PHASTpep: Analysis Software for Discovery of Cell-Selective Peptides via Phage Display and Next-Generation Sequencing

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.

Development of New CD38 Targeted Peptides for Cancer Imaging

PURPOSE

Multiple myeloma (MM) affects over 35,000 patients each year in the US. There remains a need for versatile Positron Emission Tomography (PET) tracers for the detection, accurate staging, and monitoring of treatment response of MM that have optimal specificity and translational attributes. CD38 is uniformly overexpressed in MM and thus represents an ideal target to develop CD38-targeted small molecule PET radiopharmaceuticals to address these challenges.

PROCEDURES

Using phage display peptide libraries and pioneering algorithms, we identified novel CD38 specific peptides. Imaging bioconjugates were synthesized using solid phase peptide chemistry, and systematically analyzed in vitro and in vivo in relevant MM systems.

RESULTS

The CD38-targeted bioconjugates were radiolabeled with copper-64 (64Cu) with100% radiochemical purity and an average specific activity of 3.3 - 6.6 MBq/nmol. The analog NODAGA-PEG4-SL022-GGS (SL022: Thr-His-Tyr-Pro-Ile-Val-Ile) had a Kd of 7.55 ± 0.291 nM and was chosen as the lead candidate. 64Cu-NODAGA-PEG4-SL022-GGS demonstrated high binding affinity to CD38 expressing human myeloma MM.1S-CBR-GFP-WT cells, which was blocked by the non-radiolabeled version of the peptide analog and anti-CD38 clinical antibodies, daratumumab and isatuximab, by 58%, 73%, and 78%, respectively. The CD38 positive MM.1S-CBR-GFP-WT cells had > 68% enhanced cellular binding when compared to MM.1S-CBR-GFP-KO cells devoid of CD38. Furthermore, our new CD38-targeted radiopharmaceutical allowed visualization of tumors located in marrow rich bones, remaining there for up to 4 h. Clearance from non-target organs occurred within 60 min. Quantitative PET data from a murine disseminated tumor model showed significantly higher accumulation in the bones of tumor-bearing animals compared to tumor-naïve animals (SUVmax 2.06 ± 0.4 versus 1.24 ± 0.4, P = 0.02). Independently, tumor uptake of the target compound was significantly higher (P = 0.003) compared to the scrambled peptide, 64Cu-NODAGA-PEG4-SL041-GGS (SL041: Thr-Tyr-His-Ile-Pro-Ile-Val). The subcutaneous MM model demonstrated significantly higher accumulation in tumors compared to muscle at 1 and 4 h after tracer administration (SUVmax 0.8 ± 0.2 and 0.14 ± 0.04, P = 0.04 at 1 h; SUVmax 0.89 ± 0.01 and 0.09 ± 0.01, P = 0.0002 at 4 h).

CONCLUSIONS

The novel CD38-targeted, radiolabeled bioconjugates were specific and allowed visualization of MM, providing a starting point for the clinical translation of such tracers for the detection of MM.

Depth of Sequencing Plays a Determining Role in the Characterization of Phage Display Peptide Libraries by NGS

Next-generation sequencing (NGS) has raised a growing interest in phage display research. Sequencing depth is a pivotal parameter for using NGS. In the current study, we made a side-by-side comparison of two NGS platforms with different sequencing depths, denoted as lower-throughput (LTP) and higher-throughput (HTP). The capacity of these platforms for characterization of the composition, quality, and diversity of the unselected Ph.D.TM-12 Phage Display Peptide Library was investigated. Our results indicated that HTP sequencing detects a considerably higher number of unique sequences compared to the LTP platform, thus covering a broader diversity of the library. We found a larger percentage of singletons, a smaller percentage of repeated sequences, and a greater percentage of distinct sequences in the LTP datasets. These parameters suggest a higher library quality, resulting in potentially misleading information when using LTP sequencing for such assessment. Our observations showed that HTP reveals a broader distribution of peptide frequencies, thus revealing increased heterogeneity of the library by the HTP approach and offering a comparatively higher capacity for distinguishing peptides from each other. Our analyses suggested that LTP and HTP datasets show discrepancies in their peptide composition and position-specific distribution of amino acids within the library. Taken together, these findings lead us to the conclusion that a higher sequencing depth can yield more in-depth insights into the composition of the library and provide a more complete picture of the quality and diversity of phage display peptide libraries.

A Bitter Taste Receptor as a Novel Molecular Target on Cancer-Associated Fibroblasts in Pancreatic Ductal Adenocarcinoma

Cancer-associated fibroblasts (CAFs) execute diverse and complex functions in cancer progression. While reprogramming the crosstalk between CAFs and cancer epithelial cells is a promising avenue to evade the adverse effects of stromal depletion, drugs are limited by their suboptimal pharmacokinetics and off-target effects. Thus, there is a need to elucidate CAF-selective cell surface markers that can improve drug delivery and efficacy. Here, functional proteomic pulldown with mass spectrometry was used to identify taste receptor type 2 member 9 (TAS2R9) as a CAF target. TAS2R9 target characterization included binding assays, immunofluorescence, flow cytometry, and database mining. Liposomes conjugated to a TAS2R9-specific peptide were generated, characterized, and compared to naked liposomes in a murine pancreatic xenograft model. Proof-of-concept drug delivery experiments demonstrate that TAS2R9-targeted liposomes bind with high specificity to TAS2R9 recombinant protein and exhibit stromal colocalization in a pancreatic cancer xenograft model. Furthermore, the delivery of a CXCR2 inhibitor by TAS2R9-targeted liposomes significantly reduced cancer cell proliferation and constrained tumor growth through the inhibition of the CXCL-CXCR2 axis. Taken together, TAS2R9 is a novel cell-surface CAF-selective target that can be leveraged to facilitate small-molecule drug delivery to CAFs, paving the way for new stromal therapies.

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.

Comparative Evaluation of Reproducibility of Phage-Displayed Peptide Selections and NGS Data, through High-Fidelity Mapping of Massive Peptide Repertoires

Phage-displayed peptide selections generate complex repertoires of several hundred thousand peptides as revealed by next-generation sequencing (NGS). In repeated peptide selections, however, even in identical experimental in vitro conditions, only a very small number of common peptides are found. The repertoire complexities are evidence of the difficulty of distinguishing between effective selections of specific peptide binders to exposed targets and the potential high background noise. Such investigation is even more relevant when considering the plethora of in vivo expressed targets on cells, in organs or in the entire organism to define targeting peptide agents. In the present study, we compare the published NGS data of three peptide repertoires that were obtained by phage display under identical experimental in vitro conditions. By applying the recently developed tool PepSimili we evaluate the calculated similarities of the individual peptides from each of these three repertoires and perform their mappings on the human proteome. The peptide-to-peptide mappings reveal high similarities among the three repertoires, confirming the desired reproducibility of phage-displayed peptide selections.

Phage in cancer treatment - Biology of therapeutic phage and screening of tumor targeting peptide

INTRODUCTION

There is a constant drive to improve disease treatments. Much effort has been directed at identifying less immunogenic anti-cancer agents that produce fewer and less severe side effects. For more than a decade, bacteriophages have been discussed as an effective treatment for cancer with an exact mode of delivery.

AREAS COVERED

We review how bacteriophages are used in cancer treatment, the underlying therapeutic mechanisms, and the tumour attacking peptide screening process. The filamentous bacteriophages are an effective vehicle for delivering displayed peptides toward the tumour target. The peptide must be expressed at the appropriate coat protein, and the peptide must be effective enough to disrupt the complex cancer matrix. The present review also sheds light on the dynamic use of phage in cancer treatment, from detection and diagnostics to treatment.

EXPERT OPINION

Phage has a versatile role as a diagnostic and therapeutic tool. By acting as an appropriate recombinant drug, this phage has every potential to replace existing laborious, high capital investing therapies that may at many times result in failure or drastic side effects. One of the most significant challenges would be identifying tumour homing peptides. Although a few have been discovered, the most effective ones are yet to be determined. This therapeutic method plays a significant role in tumour therapy with high accuracy and efficiency, irrespective of the target location.

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.

The emerging role of selenium metabolic pathways in cancer: New therapeutic targets for cancer

Selenium (Se) is incorporated into the body via the selenocysteine (Sec) biosynthesis pathway, which is critical in the synthesis of selenoproteins, such as glutathione peroxidases and thioredoxin reductases. Selenoproteins, which play a key role in several biological processes, including ferroptosis, drug resistance, endoplasmic reticulum stress, and epigenetic processes, are guided by Se uptake. In this review, we critically analyze the molecular mechanisms of Se metabolism and its potential as a therapeutic target for cancer. Sec insertion sequence binding protein 2 (SECISBP2), which is a positive regulator for the expression of selenoproteins, would be a novel prognostic predictor and an alternate target for cancer. We highlight strategies that attempt to develop a novel Se metabolism-based approach to uncover a new metabolic drug target for cancer therapy. Moreover, we expect extensive clinical use of SECISBP2 as a specific biomarker in cancer therapy in the near future. Of note, scientists face additional challenges in conducting successful research, including investigations on anticancer peptides to target SECISBP2 intracellular protein.

Identification of Novel Ligands for Targeted Antifibrotic Therapy of Chronic Pancreatitis

PURPOSE

Chronic pancreatitis (CP) is an inflammatory disorder of the pancreas that leads to impaired pancreatic function. The limited therapeutic options and the lack of molecular targeting ligands or non-serum-based biomarkers hinder the development of target-specific drugs. Thus, there is a need for an unbiased, comprehensive discovery and evaluation of pancreatitis-specific ligands.

METHODS

This study utilized a computational-guided in vivo phage display approach to select peptide ligands selective for cellular components in the caerulein-induced mouse model of CP. The identified peptides were conjugated to pegylated DOPC liposomes via the reverse-phase evaporation method, and the in vivo specificity and pharmacokinetics were determined. As proof of concept, CP-targeted liposomes were used to deliver an antifibrotic small molecular drug, apigenin. Antifibrotic effects determined by pancreatic histology, fibronectin expression, and collagen deposition were evaluated.

RESULTS

We have identified five peptides specific for chronic pancreatitis and demonstrated selectivity to activated pancreatic stellate cells, acinar cells, macrophages, and extracellular matrix, respectively. MDLSLKP-conjugated liposomes demonstrated an increased particle accumulation by 1.3-fold in the inflamed pancreas compared to the control liposomes. We also observed that targeted delivery of apigenin resulted in improved acini preservation, a 37.2% and 33.1% respective reduction in collagen and fibronectin expression compared to mice receiving the free drug, and reduced oxidative stress in the liver.

CONCLUSION

In summary, we have developed a systematic approach to profile peptide ligands selective for cellular components of complex disease models and demonstrated the biomedical applications of the identified peptides to improve tissue remodeling in the inflamed pancreas.

In vivo phage display: identification of organ-specific peptides using deep sequencing and differential profiling across tissues

In vivo phage display is widely used for identification of organ- or disease-specific homing peptides. However, the current in vivo phage biopanning approaches fail to assess biodistribution of specific peptide phages across tissues during the screen, thus necessitating laborious and time-consuming post-screening validation studies on individual peptide phages. Here, we adopted bioinformatics tools used for RNA sequencing for analysis of high-throughput sequencing (HTS) data to estimate the representation of individual peptides during biopanning in vivo. The data from in vivo phage screen were analyzed using differential binding-relative representation of each peptide in the target organ versus in a panel of control organs. Application of this approach in a model study using low-diversity peptide T7 phage library with spiked-in brain homing phage demonstrated brain-specific differential binding of brain homing phage and resulted in identification of novel lung- and brain-specific homing peptides. Our study provides a broadly applicable approach to streamline in vivo peptide phage biopanning and to increase its reproducibility and success rate.

Highly paralleled emulsion droplets for efficient isolation, amplification, and screening of cancer biomarker binding phages

Based on the linkage of genotype and phenotype, display technology has been widely used to generate specific ligands for profiling, imaging, diagnosis and therapy applications. However, due to the lack of effective monoclonal manipulation and affinity evaluation methods, traditional display technology has to undergo tedious steps of selection, clone isolation, amplification, sequencing, synthesis and characterization to obtain the binding sequences. To directly acquire high-affinity clones, we propose a double monoclonal display approach (dm-Display) for peptide screening based on highly paralleled monoclonal manipulation in emulsion droplets. dm-Display can monoclonally link the genotype, phenotype and affinity to realize integrated monoclonal separation, amplification, recognition and staining in one droplet so that discrete high-affinity clones can be quickly extracted. Monoclonal manipulations highly-parallelly occur in millions of droplets so that molecular screening of a highly diverse phage library is achieved. We have screened specific peptide ligands against CD71 and GPC1, proving the feasibility and generality of dm-Display. As a highly efficient ligand screening platform, dm-Display will promote the further development of molecular screening.

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.

MRI-based molecular imaging of epicardium-derived stromal cells (EpiSC) by peptide-mediated active targeting

After myocardial infarction (MI), epicardial cells reactivate their embryonic program, proliferate and migrate into the damaged tissue to differentiate into fibroblasts, endothelial cells and, if adequately stimulated, to cardiomyocytes. Targeting epicardium-derived stromal cells (EpiSC) by specific ligands might enable the direct imaging of EpiSCs after MI to better understand their biology, but also may permit the cell-specific delivery of small molecules to improve the post-MI healing process. Therefore, the aim of this study was to identify specific peptides by phage display screening to enable EpiSC specific cargo delivery by active targeting. To this end, we utilized a sequential panning of a phage library on cultured rat EpiSCs and then subtracted phage that nonspecifically bound blood immune cells. EpiSC specific phage were analyzed by deep sequencing and bioinformatics analysis to identify a total of 78 300 ± 31 900 different, EpiSC-specific, peptide insertion sequences. Flow cytometry of the five most highly abundant peptides (EP1, -2, -3, -7 or EP9) showed strong binding to EpiSCs but not to blood immune cells. The best binding properties were found for EP9 which was further studied by surface plasmon resonance (SPR). SPR revealed rapid and stable association of EpiSCs with EP9. As a negative control, THP-1 monocytes did not associate with EP9. Coupling of EP9 to perfluorocarbon nanoemulsions (PFCs) resulted in the efficient delivery of ¹⁹F cargo to EpiSCs and enabled their visualization by ¹⁹F MRI. Moreover, active targeting of EpiSCs by EP9-labelled PFCs was able to outcompete the strong phagocytic uptake of PFCs by circulating monocytes. In summary, we have identified a 7-mer peptide, (EP9) that binds to EpiSCs with high affinity and specificity. This peptide can be used to deliver small molecule cargos such as contrast agents to permit future in vivo tracking of EpiSCs by molecular imaging and to transfer small pharmaceutical molecules to modulate the biological activity of EpiSCs.

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.

InteractomeSeq: a web server for the identification and profiling of domains and epitopes from phage display and next generation sequencing data

High-Throughput Sequencing technologies are transforming many research fields, including the analysis of phage display libraries. The phage display technology coupled with deep sequencing was introduced more than a decade ago and holds the potential to circumvent the traditional laborious picking and testing of individual phage rescued clones. However, from a bioinformatics point of view, the analysis of this kind of data was always performed by adapting tools designed for other purposes, thus not considering the noise background typical of the 'interactome sequencing' approach and the heterogeneity of the data. InteractomeSeq is a web server allowing data analysis of protein domains ('domainome') or epitopes ('epitome') from either Eukaryotic or Prokaryotic genomic phage libraries generated and selected by following an Interactome sequencing approach. InteractomeSeq allows users to upload raw sequencing data and to obtain an accurate characterization of domainome/epitome profiles after setting the parameters required to tune the analysis. The release of this tool is relevant for the scientific and clinical community, because InteractomeSeq will fill an existing gap in the field of large-scale biomarkers profiling, reverse vaccinology, and structural/functional studies, thus contributing essential information for gene annotation or antigen identification. InteractomeSeq is freely available at https://InteractomeSeq.ba.itb.cnr.it/.

Challenges in the development of nanoparticle-based imaging agents: Characterization and biology

Despite imaging agents being some of the earliest nanomedicines in clinical use, the vast majority of current research and translational activities in the nanomedicine field involves therapeutics, while imaging agents are severely underrepresented. The reasons for this lack of representation are several fold, including difficulties in synthesis and scale-up, biocompatibility issues, lack of suitable tissue/disease selective targeting ligands and receptors, and a high bar for regulatory approval. The recent focus on immunotherapies and personalized medicine, and development of nanoparticle constructs with better tissue distribution and selectivity, provide new opportunities for nanomedicine imaging agent development. This manuscript will provide an overview of trends in imaging nanomedicine characterization and biocompatibility, and new horizons for future development. This article is categorized under: Diagnostic Tools > in vivo Nanodiagnostics and Imaging Toxicology and Regulatory Issues in Nanomedicine > Toxicology of Nanomaterials Toxicology and Regulatory Issues in Nanomedicine > Regulatory and Policy Issues in Nanomedicine.

Discovering Selected Antibodies From Deep-Sequenced Phage-Display Antibody Library Using ATTILA

Phage display is a powerful technique to select high-affinity antibodies for different purposes, including biopharmaceuticals. Next-generation sequencing (NGS) presented itself as a robust solution, making it possible to assess billions of sequences of the variable domains from selected sublibraries. Handling this process, a central difficulty is to find the selected clones. Here, we present the AutomaTed Tool For Immunoglobulin Analysis (ATTILA), a new tool to analyze and find the enriched variable domains throughout a biopanning experiment. The ATTILA is a workflow that combines publicly available tools and in-house programs and scripts to find the fold-change frequency of deeply sequenced amplicons generated from selected VH and VL domains. We analyzed the same human Fab library NGS data using ATTILA in 5 different experiments, as well as on 2 biopanning experiments regarding performance, accuracy, and output. These analyses proved to be suitable to assess library variability and to list the more enriched variable domains, as ATTILA provides a report with the amino acid sequence of each identified domain, along with its complementarity-determining regions (CDRs), germline classification, and fold change. Finally, the methods employed here demonstrated a suitable manner to combine amplicon generation and NGS data analysis to discover new monoclonal antibodies (mAbs).

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.

Multifaceted antibodies development against synthetic α-dystroglycan mucin glycopeptide as promising tools for dystroglycanopathies diagnostic

Dystroglycanopathies are diseases characterized by progressive muscular degeneration and impairment of patient's quality of life. They are associated with altered glycosylation of the dystrophin-glycoprotein (DGC) complex components, such as α-dystroglycan (α-DG), fundamental in the structural and functional stability of the muscle fiber. The diagnosis of dystroglycanopathies is currently based on the observation of clinical manifestations, muscle biopsies and enzymatic measures, and the available monoclonal antibodies are not specific for the dystrophic hypoglycosylated muscle condition. Thus, modified α-DG mucins have been considered potential targets for the development of new diagnostic strategies toward these diseases. In this context, this work describes the synthesis of the hypoglycosylated α-DG mimetic glycopeptide NHAc-Gly-Pro-Thr-Val-Thr[αMan]-Ile-Arg-Gly-BSA (1) as a potential tool for the development of novel antibodies applicable to dystroglycanopathies diagnosis. Glycopeptide 1 was used for the development of polyclonal antibodies and recombinant monoclonal antibodies by Phage Display technology. Accordingly, polyclonal antibodies were reactive to glycopeptide 1, which enables the application of anti-glycopeptide 1 antibodies in immune reactive assays targeting hypoglycosylated α-DG. Regarding monoclonal antibodies, for the first time variable heavy (VH) and variable light (VL) immunoglobulin domains were selected by Phage Display, identified by NGS and described by in silico analysis. The best-characterized VH and VL domains were cloned, expressed in E. coli Shuffle T7 cells, and used to construct a single chain fragment variable that recognized the Glycopeptide 1 (GpαDG1 scFv). Molecular modelling of glycopeptide 1 and GpαDG1 scFv suggested that their interaction occurs through hydrogen bonds and hydrophobic contacts involving amino acids from scFv (I51, Y33, S229, Y235, and P233) and R8 and α-mannose from Glycopeptide 1.

Phage display screening of therapeutic peptide for cancer targeting and therapy

Recently, phage display technology has been announced as the recipient of Nobel Prize in Chemistry 2018. Phage display technique allows high affinity target-binding peptides to be selected from a complex mixture pool of billions of displayed peptides on phage in a combinatorial library and could be further enriched through the biopanning process; proving to be a powerful technique in the screening of peptide with high affinity and selectivity. In this review, we will first discuss the modifications in phage display techniques used to isolate various cancer-specific ligands by in situ, in vitro, in vivo, and ex vivo screening methods. We will then discuss prominent examples of solid tumor targeting-peptides; namely peptide targeting tumor vasculature, tumor microenvironment (TME) and over-expressed receptors on cancer cells identified through phage display screening. We will also discuss the current challenges and future outlook for targeting peptide-based therapeutics in the clinics.

A Computational Pipeline for the Extraction of Actionable Biological Information From NGS-Phage Display Experiments

Phage Display is a powerful method for the identification of peptide binding to targets of variable complexities and tissues, from unique molecules to the internal surfaces of vessels of living organisms. Particularly for in vivo screenings, the resulting repertoires can be very complex and difficult to study with traditional approaches. Next Generation Sequencing (NGS) opened the possibility to acquire high resolution overviews of such repertoires and thus facilitates the identification of binders of interest. Additionally, the ever-increasing amount of available genome/proteome information became satisfactory regarding the identification of putative mimicked proteins, due to the large scale on which partial sequence homology is assessed. However, the subsequent production of massive data stresses the need for high-performance computational approaches in order to perform standardized and insightful molecular network analysis. Systems-level analysis is essential for efficient resolution of the underlying molecular complexity and the extraction of actionable interpretation, in terms of systemic biological processes and pathways that are systematically perturbed. In this work we introduce PepSimili, an integrated workflow tool, which performs mapping of massive peptide repertoires on whole proteomes and delivers a streamlined, systems-level biological interpretation. The tool employs modules for modeling and filtering of background noise due to random mappings and amplifies the biologically meaningful signal through coupling with BioInfoMiner, a systems interpretation tool that employs graph-theoretic methods for prioritization of systemic processes and corresponding driver genes. The current implementation exploits the Galaxy environment and is available online. A case study using public data is presented, with and without a control selection.

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.

Biopanning data bank 2018: hugging next generation phage display

The 2018 update of the biopanning data bank (BDB) stores phage display data sequenced by Sanger sequencing and next generation sequencing technologies. In this work, we upgraded the database with more biopanning data sets and several new features, including (i) incorporation of next generation biopanning data and the unselected population where the target is not determined and the round of screening is zero; (ii) addition of sequencing information; (iii) improvement of browsing and searching systems and 3 D chemical structure viewer; (iv) integration of standalone tools for target-unrelated peptides analysis within conventional phage display and next generation phage display (NGPD) data. In the current version of BDB (released on 19 January 2018), the database houses 3291 sets of biopanning data collected from 1540 published articles, including 95 NGPD data sets and 3196 traditional biopanning data sets. The BDB database serves as an important and comprehensive resource for developing peptide ligands.

Database URL: The BDB database is available at http://immunet.cn/bdb

Phage display peptide libraries: deviations from randomness and correctives

Peptide-expressing phage display libraries are widely used for the interrogation of antibodies. Affinity selected peptides are then analyzed to discover epitope mimetics, or are subjected to computational algorithms for epitope prediction. A critical assumption for these applications is the random representation of amino acids in the initial naïve peptide library. In a previous study, we implemented next generation sequencing to evaluate a naïve library and discovered severe deviations from randomness in UAG codon over-representation as well as in high G phosphoramidite abundance causing amino acid distribution biases. In this study, we demonstrate that the UAG over-representation can be attributed to the burden imposed on the phage upon the assembly of the recombinant Protein 8 subunits. This was corrected by constructing the libraries using supE44-containing bacteria which suppress the UAG driven abortive termination. We also demonstrate that the overabundance of G stems from variant synthesis-efficiency and can be corrected using compensating oligonucleotide-mixtures calibrated by mass spectroscopy. Construction of libraries implementing these correctives results in markedly improved libraries that display random distribution of amino acids, thus ensuring that enriched peptides obtained in biopanning represent a genuine selection event, a fundamental assumption for phage display applications.

PuLSE: Quality control and quantification of peptide sequences explored by phage display libraries

The design of highly diverse phage display libraries is based on assumption that DNA bases are incorporated at similar rates within the randomized sequence. As library complexity increases and expected copy numbers of unique sequences decrease, the exploration of library space becomes sparser and the presence of truly random sequences becomes critical. We present the program PuLSE (Phage Library Sequence Evaluation) as a tool for assessing randomness and therefore diversity of phage display libraries. PuLSE runs on a collection of sequence reads in the fastq file format and generates tables profiling the library in terms of unique DNA sequence counts and positions, translated peptide sequences, and normalized 'expected' occurrences from base to residue codon frequencies. The output allows at-a-glance quantitative quality control of a phage library in terms of sequence coverage both at the DNA base and translated protein residue level, which has been missing from toolsets and literature. The open source program PuLSE is available in two formats, a C++ source code package for compilation and integration into existing bioinformatics pipelines and precompiled binaries for ease of use.

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.

Virus-Derived Peptides for Clinical Applications

Novel affinity agents with high specificity are needed to make progress in disease diagnosis and therapy. Over the last several years, peptides have been considered to have fundamental benefits over other affinity agents, such as antibodies, due to their fast blood clearance, low immunogenicity, rapid tissue penetration, and reproducible chemical synthesis. These features make peptides ideal affinity agents for applications in disease diagnostics and therapeutics for a wide variety of afflictions. Virus-derived peptide techniques provide a rapid, robust, and high-throughput way to identify organism-targeting peptides with high affinity and selectivity. Here, we will review viral peptide display techniques, how these techniques have been utilized to select new organism-targeting peptides, and their numerous biomedical applications with an emphasis on targeted imaging, diagnosis, and therapeutic techniques. In the future, these virus-derived peptides may be used as common diagnosis and therapeutics tools in local clinics.

High-Throughput Approaches to the Development of Molecular Imaging Agents

Molecular imaging allows for the visualization of changes at the cellular level in diseases such as cancer. A successful molecular imaging agent must rely on disease-selective targets and ligands that specifically interact with those targets. Unfortunately, the translation of novel target-specific ligands into the clinic has been frustratingly slow with limitations including the complex design and screening approaches for ligand identification, as well as their subsequent optimization into useful imaging agents. This review focuses on combinatorial library approaches towards addressing these two challenges, with particular focus on phage display and one-bead one-compound (OBOC) libraries. Both of these peptide-based techniques have proven successful in identifying new ligands for cancer-specific targets and some of the success stories will be highlighted. New developments in screening methodology and sequencing technology have pushed the bounds of phage display and OBOC even further, allowing for even faster and more robust discovery of novel ligands. The combination of multiple high-throughput technologies will not only allow for more accurate identification, but also faster affinity maturation, while overall streamlining the process of translating novel ligands into clinical imaging agents.