Compositional Bias in Naïve and Chemically-modified Phage-Displayed Libraries uncovered by Paired-end Deep Sequencing

Brain-Penetrating Peptide Shuttles across the Blood-Brain Barrier and Extracellular-like Space

Systemic delivery of therapeutics into the brain is greatly impaired by multiple biological barriers─the blood-brain barrier (BBB) and the extracellular matrix (ECM) of the extracellular space. To address this problem, we developed a combinatorial approach to identify peptides that can shuttle and transport across both barriers. A cysteine-constrained heptapeptide M13 phage display library was iteratively panned against an established BBB model for three rounds to select for peptides that can transport across the barrier. Using next-generation DNA sequencing and in silico analysis, we identified peptides that were selectively enriched from successive rounds of panning for functional validation in vitro and in vivo. Select peptide-presenting phages exhibited efficient shuttling across the in vitro BBB model. Two clones, Pep-3 and Pep-9, exhibited higher specificity and efficiency of transcytosis than controls. We confirmed that peptides Pep-3 and Pep-9 demonstrated better diffusive transport through the extracellular matrix than gold standard nona-arginine and clinically trialed angiopep-2 peptides. In in vivo studies, we demonstrated that systemically administered Pep-3 and Pep-9 peptide-presenting phages penetrate the BBB and distribute into the brain parenchyma. In addition, free peptides Pep-3 and Pep-9 achieved higher accumulation in the brain than free angiopep-2 and may exhibit brain targeting. In summary, these in vitro and in vivo studies highlight that combinatorial phage display with a designed selection strategy can identify peptides as promising carriers, which are able to overcome the multiple biological barriers of the brain and shuttle different-sized molecules from small fluorophores to large macromolecules for improved delivery into the brain.

Genetically encoded discovery of perfluoroaryl macrocycles that bind to albumin and exhibit extended circulation in vivo

Peptide-based therapeutics have gained attention as promising therapeutic modalities, however, their prevalent drawback is poor circulation half-life in vivo. In this paper, we report the selection of albumin-binding macrocyclic peptides from genetically encoded libraries of peptides modified by perfluoroaryl-cysteine SNAr chemistry, with decafluoro-diphenylsulfone (DFS). Testing of the binding of the selected peptides to albumin identified SICRFFC as the lead sequence. We replaced DFS with isosteric pentafluorophenyl sulfide (PFS) and the PFS-SICRFFCGG exhibited KD = 4-6 µM towards human serum albumin. When injected in mice, the concentration of the PFS-SICRFFCGG in plasma was indistinguishable from the reference peptide, SA-21. More importantly, a conjugate of PFS-SICRFFCGG and peptide apelin-17 analogue (N3-PEG6-NMe17A2) showed retention in circulation similar to SA-21; in contrast, apelin-17 analogue was cleared from the circulation after 2 min. The PFS-SICRFFC is the smallest known peptide macrocycle with a significant affinity for human albumin and substantial in vivo circulation half-life. It is a productive starting point for future development of compact macrocycles with extended half-life in vivo.

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.

DNA-Encoded Multivalent Display of Chemically Modified Protein Tetramers on Phage: Synthesis and in Vivo Applications

Phage display links the phenotype of displayed polypeptides with the DNA sequence in the phage genome and offers a universal method for the discovery of proteins with novel properties. However, the display of large multisubunit proteins on phages remains a challenge. A majority of protein display systems are based on monovalent phagemid constructs, but methods for the robust display of multiple copies of large proteins are scarce. Here, we describe a DNA-encoded display of a ∼ 200 kDa tetrameric l-asparaginase protein on M13 and fd phages produced by ligation of SpyCatcher-Asparaginase fusion (ScA) and PEGylated-ScA (PEG-ScA) to barcoded phage clones displaying SpyTag peptide. Starting from the SpyTag display on p3 or p8 coat proteins yielded constructs with five copies of ScA displayed on p3 (ScA-p3), ∼100 copies of ScA on p8 protein (ScA-p8) and ∼300 copies of PEG-ScA on p8 protein (PEG-ScA-p8). Display constructs of different valencies and chemical modifications on protein (e.g., PEGylation) can be injected into mice and analyzed by deep sequencing of the DNA barcodes associated with phage clones. In these multiplexed studies, we observed a density and protein-dependent clearance rate in vivo. Our observations link the absence of PEGylation and increase in density of the displayed protein with the increased rate of the endocytosis by cells in vivo. In conclusion, we demonstrate that a multivalent display of l-asparaginase on phages could be used to study the circulation life of this protein in vivo, and such an approach opens the possibility to use DNA sequencing to investigate multiplexed libraries of other multisubunit proteins in vivo.

Pattern enrichment analysis for phage selection of stapled peptide ligands

Phage display is the most widely used technique to discover de novo peptides that bind to target proteins. However, it is associated with some challenges such as compositional bias. In this study, to overcome these difficulties, we devised a 'pattern enrichment analysis.' In this method, two samples (one obtained by affinity selection, the other simply amplified without selection) are prepared, and the two sequence datasets read on next-generation sequencer are compared to find the three-residue pattern most enriched in the selected sample. This allows us to compare two sequence datasets with high coverage and facilitates the identification of peptide sequences and the key residues for binding. We also demonstrated that this approach in the combination with structured peptide libraries allowed spatial mapping of the enriched sequence patterns. Here, we prepared a phage library displaying chemically stapled helical peptides with the X1C2X3X4X5X6X7X8C9X10 sequence, where X is any amino acid. To validate our method, we performed screening against the HDM2 protein. The results showed that the hydrophobic residues (Phe, Tyr, Trp and Leu) that are key to interactions with HDM2 were clearly identified by the pattern enrichment analysis. We also performed selection targeting the SARS-CoV-2 spike RBD in the same manner. The results showed that similar patterns were enriched among the hit peptides that inhibited the protein-protein interaction.

PDL1Binder: Identifying programmed cell death ligand 1 binding peptides by incorporating next-generation phage display data and different peptide descriptors

Monoclonal antibody drugs targeting the PD-1/PD-L1 pathway have showed efficacy in the treatment of cancer patients, however, they have many intrinsic limitations and inevitable drawbacks. Peptide inhibitors as alternatives might compensate for the drawbacks of current PD-1/PD-L1 interaction blockers. Identifying PD-L1 binding peptides by random peptide library screening is a time-consuming and labor-intensive process. Machine learning-based computational models enable rapid discovery of peptide candidates targeting the PD-1/PD-L1 pathway. In this study, we first employed next-generation phage display (NGPD) biopanning to isolate PD-L1 binding peptides. Different peptide descriptors and feature selection methods as well as diverse machine learning methods were then incorporated to implement predictive models of PD-L1 binding. Finally, we proposed PDL1Binder, an ensemble computational model for efficiently obtaining PD-L1 binding peptides. Our results suggest that predictive models of PD-L1 binding can be learned from deep sequencing data and provide a new path to discover PD-L1 binding peptides. A web server was implemented for PDL1Binder, which is freely available at http://i.uestc.edu.cn/pdl1binder/cgi-bin/PDL1Binder.pl.

Learning the structure-activity relationship (SAR) of the Wittig reaction from genetically-encoded substrates

The Wittig reaction can be used for late stage functionalization of proteins and peptides to ligate glycans, pharmacophores, and many other functionalities. In this manuscript, we modified 160 000 N-terminal glyoxaldehyde peptides displayed on phage with the Wittig reaction by using a biotin labeled ylide under conditions that functionalize only 1% of the library population. Deep-sequencing of the biotinylated and input populations estimated the rate of conversion for each sequence. This “deep conversion” (DC) from deep sequencing correlates with rate constants measured by HPLC. Peptide sequences with fast and slow reactivity highlighted the critical role of primary backbone amides (N–H) in accelerating the rate of the aqueous Wittig reaction. Experimental measurement of reaction rates and density functional theory (DFT) computation of the transition state geometries corroborated this relationship. We also collected deep-sequencing data to build structure–activity relationship (SAR) models that can predict the DC value of the Wittig reaction. By using these data, we trained two classifier models based on gradient boosted trees. These classifiers achieved area under the ROC (receiver operating characteristic) curve (ROC AUC) of 81.2 ± 0.4 and 73.7 ± 0.8 (90–92% accuracy) in determining whether a sequence belonged to the top 5% or the bottom 5% in terms of its reactivity. This model can suggest new peptides never observed experimentally with ‘HIGH’ or ‘LOW’ reactivity. Experimental measurement of reaction rates for 11 new sequences corroborated the predictions for 8 of them. We anticipate that phage-displayed peptides and related mRNA or DNA-displayed substrates can be employed in a similar fashion to study the substrate scope and mechanisms of many other chemical reactions.

160 000 peptides displayed on phage were subjected to the Wittig reaction with a biotinylated ylide. Deep-sequencing estimated the conversion rate for each sequence and unveiled the relationship between sequences and the rate of the Wittig reaction.

Genetically Encoded Fragment-Based Discovery from Phage-Displayed Macrocyclic Libraries with Genetically Encoded Unnatural Pharmacophores

Genetically encoded macrocyclic peptide libraries with unnatural pharmacophores are valuable sources for the discovery of ligands for many targets of interest. Traditionally, generation of such libraries employs "early stage" incorporation of unnatural building blocks into the chemically or translationally produced macrocycles. Here, we describe a divergent late-stage approach to such libraries starting from readily available starting material: genetically encoded libraries of peptides. A diketone linchpin 1,5-dichloropentane-2,4-dione converts peptide libraries displayed on phage to 1,3-diketone bearing macrocyclic peptides (DKMP): shelf-stable precursors for Knorr pyrazole synthesis. Ligation of diverse hydrazine derivatives onto DKMP libraries displayed on phage that carries silent DNA-barcodes yields macrocyclic libraries in which the amino acid sequence and the pharmacophore are encoded by DNA. Selection of this library against carbonic anhydrase enriched macrocycles with benzenesulfonamide pharmacophore and nanomolar Kd. The methodology described in this manuscript can graft diverse pharmacophores into many existing genetically encoded phage libraries and significantly increase the value of such libraries in molecular discoveries.

Phage display: an ideal platform for coupling protein to nucleic acid

Display technology, especially phage display technology, has been widely applied in many fields. The theoretical core of display technology is the physical linkage between the protein/peptide on the surface of a phage and the coding DNA sequence inside the same phage. Starting from phage-displayed peptide/protein/antibody libraries and taking advantage of the ever-growing power of next-generation sequencing (NGS) for DNA sequencing/decoding, rich protein-related information can easily be obtained in a high-throughput way. Based on this information, many scientific and clinical questions can be readily addressed. In the past few years, aided by the development of NGS, droplet technology, and massive oligonucleotide synthesis, we have witnessed and continue to witness large advances of phage display technology, in both technology development and application. The aim of this review is to summarize and discuss these recent advances.

Expanding the Chemical Diversity of Genetically Encoded Libraries

The power of ribosomes has increasingly been harnessed for the synthesis and selection of molecular libraries. Technologies, such as phage display, yeast display, and mRNA display, effectively couple genotype to phenotype for the molecular evolution of high affinity epitopes for many therapeutic targets. Genetic code expansion is central to the success of these technologies, allowing researchers to surpass the intrinsic capabilities of the ribosome and access new, genetically encoded materials for these selections. Here, we review techniques for the chemical expansion of genetically encoded libraries, their abilities and limits, and opportunities for further development. Importantly, we also discuss methods and metrics used to assess the efficiency of modification and library diversity with these new techniques.

Generation of a Large Peptide Phage Display Library by Self-Ligation of Whole-Plasmid PCR Product

The success of phage display, used for developing target-specific binders based on peptides and proteins, depends on the size and diversity of the library screened, but generating large libraries of phage-encoded polypeptides remains challenging. New peptide phage display libraries developed in recent years rarely contained more than 1 billion clones, which appears to have become the upper size limit for libraries generated with reasonable effort. Here, we established a strategy based on whole-plasmid PCR and self-ligation to clone a library with more than 2 × 10¹⁰ members. The enormous library size could be obtained through amplifying the entire vector DNA by PCR, which omitted the step of vector isolation from bacterial cells, and through appending DNA coding for the peptide library via a PCR primer, which enabled efficient DNA circularization by end-ligation to facilitate the difficult step of vector-insertion of DNA fragments. Panning the peptide repertoires against a target yielded high-affinity ligands and validated the quality of the library and thus the new library cloning strategy. This simple and efficient strategy places larger libraries within reach for nonspecialist researchers to hopefully expand the possible targets of phage display applications.

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/.

An amber obligate active site-directed ligand evolution technique for phage display

Although noncanonical amino acids (ncAAs) were first incorporated into phage libraries through amber suppression nearly two decades ago, their application for use in drug discovery has been limited due to inherent library bias towards sense-containing phages. Here, we report a technique based on superinfection immunity of phages to enrich amber-containing clones, thus avoiding the observed bias that has hindered incorporation of ncAAs into phage libraries. We then take advantage of this technique for development of active site-directed ligand evolution of peptides, where the ncAA serves as an anchor to direct the binding of its peptides to the target’s active site. To demonstrate this, phage-displayed peptide libraries are developed that contain a genetically encoded butyryl lysine and are subsequently used to select for ligands that bind SIRT2. These ligands are then modified to develop low nanomolar inhibitors of SIRT2.

Most epigenetic regulator inhibitors target tunnels of active sites, rather than the peptide binding groove, leading to concerns with low selectivity. Here the authors use an amber obligate phage library to rapidly identify isoform-selective inhibitors of SIRT2.

Exploring the Post-translational Enzymology of PaaA by mRNA Display

PaaA is a RiPP enzyme that catalyzes the transformation of two glutamic acid residues within a substrate peptide into the bicyclic core of Pantocin A. Here, for the first time, we use mRNA display techniques to understand RiPP enzyme-substrate interactions to illuminate PaaA substrate recognition. Additionally, our data revealed insights into the enzymatic timing of glutamic acid modification. The technique developed is quite sensitive and a significant advancement over current RiPP studies and opens the door to enzyme modified mRNA display libraries for natural product-like inhibitor pans.

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.

Evolving a Peptide: Library Platforms and Diversification Strategies

Peptides are widely used in pharmaceutical industry as active pharmaceutical ingredients, versatile tools in drug discovery, and for drug delivery. They find themselves at the crossroads of small molecules and proteins, possessing favorable tissue penetration and the capability to engage into specific and high-affinity interactions with endogenous receptors. One of the commonly employed approaches in peptide discovery and design is to screen combinatorial libraries, comprising a myriad of peptide variants of either chemical or biological origin. In this review, we focus mainly on recombinant peptide libraries, discussing different platforms for their display or expression, and various diversification strategies for library design. We take a look at well-established technologies as well as new developments and future directions.

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.

Peptide design by optimization on a data-parameterized protein interaction landscape

Many applications in protein engineering require optimizing multiple protein properties simultaneously, such as binding one target but not others or binding a target while maintaining stability. Such multistate design problems require navigating a high-dimensional space to find proteins with desired characteristics. A model that relates protein sequence to functional attributes can guide design to solutions that would be hard to discover via screening. In this work, we measured thousands of protein-peptide binding affinities with the high-throughput interaction assay amped SORTCERY and used the data to parameterize a model of the alpha-helical peptide-binding landscape for three members of the Bcl-2 family of proteins: Bcl-x_L, Mcl-1, and Bfl-1. We applied optimization protocols to explore extremes in this landscape to discover peptides with desired interaction profiles. Computational design generated 36 peptides, all of which bound with high affinity and specificity to just one of Bcl-x_L, Mcl-1, or Bfl-1, as intended. We designed additional peptides that bound selectively to two out of three of these proteins. The designed peptides were dissimilar to known Bcl-2-binding peptides, and high-resolution crystal structures confirmed that they engaged their targets as expected. Excellent results on this challenging problem demonstrate the power of a landscape modeling approach, and the designed peptides have potential uses as diagnostic tools or cancer therapeutics.

Display Selection of Exotic Macrocyclic Peptides Expressed under a Radically Reprogrammed 23 Amino Acid Genetic Code

Bioactive naturally occurring macrocyclic peptides often exhibit a strong bias for hydrophobic residues. Recent advances in in vitro display technologies have made possible the identification of potent macrocyclic peptide ligands to protein targets of interest. However, such approaches have so far been restricted to using libraries composed of peptides containing mixtures of hydrophobic and hydrophilic/charged amino acids encoded by the standard genetic code. In the present study, we have demonstrated ribosomal expression of exotic macrocyclic peptides under a radically reprogrammed, relatively hydrophobic, genetic code, comprising 12 proteinogenic and 11 nonproteinogenic amino acids. Screening of this library for affinity to the interleukin-6 receptor (IL6R) as a case study successfully identified exotic macrocyclic peptide ligands with high affinity, validating the feasibility of this approach for the discovery of relatively hydrophobic exotic macrocyclic peptide ligands.

Genetically-encoded fragment-based discovery of glycopeptide ligands for DC-SIGN

We have employed genetically-encoded fragment-based discovery to identify novel glycopeptides with affinity for the dendritic cell receptor DC-SIGN. Starting from libraries of 10⁸ mannose-conjugated peptides, we identified glycopeptides that exhibited up to a 650-fold increase in multivalent binding affinity for DC-SIGN, which is also preserved in cells. Monovalently, our most potent glycopeptides have a similar potency to a Man₃ oligosaccharide, representing a 15-fold increase in activity compared to mannose. These compounds represent the first examples of glycopeptide ligands that target the CRD of DC-SIGN. The natural framework of glycopeptide conjugates and the simplicity of orthogonal conjugation to make these glycopeptides anticipates a promising future for development of DC-SIGN-targeting moieties.

Inhibitors of protein-protein interactions (PPIs): an analysis of scaffold choices and buried surface area

Protein-protein interactions (PPI) were once considered 'undruggable', but clinical successes, driven by advanced methods in drug discovery, have challenged that notion. Here, we review the last three years of literature on PPI inhibitors to understand what is working and why. From the 66 recently reported PPI inhibitors, we found that the average molecular weight was significantly greater than 500Da, but that this trend was driven, in large part, by the contribution of peptide-based compounds. Despite differences in average molecular weight, we found that compounds based on small molecules or peptides were almost equally likely to be potent inhibitors (K_D<1μM). Finally, we found PPIs with buried surface area (BSA) less than 2000Ų were more likely to be inhibited by small molecules, while PPIs with larger BSA values were typically inhibited by peptides. PPIs with BSA values over 4000Ų seemed to create a particular challenge, especially for orthosteric small molecules. Thus, it seems important to choose the inhibitor scaffold based on the properties of the target interaction. Moreover, this survey suggests a (more nuanced) conclusion to the question of whether PPIs are good drug targets; namely, that some PPIs are readily 'druggable' given the right choice of scaffold, while others still seem to deserve the 'undruggable' moniker.

Biopanning data bank 2018: hugging next generation phage display

Database URL

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