enriched peptides were sequenced by Sanger sequencing. Here we present a streamlined protocol for identification of insect gut binding peptides, using insect-appropriate feeding strategies, with next generation sequencing and tailored bioinformatics analyses. The bioinformatics pipeline is designed to eliminate poorly enriched and false positive peptides, and to identify peptides predicted to be stable and hydrophilic. In addition to developing streamlined protocols, we also sought to address whether candidate gut binding peptides can bind to insects from more than one order, which is an important consideration for safe, practical use of peptide-modified pesticidal proteins. To this end, we screened phage display libraries for peptides that bind to the gut epithelia of two pest insects, the Asian citrus psyllid, Diaphorina citri (Hemiptera) and beet armyworm, Spodoptera exigua (Lepidoptera), and one beneficial insect, the western honey bee, Apis mellifera (Hymenoptera). While unique peptide sequences totaling 13,427 for D. citri, 89,561 for S. exigua and 69,053 for A. mellifera were identified from phage eluted from the surface of the insect guts, final candidate pools were comprised of 53, 107 and 1423 peptides respectively. The benefits of multiple rounds of biopanning, along with peptide binding properties in relation to practical use of peptide-modified pesticidal proteins for insect pest control are discussed.

Application of Next Generation Sequencing (NGS) in Phage Displayed Peptide Selection to Support the Identification of Arsenic-Binding Motifs

Next generation sequencing (NGS) in combination with phage surface display (PSD) are powerful tools in the newly equipped molecular biology toolbox for the identification of specific target binding biomolecules. Application of PSD led to the discovery of manifold ligands in clinical and material research. However, limitations of traditional phage display hinder the identification process. Growth-based library biases and target-unrelated peptides often result in the dominance of parasitic sequences and the collapse of library diversity. This study describes the effective enrichment of specific peptide motifs potentially binding to arsenic as proof-of-concept using the combination of PSD and NGS. Arsenic is an environmental toxin, which is applied in various semiconductors as gallium arsenide and selective recovery of this element is crucial for recycling and remediation. The development of biomolecules as specific arsenic-binding sorbents is a new approach for its recovery. Usage of NGS for all biopanning fractions allowed for evaluation of motif enrichment, in-depth insight into the selection process and the discrimination of biopanning artefacts, e.g., the amplification-induced library-wide reduction in hydrophobic amino acid proportion. Application of bioinformatics tools led to the identification of an SxHS and a carboxy-terminal QxQ motif, which are potentially involved in the binding of arsenic. To the best of our knowledge, this is the first report of PSD combined with NGS of all relevant biopanning fractions.

Phage Display Derived Monoclonal Antibodies: From Bench to Bedside

Monoclonal antibodies (mAbs) have become one of the most important classes of biopharmaceutical products, and they continue to dominate the universe of biopharmaceutical markets in terms of approval and sales. They are the most profitable single product class, where they represent six of the top ten selling drugs. At the beginning of the 1990s, an in vitro antibody selection technology known as antibody phage display was developed by John McCafferty and Sir. Gregory Winter that enabled the discovery of human antibodies for diverse applications, particularly antibody-based drugs. They created combinatorial antibody libraries on filamentous phage to be utilized for generating antigen specific antibodies in a matter of weeks. Since then, more than 70 phage–derived antibodies entered clinical studies and 14 of them have been approved. These antibodies are indicated for cancer, and non-cancer medical conditions, such as inflammatory, optical, infectious, or immunological diseases. This review will illustrate the utility of phage display as a powerful platform for therapeutic antibodies discovery and describe in detail all the approved mAbs derived from phage display.

Development and Application of Computational Methods in Phage Display Technology

BACKGROUND

Phage display is a powerful and versatile technology for the identification of peptide ligands binding to multiple targets, which has been successfully employed in various fields, such as diagnostics and therapeutics, drug-delivery and material science. The integration of next generation sequencing technology with phage display makes this methodology more productive. With the widespread use of this technique and the fast accumulation of phage display data, databases for these data and computational methods have become an indispensable part in this community. This review aims to summarize and discuss recent progress in the development and application of computational methods in the field of phage display.

METHODS

We undertook a comprehensive search of bioinformatics resources and computational methods for phage display data via Google Scholar and PubMed. The methods and tools were further divided into different categories according to their uses.

RESULTS

We described seven special or relevant databases for phage display data, which provided an evidence-based source for phage display researchers to clean their biopanning results. These databases can identify and report possible target-unrelated peptides (TUPs), thereby excluding false-positive data from peptides obtained from phage display screening experiments. More than 20 computational methods for analyzing biopanning data were also reviewed. These methods were classified into computational methods for reporting TUPs, for predicting epitopes and for analyzing next generation phage display data.

CONCLUSION

The current bioinformatics archives, methods and tools reviewed here have benefitted the biopanning community. To develop better or new computational tools, some promising directions are also discussed.

Phage Display Derived Monoclonal Antibodies: From Bench to Bedside

Monoclonal antibodies (mAbs) have become one of the most important classes of biopharmaceutical products, and they continue to dominate the universe of biopharmaceutical markets in terms of approval and sales. They are the most profitable single product class, where they represent six of the top ten selling drugs. At the beginning of the 1990s, an in vitro antibody selection technology known as antibody phage display was developed by John McCafferty and Sir. Gregory Winter that enabled the discovery of human antibodies for diverse applications, particularly antibody-based drugs. They created combinatorial antibody libraries on filamentous phage to be utilized for generating antigen specific antibodies in a matter of weeks. Since then, more than 70 phage-derived antibodies entered clinical studies and 14 of them have been approved. These antibodies are indicated for cancer, and non-cancer medical conditions, such as inflammatory, optical, infectious, or immunological diseases. This review will illustrate the utility of phage display as a powerful platform for therapeutic antibodies discovery and describe in detail all the approved mAbs derived from phage display.

PhD7Faster 2.0: predicting clones propagating faster from the Ph.D.-7 phage display library by coupling PseAAC and tripeptide composition

Selection from phage display libraries empowers isolation of high-affinity ligands for various targets. However, this method also identifies propagation-related target-unrelated peptides (PrTUPs). These false positive hits appear because of their amplification advantages. In this report, we present PhD7Faster 2.0 for predicting fast-propagating clones from the Ph.D.-7 phage display library, which was developed based on the support vector machine. Feature selection was performed against PseAAC and tripeptide composition using the incremental feature selection method. Ten-fold cross-validation results show that PhD7Faster 2.0 succeeds a decent performance with the accuracy of 81.84%, the Matthews correlation coefficient of 0.64 and the area under the ROC curve of 0.90. The permutation test with 1,000 shuffles resulted in p < 0.001. We implemented PhD7Faster 2.0 into a publicly accessible web tool (http://i.uestc.edu.cn/sarotup3/cgi-bin/PhD7Faster.pl) and constructed standalone graphical user interface and command-line versions for different systems. The standalone PhD7Faster 2.0 is able to detect PrTUPs within small datasets as well as large-scale datasets. This makes PhD7Faster 2.0 an enhanced and powerful tool for scanning and reporting faster-growing clones from the Ph.D.-7 phage display library.

SAROTUP: a suite of tools for finding potential target-unrelated peptides from phage display data

SAROTUP (Scanner And Reporter Of Target-Unrelated Peptides) 3.1 is a significant upgrade to the widely used SAROTUP web server for the rapid identification of target-unrelated peptides (TUPs) in phage display data. At present, SAROTUP has gathered a suite of tools for finding potential TUPs and other purposes. Besides the TUPScan, the motif-based tool, and three tools based on the BDB database, i.e., MimoScan, MimoSearch, and MimoBlast, three predictors based on support vector machine, i.e., PhD7Faster, SABinder and PSBinder, are integrated into SAROTUP. The current version of SAROTUP contains 27 TUP motifs and 823 TUP sequences. We also developed the standalone SAROTUP application with graphical user interface (GUI) and command line versions for processing deep sequencing phage display data and distributed it as an open source package, which can perform perfectly locally on almost all systems that support C++ with little or no modification. The web interfaces of SAROTUP have also been redesigned to be more self-evident and user-friendly. The latest version of SAROTUP is freely available at http://i.uestc.edu.cn/sarotup3.

Molecular Design of Peptide-Fc Fusion Drugs

Background:

Peptide-Fc fusion drugs, also known as peptibodies, are a category of biological therapeutics in which the Fc region of an antibody is genetically fused to a peptide of interest. However, to develop such kind of drugs is laborious and expensive. Rational design is urgently needed.

Methods:

We summarized the key steps in peptide-Fc fusion technology and stressed the main computational resources, tools, and methods that had been used in the rational design of peptide-Fc fusion drugs. We also raised open questions about the computer-aided molecular design of peptide-Fc.

Results:

The design of peptibody consists of four steps. First, identify peptide leads from native ligands, biopanning, and computational design or prediction. Second, select the proper Fc region from different classes or subclasses of immunoglobulin. Third, fuse the peptide leads and Fc together properly. At last, evaluate the immunogenicity of the constructs. At each step, there are quite a few useful resources and computational tools.

Conclusion:

Reviewing the molecular design of peptibody will certainly help make the transition from peptide leads to drugs on the market quicker and cheaper.

Competitive and noncompetitive immunoassays for the detection of benzothiostrobin using magnetic nanoparticles and fluorescein isothiocyanate-labeled peptides

Phage-displayed peptides have been proven to be powerful reagents for competitive and noncompetitive immunoassays. However, they are unconventional reagents, which greatly limit their analytical commercial applications and require additional reagents for detection. In this work, the peptides that specifically bind with anti-benzothiostrobin monoclonal antibody (mAb) or benzothiostrobin-mAb immunocomplex were synthesized and conjugated with fluorescein isothiocyanate (FITC) as substitutes of the phage-displayed peptides to avoid their shortcomings and extend their applications. Competitive and noncompetitive fluorescence immunoassays (FIAs) for benzothiostrobin were developed by mAb coupling with magnetic nanoparticles as concentration elements and peptides conjugated with FITC as tracers. Compared with enzyme-linked immunosorbent assays, the FIAs reduced the number of steps from 6 to 2 and analysis time from more than 5 to 1.2 h. The competitive FIA showed the half-maximal inhibition concentration (IC₅₀) of 16.8 ng mL^-1 and detection range (IC₁₀-IC₉₀) of 1.0-759.9 ng mL^-1, while the concentration of analyte producing 50% saturation of the signal (SC₅₀) and detection range (SC₁₀-SC₉₀) of noncompetitive FIA were 93.4 and 5.9-788.2 ng mL^-1, respectively. The average spiked recoveries were 68.33-98.50% and 73.33-96.67% for competitive and noncompetitive FIAs, respectively. The FIAs showed good correlation with high-performance liquid chromatography for the detection of benzothiostrobin in authentic samples. Graphical abstract Development of competitive and noncompetitive fluorescence immunoassays for benzothiostrobin by using monoclonal antibody coupling with magnetic nanoparticles as concentration elements and peptides conjugated with fluorescein isothiocyanate as tracers.

KnowVolution of the Polymer-Binding Peptide LCI for Improved Polypropylene Binding

The functionalization of polymer surfaces by polymer-binding peptides offers tremendous opportunities for directed immobilization of enzymes, bioactive peptides, and antigens. The application of polymer-binding peptides as adhesion promoters requires reliable and stable binding under process conditions. Molecular modes of interactions between material surfaces, peptides, and solvent are often not understood to an extent that enables (semi-) rational design of polymer-binding peptides, hindering the full exploitation of their potential. Knowledge-gaining directed evolution (KnowVolution) is an efficient protein engineering strategy that facilitates tailoring protein properties to application demands through a combination of directed evolution and computational guided protein design. A single round of KnowVolution was performed to gain molecular insights into liquid chromatography peak I peptide, 47 aa (LCI)-binding to polypropylene (PP) in the presence of the competing surfactant Triton X-100. KnowVolution yielded a total of 8 key positions (D19, S27, Y29, D31, G35, I40, E42, and D45), which govern PP-binding in the presence of Triton X-100. The recombination of two of the identified amino acid substitutions (Y29R and G35R; variant KR-2) yielded a 5.4 ± 0.5-fold stronger PP-binding peptide compared to LCI WT in the presence of Triton X-100 (1 mM). The LCI variant KR-2 shows a maximum binding capacity of 8.8 ± 0.1 pmol/cm² on PP in the presence of Triton X-100 (up to 1 mM). The KnowVolution approach enables the development of polymer-binding peptides, which efficiently coat and functionalize PP surfaces and withstand surfactant concentrations that are commonly used, such as in household detergents.

PSBinder: A Web Service for Predicting Polystyrene Surface-Binding Peptides

Polystyrene surface-binding peptides (PSBPs) are useful as affinity tags to build a highly effective ELISA system. However, they are also a quite common type of target-unrelated peptides (TUPs) in the panning of phage-displayed random peptide library. As TUP, PSBP will mislead the analysis of panning results if not identified. Therefore, it is necessary to find a way to quickly and easily foretell if a peptide is likely to be a PSBP or not. In this paper, we describe PSBinder, a predictor based on SVM. To our knowledge, it is the first web server for predicting PSBP. The SVM model was built with the feature of optimized dipeptide composition and 87.02% (MCC = 0.74; AUC = 0.91) of peptides were correctly classified by fivefold cross-validation. PSBinder can be used to exclude highly possible PSBP from biopanning results or to find novel candidates for polystyrene affinity tags. Either way, it is valuable for biotechnology community.

Cancer therapeutic approach based on conformational stabilization of mutant p53 protein by small peptides

The p53 tumor suppressor serves as a major barrier against malignant transformation. Over 50% of tumors inactivate p53 by point mutations in its DNA binding domain. Most mutations destabilize p53 protein folding, causing its partial denaturation at physiological temperature. Thus a high proportion of human tumors overexpress a potential potent tumor suppressor in a non-functional, misfolded form. The equilibrium between the properly folded and misfolded states of p53 may be affected by molecules that interact with p53, stabilizing its native folding and restoring wild type p53 activity to cancer cells. To select for mutant p53 (mutp53) reactivating peptides, we adopted the phage display technology, allowing interactions between mutp53 and random peptide libraries presented on phages and enriching for phage that favor the correctly folded p53 conformation. We obtained a large database of potential reactivating peptides. Lead peptides were synthesized and analyzed for their ability to restore proper p53 folding and activity. Remarkably, many enriched peptides corresponded to known p53-binding proteins, including RAD9. Importantly, lead peptides elicited dramatic regression of aggressive tumors in mouse xenograft models. Such peptides might serve as novel agents for human cancer therapy.

Upgrading Affinity Screening Experiments by Analysis of Next-Generation Sequencing Data

Computational analysis of next-generation sequencing data (NGS; also termed deep sequencing) enables the analysis of affinity screening procedures (or biopanning experiments) in an unprecedented depth and therewith improves the identification of relevant peptide or antibody ligands with desired binding or functional properties. Virtually any selection methodology employing the direct physical linkage of geno- and phenotype to select for desired properties can be leveraged by computational analysis. This article describes a concept how relevant ligands can be identified by harnessing NGS data. Thereby, the focus lays on improved ligand identification and describes how NGS data can be structured for single-round analysis as well as for comparative analysis of multiple selection rounds. Especially, the comparative analysis opens new avenues in the field of ligand identification. The concept of computational analysis is described at the example of the software tool "AptaAnalyzer ^TM ." This intuitive tool was developed for scientists without special computer skills and makes the computational approach accessible to a broad user range.

Strategies for Selecting Membrane Protein-Specific Antibodies using Phage Display with Cell-Based Panning

Membrane proteins are attractive targets for monoclonal antibody (mAb) discovery and development. Although several approved mAbs against membrane proteins have been isolated from phage antibody libraries, the process is challenging, as it requires the presentation of a correctly folded protein to screen the antibody library. Cell-based panning could represent the optimal method for antibody discovery against membrane proteins, since it allows for presentation in their natural conformation along with the appropriate post-translational modifications. Nevertheless, screening antibodies against a desired antigen, within a selected cell line, may be difficult due to the abundance of irrelevant organic molecules, which can potentially obscure the antigen of interest. This review will provide a comprehensive overview of the different cell-based phage panning strategies, with an emphasis placed on the optimisation of four critical panning conditions: cell surface antigen presentation, non-specific binding events, incubation time, and temperature and recovery of phage binders.

Discovery of a polystyrene binding peptide isolated from phage display library and its application in peptide immobilization

Phage peptide display is a powerful technique for discovery of various target-specific ligands. However, target-unrelated peptides can often be obtained and cause ambiguous results. Peptide PB-TUP has been isolated repeatedly in our laboratory on different targets and we conducted a research on PB-TUP phage to investigate their binding properties and rate of propagation. ELISA and phage recovery assay demonstrated that PB-TUP phage had a significant superior affinity to polystyrene solid surface compared with control phage clones. In this study, some incidental bindings are excluded like blocking agents and non-specific binding of secondary antibodies. Propagation rate assays of the selected phage clones showed that the growth rate of PB-TUP phage was not superior to the control phages. Furthermore, the binding of PB-TUB to polystyrene was concentration dependent and varied with solution pH. Molecular modeling revealed that stable structures of α-helix and β-turn may contribute to the binding of PB-TUP to polystyrene plate. The PB-TUP sequence was fused to the N-terminus of peptide P2 and the fusion peptide significantly increased the binding affinity to polystyrene. The fusion peptide also enhanced the cell adhesion ability of peptide P2 with human umbilical vein endothelial cell (HUVEC). The addition of the polystyrene binding peptide provided a convenient method for peptide immobilization.

A novel peptide specifically binding to VEGF receptor suppresses angiogenesis in vitro and in vivo

Vascular endothelial growth factor (VEGF), one of the most important angiogenic factors, plays an essential role in both physiological and pathological angiogenesis through binding to VEGF receptors (VEGFRs). Here we report a novel peptide designated HRHTKQRHTALH (peptide HRH), which was isolated from the Ph.D. -12 phage display library using VEGFR-Fc fusion protein as the bait. This peptide was found to dose-dependently inhibit the proliferation of human umbilical vein endothelial cells stimulated by VEGF. The anti-angiogenesis effect of the HRH peptide was further confirmed in vivo using the chick chorioallantoic membrane assay, which was also dose-dependent. Besides, peptide HRH was proved to inhibit corneal neovascularization in an alkali-burnt rat corneal model and a suture-induced rat corneal model. Taken together, these findings suggest that the HRH peptide can inhibit angiogenesis both in vitro and in vivo. Consequently, the HRHTKQRHTALH peptide might be a promising lead peptide for the development of potential angiogenic inhibitors.

Various mutations compensate for a deleterious lacZα insert in the replication enhancer of M13 bacteriophage

M13 and other members of the Ff class of filamentous bacteriophages have been extensively employed in myriad applications. The Ph.D. series of phage-displayed peptide libraries were constructed from the M13-based vector M13KE. As a direct descendent of M13mp19, M13KE contains the lacZα insert in the intergenic region between genes IV and II, where it interrupts the replication enhancer of the (+) strand origin. Phage carrying this 816-nucleotide insert are viable, but propagate in E. coli at a reduced rate compared to wild-type M13 phage, presumably due to a replication defect caused by the insert. We have previously reported thirteen compensatory mutations in the 5'-untranslated region of gene II, which encodes the replication initiator protein gIIp. Here we report several additional mutations in M13KE that restore a wild-type propagation rate. Several clones from constrained-loop variable peptide libraries were found to have ejected the majority of lacZα gene in order to reconstruct the replication enhancer, albeit with a small scar. In addition, new point mutations in the gene II 5'-untranslated region or the gene IV coding sequence have been spontaneously observed or synthetically engineered. Through phage propagation assays, we demonstrate that all these genetic modifications compensate for the replication defect in M13KE and restore the wild-type propagation rate. We discuss the mechanisms by which the insertion and ejection of the lacZα gene, as well as the mutations in the regulatory region of gene II, influence the efficiency of replication initiation at the (+) strand origin. We also examine the presence and relevance of fast-propagating mutants in phage-displayed peptide libraries.

ArrayPitope: Automated Analysis of Amino Acid Substitutions for Peptide Microarray-Based Antibody Epitope Mapping

Identification of epitopes targeted by antibodies (B cell epitopes) is of critical importance for the development of many diagnostic and therapeutic tools. For clinical usage, such epitopes must be extensively characterized in order to validate specificity and to document potential cross-reactivity.

B cell epitopes are typically classified as either linear epitopes, i.e. short consecutive segments from the protein sequence or conformational epitopes adapted through native protein folding. Recent advances in high-density peptide microarrays enable high-throughput, high-resolution identification and characterization of linear B cell epitopes. Using exhaustive amino acid substitution analysis of peptides originating from target antigens, these microarrays can be used to address the specificity of polyclonal antibodies raised against such antigens containing hundreds of epitopes. However, the interpretation of the data provided in such large-scale screenings is far from trivial and in most cases it requires advanced computational and statistical skills. Here, we present an online application for automated identification of linear B cell epitopes, allowing the non-expert user to analyse peptide microarray data. The application takes as input quantitative peptide data of fully or partially substituted overlapping peptides from a given antigen sequence and identifies epitope residues (residues that are significantly affected by substitutions) and visualize the selectivity towards each residue by sequence logo plots. Demonstrating utility, the application was used to identify and address the antibody specificity of 18 linear epitope regions in Human Serum Albumin (HSA), using peptide microarray data consisting of fully substituted peptides spanning the entire sequence of HSA and incubated with polyclonal rabbit anti-HSA (and mouse anti-rabbit-Cy3). The application is made available at: www.cbs.dtu.dk/services/ArrayPitope.

Pharmacological targeting of mutant p53

TP53 is the most commonly mutated gene in cancer, with over half of all human cancers harboring a mutation in the gene. The p53 protein is a transcription factor that functions as a tumor suppressor, and a subset of its numerous roles include the arrest of proliferation, promotion of DNA repair, and induction of apoptosis in cells with severe DNA damage or stress. The vast majority of p53 mutations are single amino acid substitutions within the DNA binding domain, which either directly impede the protein's ability to bind DNA or destabilize the structure, resulting in misfolding. These missense mutant proteins are found at high levels due to loss of the MDM2 mediated regulation, and consequently serve as potential drug targets. Numerous pharmacological approaches have been investigated to restore wild type p53 function to these mutants (so-called reactivating mutant p53) with some entering in clinical trials while most have failed in early development. Recently, the field of cancer drug development has produced a number of new compounds that continue to advance this field, each with a different mechanism of action. Here we sought to review these compounds and approaches to reactivating mutant p53. Given the large number of patients with missense mutant p53 mutations, reactivating mutant p53 remains a highly sought after goal in developmental therapeutics.

Phage display as a promising approach for vaccine development

Bacteriophages are specific antagonists to bacterial hosts. These viral entities have attracted growing interest as optimal vaccine delivery vehicles. Phages are well-matched for vaccine design due to being highly stable under harsh environmental conditions, simple and inexpensive large scale production, and potent adjuvant capacities. Phage vaccines have efficient immunostimulatory effects and present a high safety profile because these viruses have made a constant relationship with the mammalian body during a long-standing evolutionary period. The birth of phage display technology has been a turning point in the development of phage-based vaccines. Phage display vaccines are made by expressing multiple copies of an antigen on the surface of immunogenic phage particles, thereby eliciting a powerful and effective immune response. Also, the ability to produce combinatorial peptide libraries with a highly diverse pool of randomized ligands has transformed phage display into a straightforward, versatile and high throughput screening methodology for the identification of potential vaccine candidates against different diseases in particular microbial infections. These libraries can be conveniently screened through an affinity selection-based strategy called biopanning against a wide variety of targets for the selection of mimotopes with high antigenicity and immunogenicity. Also, they can be panned against the antiserum of convalescent individuals to recognize novel peptidomimetics of pathogen-related epitopes. Phage display has represented enormous promise for finding new strategies of vaccine discovery and production and current breakthroughs promise a brilliant future for the development of different phage-based vaccine platforms.

Localized lentivirus delivery via peptide interactions

Gene delivery from biomaterial scaffolds has been employed to induce the expression of tissue inductive factors for applications in regenerative medicine. The delivery of viral vectors has been described as reflecting a balance between vector retention and release. Herein, we investigated the design of hydrogels in order to retain the vector at the material in order to enhance transgene expression. Poly(ethylene-glycol) (PEG) hydrogels were modified with poly-l-lysine (PLL) to non-covalently bind lentivirus. For cells cultured on the hydrogels, increasing the PLL molecular weight from 1 to 70 kDa led to increased transgene expression. The incubation time of the virus with the hydrogel and the PLL concentration modulated the extent of virus adsorption, and adsorbed virus had a 20% increase in the half-life at 37°C. Alternatives to high molecular weight PLL were identified through phage display technology, with peptide sequences specific for the VSV-G ectodomain, an envelope protein pseudotyped on the virus. These affinity peptides could easily be incorporated into the hydrogel, and expression was increased 20-fold relative to control peptide, and comparable to levels observed with the high molecular weight PLL. The modification of hydrogels with affinity proteins or peptides to bind lentivirus can be a powerful strategy to enhance and localized transgene expression. Biotechnol. Bioeng. 2016;113: 2033-2040. © 2016 Wiley Periodicals, Inc.

Selection of Novel Peptides Homing the 4T1 CELL Line: Exploring Alternative Targets for Triple Negative Breast Cancer

The use of bacteriophages to select novel ligands has been widely explored for cancer therapy. Their application is most warranted in cancer subtypes lacking knowledge on how to target the cancer cells in question, such as the triple negative breast cancer, eventually leading to the development of alternative nanomedicines for cancer therapeutics. Therefore, the following study aimed to select and characterize novel peptides for a triple negative breast cancer murine mammary carcinoma cell line– 4T1. Using phage display, 7 and 12 amino acid random peptide libraries were screened against the 4T1 cell line. A total of four rounds, plus a counter-selection round using the 3T3 murine fibroblast cell line, was performed. The enriched selective peptides were characterized and their binding capacity towards 4T1 tissue samples was confirmed by immunofluorescence and flow cytometry analysis. The selected peptides (4T1pep1 –CPTASNTSC and 4T1pep2—EVQSSKFPAHVS) were enriched over few rounds of selection and exhibited specific binding to the 4T1 cell line. Interestingly, affinity to the human MDA-MB-231 cell line was also observed for both peptides, promoting the translational application of these novel ligands between species. Additionally, bioinformatics analysis suggested that both peptides target human Mucin-16. This protein has been implicated in different types of cancer, as it is involved in many important cellular functions. This study strongly supports the need of finding alternative targeting systems for TNBC and the peptides herein selected exhibit promising future application as novel homing peptides for breast cancer therapy.

SABinder: A Web Service for Predicting Streptavidin-Binding Peptides

Streptavidin is sometimes used as the intended target to screen phage-displayed combinatorial peptide libraries for streptavidin-binding peptides (SBPs). More often in the biopanning system, however, streptavidin is just a commonly used anchoring molecule that can efficiently capture the biotinylated target. In this case, SBPs creeping into the biopanning results are not desired binders but target-unrelated peptides (TUP). Taking them as intended binders may mislead subsequent studies. Therefore, it is important to find if a peptide is likely to be an SBP when streptavidin is either the intended target or just the anchoring molecule. In this paper, we describe an SVM-based ensemble predictor called SABinder. It is the first predictor for SBP. The model was built with the feature of optimized dipeptide composition. It was observed that 89.20% (MCC = 0.78; AUC = 0.93; permutation test, p < 0.001) of peptides were correctly classified. As a web server, SABinder is freely accessible. The tool provides a highly efficient way to exclude potential SBP when they are TUP or to facilitate identification of possibly new SBP when they are the desired binders. In either case, it will be helpful and can benefit related scientific community.