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Adeno-associated viruses (AAVs) hold tremendous promise as delivery vectors for gene therapies. AAVs have been successfully engineered-for instance, for more efficient and/or cell-specific delivery to numerous tissues-by creating large, diverse starting libraries and selecting for desired properties. However, these starting libraries often contain a high proportion of variants unable to assemble or package their genomes, a prerequisite for any gene delivery goal. Here, we present and showcase a machine learning (ML) method for designing AAV peptide insertion libraries that achieve fivefold higher packaging fitness than the standard NNK library with negligible reduction in diversity. To demonstrate our ML-designed librarys utility for downstream engineering goals, we show that it yields approximately 10-fold more successful variants than the NNK library after selection for infection of human brain tissue, leading to a promising glial-specific variant. Moreover, our design approach can be applied to other types of libraries for AAV and beyond.

Here, we present the second generation of our bicyclic peptide library (NTB), featuring a stereodiversified structure and a simplified construction strategy. We utilized a tandem ring-opening metathesis and ring-closing metathesis reaction (ROM-RCM) to cyclize the linear peptide library in a single step, representing the first reported instance of this reaction being applied to the preparation of macrocyclic peptides. Moreover, the resulting bicyclic peptide can be easily linearized for MS/MS sequencing with a one-step deallylation process. We employed this library to screen against the E363-R378 epitope of MYC and identified several MYC-targeting bicyclic peptides. Subsequent in vitro cell studies demonstrated that one candidate, NT-B2R, effectively suppressed MYC transcription activities and cell proliferation.

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.

Short sequences that mediate interactions with modular binding domains are ubiquitous throughout eukaryotic proteomes. Networks of short linear motifs (SLiMs) and their corresponding binding domains orchestrate many cellular processes, and the low mutational barrier to evolving novel interactions provides a way for biological systems to rapidly sample selectable phenotypes. Mapping SLiM binding specificity and the rules that govern SLiM evolution is fundamental to uncovering the pathways regulated by these networks and developing the tools to manipulate them. We used high‐throughput screening of the human proteome to identify sequences that bind to the Enabled/VASP homology 1 (EVH1) domain of the postsynaptic density scaffolding protein Homer1. This expanded our understanding of the determinants of Homer EVH1 binding preferences and defined a new motif that can facilitate the discovery of additional Homer‐mediated interactions. Interestingly, the Homer1 EVH1 domain preferentially binds to sequences containing an N‐terminally overlapping motif that is bound by the paralogous family of Ena/VASP actin polymerases, and many of these sequences can bind to EVH1 domains from both protein families. We provide evidence from orthologous EVH1 domains in pre‐metazoan organisms that the overlap in human Ena/VASP and Homer binding preferences corresponds to an incomplete divergence from a common Ena/VASP ancestor. Given this overlap in binding profiles, promiscuous sequences that can be recognized by both families either achieve specificity through extrinsic regulatory strategies or may provide functional benefits via multi‐specificity. This may explain why these paralogs incompletely diverged despite the accessibility of further diverged isoforms. [ABSTRACT FROM AUTHOR]

Objective To screen and identify new human sperm specific antigen epitopes from candidate sperm-specific antigen epitope peptides using phage display random peptide library technolog and bioinformatics methods. Methods Candidate sperm-specific epitope peptide monomers and trimers were synthesized by solid phase polypeptide synthesis. Dot immunoblotting and enzyme-linked immunosorbent assay (ELISA) were used to detect the immune reaction of the peptides with anti-sperm antibody (ASA) positive serum. ELISA was used to detect antibody titers against candidate sperm-specific epitope peptides in serum of immunized mice. The effects of the sera of the mice immunized with the candidate sperm-specific epitope peptide on human spermatozoa were examined by computer aided sperm analysis. Results High performance liquid chromatography and mass spectrometry showed that the purity and structure of the synthesized candidate sperm-specific epitope peptide were in accordance with the design. Blot and ELISA results indicated that the sperm-specific epitope peptide with the amino acid sequence n-TRRIHRHMTIRR-c and its trimers displayed strong immune response to 17 of 35 ASA positive sera. The serum from mice immunized with the peptide and its trimers significantly attenuated the sperm motility parameters compared with serum from the control group (P < 0. 05), with trimeric-induced decrease in motility parameters being particularly significant. (P<0.01). Conclusion The dodecapeptide with amino acid sequence n-TRRIHRHMTIRR-c is a novel human sperm-specific epitope peptide. [ABSTRACT FROM AUTHOR]

MotivationDriven by technological advances, the throughput and cost of mass spectrometry (MS) proteomics experiments have improved by orders of magnitude in recent decades. Spectral library searching is a common approach to annotating experimental mass spectra by matching them against large libraries of reference spectra corresponding to known peptides. An important disadvantage, however, is that only peptides included in the spectral library can be found, whereas novel peptides, such as those with unexpected post-translational modifications (PTMs), will remain unknown. Open modification searching (OMS) is an increasingly popular approach to annotate modified peptides based on partial matches against their unmodified counterparts. Unfortunately, this leads to very large search spaces and excessive runtimes, which is especially problematic considering the continuously increasing sizes of MS proteomics datasets.ResultsWe propose an OMS algorithm, called HOMS-TC, that fully exploits parallelism in the entire pipeline of spectral library searching. We designed a new highly parallel encoding method based on the principle of hyperdimensional computing to encode mass spectral data to hypervectors while minimizing information loss. This process can be easily parallelized since each dimension is calculated independently. HOMS-TC processes two stages of existing cascade search in parallel and selects the most similar spectra while considering PTMs. We accelerate HOMS-TC on NVIDIA's tensor core units, which is emerging and readily available in the recent graphics processing unit (GPU). Our evaluation shows that HOMS-TC is 31× faster on average than alternative search engines and provides comparable accuracy to competing search tools.Availability and implementationHOMS-TC is freely available under the Apache 2.0 license as an open-source software project at https://github.com/tycheyoung/homs-tc.

In vitro biopanning platforms using synthetic phage display antibody libraries have enabled the identification of antibodies against antigens that were once thought to be beyond the scope of immunization. Applying these methods against challenging targets remains a critical challenge. Here, we present a new biopanning pipeline, RAPID (Rare Antibody Phage Isolation and Discrimination), for the identification of rare high-affinity antibodies against challenging targets. RAPID biopanning uses fluorescent labeled phage displayed fragment antigen-binding (Fab) antibody libraries for the isolation of high-affinity binders with fluorescent activated sorting. Subsequently, discriminatory hit screening is performed with a biolayer interferometry (BLI) method, BIAS (Biolayer Interferometry Antibody Screen), where candidate binders are ranked and prioritized according to their estimated kinetic off rates. Previously reported antibodies were used to develop the methodology, and the RAPID biopanning pipeline was applied to three challenging targets (CHIP, Gαq, and CS3D), enabling the identification of high-affinity antibodies.

The sandwich format immunoassay is generally more sensitive and specific than more common assay formats, including direct, indirect, or competitive. A sandwich assay, however, requires two receptors to bind non-competitively to the target analyte. Typically, pairs of antibodies (Abs) or antibody fragments (Fabs) that are capable of forming a sandwiching with the target are identified through a slow, guess-and-check method with panels of candidate binding partners. Additionally, sandwich assays that are reliant on commercial antibodies can suffer from changes to reagent quality outside the researchers' control. This report presents a reimagined and simplified phage display selection protocol that directly identifies sandwich binding peptides and Fabs. The approach yielded two sandwich pairs, one peptide-peptide and one Fab-peptide sandwich for the cancer and Parkinson's disease biomarker DJ-1. Requiring just a few weeks to identify, the sandwich pairs delivered apparent affinity that is comparable to other commercial peptide and antibody sandwiches. The results reported here could expand the availability of sandwich binding partners for a wide range of clinical biomarker assays.

Human serum albumin (HSA) is the most abundant protein in human blood plasma. It plays a critical role in the native transportation of numerous drugs, metabolites, nutrients, and small molecules. HSA has been successfully used clinically as a noncovalent carrier for insulin (e.g., Levemir), GLP-1 (e.g., Liraglutide), and paclitaxel (e.g., Abraxane). Site-specific bioconjugation strategies for HSA only would greatly expand its role as the biocompatible, non-toxic platform for theranostics purposes. Using the enabling one-bead one-compound (OBOC) technology, we generated combinatorial peptide libraries containing myristic acid, a well-known binder to HSA at Sudlow I and II binding pockets, and an acrylamide. We then used HSA as a probe to screen the OBOC myristylated peptide libraries for reactive affinity elements (RAEs) that can specifically and covalently ligate to the lysine residue at the proximity of these pockets. Several RAEs have been identified and confirmed to be able to conjugate to HSA covalently. The conjugation can occur at physiological pH and proceed with a high yield within 1 h at room temperature. Tryptic peptide profiling of derivatized HSA has revealed two lysine residues (K225 and K414) as the conjugation sites, which is much more specific than the conventional lysine labeling strategy with N-hydroxysuccinimide ester. The RAE-driven site-specific ligation to HSA was found to occur even in the presence of other prevalent blood proteins such as immunoglobulin or whole serum. Furthermore, these RAEs are orthogonal to the maleimide-based conjugation strategy for Cys34 of HSA. Together, these attributes make the RAEs the promising leads to further develop in vitro and in vivo HSA bioconjugation strategies for numerous biomedical applications.

Chimeric antigen receptor (CAR) costimulatory domains derived from native immune receptors steer the phenotypic output of therapeutic T cells. We constructed a library of CARs containing ~2300 synthetic costimulatory domains, built from combinations of 13 signaling motifs. These CARs promoted diverse human T cell fates, which were sensitive to motif combinations and configurations. Neural networks trained to decode the combinatorial grammar of CAR signaling motifs allowed extraction of key design rules. For example, non-native combinations of motifs that bind tumor necrosis factor receptor-associated factors (TRAFs) and phospholipase C gamma 1 (PLCγ1) enhanced cytotoxicity and stemness associated with effective tumor killing. Thus, libraries built from minimal building blocks of signaling, combined with machine learning, can efficiently guide engineering of receptors with desired phenotypes.

Newer solid‐phase peptide synthesis and release strategies enable the production of short peptides with high purity, allowing direct screening for desired bioactivity without prior chromatographic purification. However, the maximum number of peptides that can currently be synthesized per microplate reactor is 96, allowing the parallel synthesis of 384 peptides in modern devices that have space for 4 microplate reactors. To synthesize larger numbers of peptides, we modified a commercially available peptide synthesizer to enable the production of peptides in 384‐well plates, which allows the synthesis of 1,536 peptides in one run (4 × 384 peptides). We report new hardware components and customized software that allowed for the synthesis of 1,536 short peptides in good quantity (average > 0.5 μmol), at high concentration (average > 10 mM), and decent purity without purification (average > 80%). The high‐throughput peptide synthesis, which we developed with peptide drug development in mind, may be widely used for peptide library synthesis and screening, antibody epitope scanning, epitope mimetic development, or protease/kinase substrate screening. [ABSTRACT FROM AUTHOR]

Ferritin, widely present in liver and spleen tissue, is considered as a serological biomarker for liver diseases and cancers. The detection of ferritin may be an important tool in health diagnosis. In this study, 14 non-immunized chicken spleens were utilized to construct a single-chain fragment (scFv) phage library. After 4 rounds of panning, 7 unique clones were obtained. The optimal clone was further screened and combined with NanoLuc luciferase (Nluc) as a dual functional immunoprobe to bioluminescent enzyme immunoassay (BLEIA), which was twice as sensitive as its parental scFv-based double-sandwich enzyme-linked immunoassay (ds-ELISA). The cross-reactivity analysis revealed that the proposed methods were highly selective and suitable for clinical detection. To further verify the performance of the immunoassays, serum samples were tested by the proposed methods and a commercial ELISA kit, and there was a good correlation between the results. These results suggested that scFv fused with Nluc might be a powerful dual functional tool for rapid, practically reliable, and highly sensitive ferritin detection.

Background: Systemic AA amyloidosis is a world-wide occurring protein misfolding disease in humans and animals that arises from the formation of amyloid fibrils from serum amyloid A (SAA) protein and their deposition in multiple organs. Objective: To identify new agents that prevent fibril formation from SAA protein and to determine their mode of action. Materials and Methods: We used a cell model for the formation of amyloid deposits from SAA protein to screen a library of peptides and small proteins, which were purified from human hemofiltrate. To clarify the inhibitory mechanism the obtained inhibitors were characterised in cell-free fibril formation assays and other biochemical methods. Results: We identified lysozyme as an inhibitor of SAA fibril formation. Lysozyme antagonised fibril formation both in the cell model as well as in cell-free fibril formation assays. The protein binds SAA with a dissociation constant of 16.5 ± 0.6 mM, while the binding site on SAA is formed by segments of positively charged amino acids. Conclusion: Our data imply that lysozyme acts in a chaperone-like fashion and prevents the aggregation of SAA protein through direct, physical interactions. [ABSTRACT FROM AUTHOR]

The predominant approach for antibody generation remains animal immunization, which can yield exceptionally selective and potent antibody clones owing to the powerful evolutionary process of somatic hypermutation. However, animal immunization is inherently slow, not always accessible and poorly compatible with many antigens. Here, we describe 'autonomous hypermutation yeast surface display' (AHEAD), a synthetic recombinant antibody generation technology that imitates somatic hypermutation inside engineered yeast. By encoding antibody fragments on an error-prone orthogonal DNA replication system, surface-displayed antibody repertoires continuously mutate through simple cycles of yeast culturing and enrichment for antigen binding to produce high-affinity clones in as little as two weeks. We applied AHEAD to generate potent nanobodies against the SARS-CoV-2 S glycoprotein, a G-protein-coupled receptor and other targets, offering a template for streamlined antibody generation at large.

Phage-borne peptides and antibody fragments isolated from phage display libraries have proven to be versatile and valuable reagents for immunoassay development. Due to the lack of convenient and mild-condition methods for the labeling of the phage particles, isolated peptide/protein affinity ligands are commonly removed from the viral particles and conjugated to protein tracers or nanoparticles for analytical use. This abolishes the advantage of isolating ready-to-use affinity binders and creates the risk of affecting the polypeptide activity. To circumvent this problem, we optimized the phage display system to produce phage particles that express the affinity binder on pIII and a polyglycine short peptide fused to pVIII that allows the covalent attachment of tracer molecules employing sortase A. Using a llama heavy chain only variable domain (VHH) against the herbicide 2,4-D on pIII as the model, we showed that the phage can be extensively decorated with a rhodamine-LPETGG peptide conjugate or the protein nanoluciferase (Nluc) equipped with a C-terminal LPETGG peptide. The maximum labeling amounts of rhodamine-LPETGG and Nluc-LPETGG were 1238 ± 63 and 102 ± 16 per phage, respectively. The Nluc-labeled dual display phage was employed to develop a phage bioluminescent immunoassay (P-BLEIA) for the detection of 2,4-D. The limit of detection and 50% inhibition concentration of P-BLEIA were 0.491 and 2.15 ng mL-1, respectively, which represent 16-fold and 8-fold improvement compared to the phage enzyme-linked immunosorbent assay. In addition, the P-BLEIA showed good accuracy for the detection of 2,4-D in spiked samples.

Self-assembling peptides have shown tremendous potential in the fields of material sciences, nanoscience, and medicine. Because of the vast combinatorial space of even short peptides, identification of self-assembling sequences remains a challenge. Herein, we develop an experimental method to rapidly screen a huge array of peptide sequences for self-assembling property, using the one-bead one-compound (OBOC) combinatorial library method. In this approach, peptides on beads are N-terminally capped with nitro-1,2,3-benzoxadiazole, a hydrophobicity-sensitive fluorescence molecule. Beads displaying self-assembling peptides would fluoresce under aqueous environment. Using this approach, we identify eight pentapeptides, all of which are able to self-assemble into nanoparticles or nanofibers. Some of them are able to interact with and are taken up efficiently by HeLa cells. Intracellular distribution varied among these non-toxic peptidic nanoparticles. This simple screening strategy has enabled rapid identification of self-assembling peptides suitable for the development of nanostructures for various biomedical and material applications.

Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is initiated by binding of the viral Spike protein to host receptor angiotensin-converting enzyme 2 (ACE2), followed by fusion of viral and host membranes. Although antibodies that block this interaction are in emergency use as early coronavirus disease 2019 (COVID-19) therapies, the precise determinants of neutralization potency remain unknown. We discovered a series of antibodies that potently block ACE2 binding but exhibit divergent neutralization efficacy against the live virus. Strikingly, these neutralizing antibodies can inhibit or enhance Spike-mediated membrane fusion and formation of syncytia, which are associated with chronic tissue damage in individuals with COVID-19. As revealed by cryoelectron microscopy, multiple structures of Spike-antibody complexes have distinct binding modes that not only block ACE2 binding but also alter the Spike protein conformational cycle triggered by ACE2 binding. We show that stabilization of different Spike conformations leads to modulation of Spike-mediated membrane fusion with profound implications for COVID-19 pathology and immunity.

Peptide-based therapeutics are increasingly pushing to the forefront of biomedicine with their promise of high specificity and low toxicity. Although noncanonical residues can always be used, employing only the natural 20 residues restricts the chemical space to a finite dimension allowing for comprehensive in silico screening. Towards this goal, the dataset comprising all possible di-, tri-, and tetra-peptide combinations of the canonical residues has been previously reported. However, with increasing computational power, the comprehensive set of pentapeptides is now also feasible for screening as the comprehensive set of cyclic peptides comprising four or five residues. Here, we provide both the complete and prefiltered libraries of all di-, tri-, tetra-, and penta-peptide sequences from 20 canonical amino acids and their homodetic (N-to-C-terminal) cyclic homologues. The FASTA, simplified molecular-input line-entry system (SMILES), and structure-data file (SDF)-three dimension (3D) libraries can be readily used for screening against protein targets. We also provide a simple method and tool for conducting identity-based filtering. Access to this dataset will accelerate small peptide screening workflows and encourage their use in drug discovery campaigns. As a case study, the developed library was screened against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease to identify potential small peptide inhibitors.

G protein-coupled receptors (GPCRs) are a group of seven-transmembrane receptor proteins that have proven to be successful drug targets. Antibodies are becoming an increasingly promising modality to target these receptors due to their unique properties, such as exquisite specificity, long half-life, and fewer side effects, and their improved pharmacokinetic and pharmacodynamic profiles compared to peptides and small molecules, which results from their more favorable biodistribution. To date, there are only two US Food and Drug Administration-approved GPCR antibody drugs, namely erenumab and mogamulizumab, and this highlights the challenges encountered in identifying functional antibodies against GPCRs. Utilizing Twists precision DNA writing technologies, we have created a GPCR-focused phage display library with 1 × 1010 diversity. Specifically, we mined endogenous GPCR binding ligand and peptide sequences and incorporated these binding motifs into the heavy chain complementarity-determining region 3 in a synthetic antibody library. Glucagon-like peptide-1 receptor (GLP-1 R) is a class B GPCR that acts as the receptor for the incretin GLP-1, which is released to regulate insulin levels in response to food intake. GLP-1 R agonists have been widely used to increase insulin secretion to lower blood glucose levels for the treatment of type 1 and type 2 diabetes, whereas GLP-1 R antagonists have applications in the treatment of severe hypoglycemia associated with bariatric surgery and hyperinsulinomic hypoglycemia. Here we present the discovery and creation of both antagonistic and agonistic GLP-1 R antibodies by panning this GPCR-focused phage display library on a GLP-1 R-overexpressing Chinese hamster ovary cell line and demonstrate their in vitro and in vivo functional activity.

Antibodies against Aß amyloid are indispensable research tools and potential therapeutics for Alzheimer's disease. They display several unusual properties, such as specificity for aggregated forms of the peptide, the ability to distinguish polymorphic aggregate structures, and the ability to recognize generic aggregation-related epitopes formed by unrelated amyloid sequences. Understanding the mechanisms underlying these unusual properties and the structures of their corresponding epitopes is crucial for the understanding why antibodies display different therapeutic activities and for the development of more effective therapeutic agents. Here we employed a novel "epitomic" approach to map the fine structure of the epitopes of 28 monoclonal antibodies against amyloid-beta using immunoselection of random sequences from a phage display library, deep sequencing, and pattern analysis to define the critical sequence elements recognized by the antibodies. Although most of the antibodies map to major linear epitopes in the amino terminal 1 to 14 residues of Aß, the antibodies display differences in the target sequence residues that are critical for binding and in their individual preferences for nontarget residues, indicating that the antibodies bind to alternative conformations of the sequence by different mechanisms. Epitomic analysis also identifies discontinuous, nonoverlapping sequence Aß segments that may constitute the conformational epitopes that underlie the aggregation specificity of antibodies. Aggregation-specific antibodies recognize sequences that display a significantly higher predicted propensity for forming amyloid than antibodies that recognize the monomer, indicating that the ability of random sequences to aggregate into amyloid is a critical element of their binding mechanism.

Neutralizing agents against SARS-CoV-2 are urgently needed for the treatment and prophylaxis of COVID-19. Here, we present a strategy to rapidly identify and assemble synthetic human variable heavy (VH) domains toward neutralizing epitopes. We constructed a VH-phage library and targeted the angiotensin-converting enzyme 2 (ACE2) binding interface of the SARS-CoV-2 Spike receptor-binding domain (Spike-RBD). Using a masked selection approach, we identified VH binders to two non-overlapping epitopes and further assembled these into multivalent and bi-paratopic formats. These VH constructs showed increased affinity to Spike (up to 600-fold) and neutralization potency (up to 1,400-fold) on pseudotyped SARS-CoV-2 virus when compared to standalone VH domains. The most potent binder, a trivalent VH, neutralized authentic SARS-CoV-2 with a half-maximal inhibitory concentration (IC50) of 4.0 nM (180 ng ml-1). A cryo-EM structure of the trivalent VH bound to Spike shows each VH domain engaging an RBD at the ACE2 binding site, confirming our original design strategy.

Neutralizing agents against SARS-CoV-2 are urgently needed for the treatment and prophylaxis of COVID-19. Here, we present a strategy to rapidly identify and assemble synthetic human variable heavy (VH) domains toward neutralizing epitopes. We constructed a VH-phage library and targeted the angiotensin-converting enzyme 2 (ACE2) binding interface of the SARS-CoV-2 Spike receptor-binding domain (Spike-RBD). Using a masked selection approach, we identified VH binders to two non-overlapping epitopes and further assembled these into multivalent and bi-paratopic formats. These VH constructs showed increased affinity to Spike (up to 600-fold) and neutralization potency (up to 1,400-fold) on pseudotyped SARS-CoV-2 virus when compared to standalone VH domains. The most potent binder, a trivalent VH, neutralized authentic SARS-CoV-2 with a half-maximal inhibitory concentration (IC50) of 4.0 nM (180 ng ml-1). A cryo-EM structure of the trivalent VH bound to Spike shows each VH domain engaging an RBD at the ACE2 binding site, confirming our original design strategy.

An essential mechanism for severe acute respiratory syndrome coronavirus 1 (SARS-CoV-1) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection begins with the viral spike protein binding to the human receptor protein angiotensin-converting enzyme II (ACE2). Here, we describe a stepwise engineering approach to generate a set of affinity optimized, enzymatically inactivated ACE2 variants that potently block SARS-CoV-2 infection of cells. These optimized receptor traps tightly bind the receptor binding domain (RBD) of the viral spike protein and prevent entry into host cells. We first computationally designed the ACE2-RBD interface using a two-stage flexible protein backbone design process that improved affinity for the RBD by up to 12-fold. These designed receptor variants were affinity matured an additional 14-fold by random mutagenesis and selection using yeast surface display. The highest-affinity variant contained seven amino acid changes and bound to the RBD 170-fold more tightly than wild-type ACE2. With the addition of the natural ACE2 collectrin domain and fusion to a human immunoglobulin crystallizable fragment (Fc) domain for increased stabilization and avidity, the most optimal ACE2 receptor traps neutralized SARS-CoV-2-pseudotyped lentivirus and authentic SARS-CoV-2 virus with half-maximal inhibitory concentrations (IC50s) in the 10- to 100-ng/mL range. Engineered ACE2 receptor traps offer a promising route to fighting infections by SARS-CoV-2 and other ACE2-using coronaviruses, with the key advantage that viral resistance would also likely impair viral entry. Moreover, such traps can be predesigned for viruses with known entry receptors for faster therapeutic response without the need for neutralizing antibodies isolated from convalescent patients.

The 2018 Nobel Prize in Chemistry recognized in vitro evolution, including the development by George Smith and Gregory Winter of phage display, a technology for engineering the functional capabilities of antibodies into viruses. Such bacteriophages solve inherent problems with antibodies, including their high cost, thermal lability, and propensity to aggregate. While phage display accelerated the discovery of peptide and protein motifs for recognition and binding to proteins in a variety of applications, the development of biosensors using intact phage particles was largely unexplored in the early 2000s. Virus particles, 16.5 MDa in size and assembled from thousands of proteins, could not simply be substituted for antibodies in any existing biosensor architectures.Incorporating viruses into biosensors required us to answer several questions: What process will allow the incorporation of viruses into a functional bioaffinity layer? How can the binding of a protein disease marker to a virus particle be electrically transduced to produce a signal? Will the variable salt concentration of a bodily fluid interfere with electrical transduction? A completely new biosensor architecture and a new scheme for electrical transduction of the binding of molecules to viruses were required.This Account describes the highlights of a research program launched in 2006 that answered these questions. These efforts culminated in 2018 in the invention of a biosensor specifically designed to interface with virus particles: the Virus BioResistor (VBR). The VBR is a resistor consisting of a conductive polymer matrix in which M13 virus particles are entrained. The electrical impedance of this resistor, measured across 4 orders of magnitude in frequency, simultaneously measures the concentration of a target protein and the ionic conductivity of the medium in which the resistor is immersed. Large signal amplitudes coupled with the inherent simplicity of the VBR sensor design result in high signal-to-noise ratio (S/N > 100) and excellent sensor-to-sensor reproducibility. Using this new device, we have measured the urinary bladder cancer biomarker nucleic acid deglycase (DJ-1) in urine samples. This optimized VBR is characterized by extremely low sensor-to-sensor coefficients of variation in the range of 3-7% across the DJ-1 binding curve down to a limit of quantitation of 30 pM, encompassing 4 orders of magnitude in concentration.

Engineering sequence-specific antibodies (Abs) against phosphotyrosine (pY) motifs embedded in folded polypeptides remains highly challenging because of the stringent requirement for simultaneous recognition of the pY motif and the surrounding folded protein epitope. Here, we present a method named phosphotyrosine Targeting by Recombinant Ab Pair, or pY-TRAP, for in vitro engineering of binders for native pY proteins. Specifically, we create the pY protein by unnatural amino acid misincorporation, mutagenize a universal pY-binding Ab to create a first binder B1 for the pY motif on the pY protein, and then select against the B1-pY protein complex for a second binder B2 that recognizes the composite epitope of B1 and the pY-containing protein complex. We applied pY-TRAP to create highly specific binders to folded Ub-pY59, a rarely studied Ub phosphoform exclusively observed in cancerous tissues, and ZAP70-pY248, a kinase phosphoform regulated in feedback signaling pathways in T cells. The pY-TRAPs do not have detectable binding to wild-type proteins or to other pY peptides or proteins tested. This pY-TRAP approach serves as a generalizable method for engineering sequence-specific Ab binders to native pY proteins.

Proteolysis is a major posttranslational regulator of biology inside and outside of cells. Broad identification of optimal cleavage sites and natural substrates of proteases is critical for drug discovery and to understand protease biology. Here, we present a method that employs two genetically encoded substrate phage display libraries coupled with next generation sequencing (SPD-NGS) that allows up to 10,000-fold deeper sequence coverage of the typical six- to eight-residue protease cleavage sites compared to state-of-the-art synthetic peptide libraries or proteomics. We applied SPD-NGS to two classes of proteases, the intracellular caspases, and the ectodomains of the sheddases, ADAMs 10 and 17. The first library (Lib 10AA) allowed us to identify 104 to 105 unique cleavage sites over a 1,000-fold dynamic range of NGS counts and produced consensus and optimal cleavage motifs based position-specific scoring matrices. A second SPD-NGS library (Lib hP), which displayed virtually the entire human proteome tiled in contiguous 49 amino acid sequences with 25 amino acid overlaps, enabled us to identify candidate human proteome sequences. We identified up to 104 natural linear cut sites, depending on the protease, and captured most of the examples previously identified by proteomics and predicted 10- to 100-fold more. Structural bioinformatics was used to facilitate the identification of candidate natural protein substrates. SPD-NGS is rapid, reproducible, simple to perform and analyze, inexpensive, and renewable, with unprecedented depth of coverage for substrate sequences, and is an important tool for protease biologists interested in protease specificity for specific assays and inhibitors and to facilitate identification of natural protein substrates.

Comprehensive understanding of the serological response to SARS-CoV-2 infection is important for both pathophysiologic insight and diagnostic development. Here, we generate a pan-human coronavirus programmable phage display assay to perform proteome-wide profiling of coronavirus antigens enriched by 98 COVID-19 patient sera. Next, we use ReScan, a method to efficiently sequester phage expressing the most immunogenic peptides and print them onto paper-based microarrays using acoustic liquid handling, which isolates and identifies nine candidate antigens, eight of which are derived from the two proteins used for SARS-CoV-2 serologic assays: spike and nucleocapsid proteins. After deployment in a high-throughput assay amenable to clinical lab settings, these antigens show improved specificity over a whole protein panel. This proof-of-concept study demonstrates that ReScan will have broad applicability for other emerging infectious diseases or autoimmune diseases that lack a valid biomarker, enabling a seamless pipeline from antigen discovery to diagnostic using one recombinant protein source.

We report on a cyclic peptide that inhibits matrix metalloproteinase-2 (MMP2) activation with a low-nM-level potency. This inhibitor specifically binds to the D570-A583 epitope on proMMP2 and interferes with the protein-protein interaction (PPI) between proMMP2 and tissue inhibitor of metalloproteinases-2 (TIMP2), thereby preventing the TIMP2-assisted proMMP2 activation process. We developed this cyclic peptide inhibitor through an epitope-targeted library screening process and validated its binding to proMMP2. Using a human melanoma cell line, we demonstrated the cyclic peptide's ability to modulate cellular MMP2 activities and inhibit cell migration. These results provide the first successful example of targeting the PPI between proMMP2 and TIMP2, confirming the feasibility of an MMP2 inhibition strategy that has been sought after for 2 decades.

The identification of autoantigens remains a critical challenge for understanding and treating autoimmune diseases. Autoimmune polyendocrine syndrome type 1 (APS1), a rare monogenic form of autoimmunity, presents as widespread autoimmunity with T and B cell responses to multiple organs. Importantly, autoantibody discovery in APS1 can illuminate fundamental disease pathogenesis, and many of the antigens found in APS1 extend to more common autoimmune diseases. Here, we performed proteome-wide programmable phage-display (PhIP-Seq) on sera from a cohort of people with APS1 and discovered multiple common antibody targets. These novel APS1 autoantigens exhibit tissue-restricted expression, including expression in enteroendocrine cells, pineal gland, and dental enamel. Using detailed clinical phenotyping, we find novel associations between autoantibodies and organ-restricted autoimmunity, including a link between anti-KHDC3L autoantibodies and premature ovarian insufficiency, and between anti-RFX6 autoantibodies and diarrheal-type intestinal dysfunction. Our study highlights the utility of PhIP-Seq for extensively interrogating antigenic repertoires in human autoimmunity and the importance of antigen discovery for improved understanding of disease mechanisms.

Objective: Despite of antiviral drugs and successful treatment, an effective vaccine against hepatitis C virus (HCV)infection is still required. Recently, bioinformatic methods same as prediction algorithms, have greatly contributed tothe use of peptides in the design of immunogenic vaccines. Therefore, finding more conserved sites on the surfaceglycoproteins (E1 and E2) of HCV, as major targets to design an effective vaccine against genetically different virusesin each genotype was the goal of the study. Materials and Methods: In this experimental study, 100 entire sequences of E1 and E2 were retrieved from the NCBIwebsite and analyzed in terms of mutations and critical sites by Bioedit 7.7.9, MEGA X software. Furthermore, HCV-1asamples were obtained from some infected people in Iran, and reverse transcriptase-polymerase chain reaction (RTPCR)assay was optimized to amplify their E1 and E2 genes. Moreover, all three-dimensional structures of E1 andE2 downloaded from the PDB database were analyzed by YASARA. In the next step, three interest areas of humoralimmunity in the E2 glycoprotein were evaluated. OSPREY3.0 protein design software was performed to increase theaffinity to neutralizing antibodies in these areas. Results: We found the effective in silico binding affinity of residues in three broadly neutralizing epitopes of E2glycoprotein. First, positions that have substitution capacity were detected in these epitopes. Furthermore, residuesthat have high stability for substitution in these situations were indicated. Then, the mutants with the strongest affinityto neutralize antibodies were predicted. I414M, T416S, I422V, I414M-T416S, and Q412N-I414M-T416S substitutionstheoretically were exhibited as mutants with the best affinity binding. Conclusion: Using an innovative filtration strategy, the residues of E2 epitopes which have the best in silico bindingaffinity to neutralizing antibodies were exhibited and a distinct peptide library platform was designed.

Peptide-based therapeutics are increasingly pushing to the forefront of biomedicine with their promise of high specificity and low toxicity. Although noncanonical residues can always be used, employing only the natural 20 residues restricts the chemical space to a finite dimension allowing for comprehensive in silico screening. Towards this goal, the dataset comprising all possible di-, tri-, and tetra-peptide combinations of the canonical residues has been previously reported. However, with increasing computational power, the comprehensive set of pentapeptides is now also feasible for screening as the comprehensive set of cyclic peptides comprising four or five residues. Here, we provide both the complete and prefiltered libraries of all di-, tri-, tetra-, and penta-peptide sequences from 20 canonical amino acids and their homodetic (N-to-C-terminal) cyclic homologues. The FASTA, simplified molecular-input line-entry system (SMILES), and structure-data file (SDF)-three dimension (3D) libraries can be readily used for screening against protein targets. We also provide a simple method and tool for conducting identity-based filtering. Access to this dataset will accelerate small peptide screening workflows and encourage their use in drug discovery campaigns. As a case study, the developed library was screened against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease to identify potential small peptide inhibitors. [Display omitted] • All possible sequences of di, tri, tetra, and pentapeptides using canonical amino acids provided. • N-to-C-terminal cyclization of all peptides provided. • Methods for the filtration of peptides based on ease of synthesis, solubility, and stability provided. • Methods for the removal of duplicate cyclicpeptides implemented. • The toolkit is used to identify SARS-CoV-2 Mpro inhibitors. [ABSTRACT FROM AUTHOR]

Anticancer peptides (ACPs) are rising as a new strategy for cancer therapy. However, traditional laboratory screening to find and identify novel ACPs from hundreds to thousands of peptides is costly and time consuming. Here, a sequential procedure is applied to identify candidate ACPs from a computer‐generated peptide library inspired by alpha‐lactalbumin, a milk protein with known anticancer properties. A total of 2688 distinct peptides, 5–25 amino acids in length, are generated from alpha‐lactalbumin. In silico ACP screening using the physicochemical and structural filters and three machine learning models lead to the top candidate peptides ALA‐A1 and ALA‐A2. In vitro screening against five human cancer cell lines supports ALA‐A2 as the positive hit. ALA‐A2 selectively kills A549 lung cancer cells in a dose‐dependent manner, with no hemolytic side effects, and acts as a cell penetrating peptide without membranolytic effects. Sequential window acquisition of all theorical fragment ions‐proteomics and functional validation reveal that ALA‐A2 induces autophagy to mediate lung cancer cell death. This approach to identify ALA‐A2 is time and cost‐effective. Further investigations are warranted to elucidate the exact intracellular targets of ALA‐A2. Moreover, these findings support the use of larger computational peptide libraries built upon multiple proteins to further advance ACP research and development. [ABSTRACT FROM AUTHOR]

The United States is currently experiencing an opioid crisis, with more than 47,000 deaths in 2017 due to opioid overdoses. Current approaches for opioid identification and quantification in body fluids include immunoassays and chromatographic methods (e.g., LC-MS, GC-MS), which require expensive instrumentation and extensive sample preparation. Our aim was to develop a portable point-of-care device that can be used for the instant detection of opioids in body fluids. Here, we reported the development of a morphine-sensitive fluorescence-based sensor chip to sensitively detect morphine in the blood using a homogeneous immunoassay without any washing steps. Morphine-sensitive illuminating peptides were identified using a high throughput one-bead one-compound (OBOC) combinatorial peptide library approach. The OBOC libraries contain a large number of random peptides with a molecular rotor dye, malachite green (MG), that are coupled to the amino group on the side chain of lysine at different positions of the peptides. The OBOC libraries were then screened for fluorescent activation under a confocal microscope, using an anti-morphine monoclonal antibody as the screening probe, in the presence and absence of free morphine. Using this novel three-step fluorescent screening assay, we were able to identify the peptide-beads that fluoresce in the presence of an anti-morphine antibody, but lost fluorescence when the free morphine was present. After the positive beads were decoded using automatic Edman microsequencing, the morphine-sensitive illuminating peptides were then synthesized in soluble form, functionalized with an azido group, and immobilized onto microfabricated PEG-array spots on a glass slide. The sensor chip was then evaluated for the detection of morphine in plasma. We demonstrated that this proof-of-concept platform can be used to develop fluorescence-based sensors against morphine. More importantly, this technology can also be applied to the discovery of other novel illuminating peptidic sensors for the detection of illicit drugs and cancer biomarkers in body fluids.

APEX is an engineered peroxidase that catalyzes the oxidation of a wide range of substrates, facilitating its use in a variety of applications from subcellular staining for electron microscopy to proximity biotinylation for spatial proteomics and transcriptomics. To further advance the capabilities of APEX, we used directed evolution to engineer a split APEX tool (sAPEX). A total of 20 rounds of fluorescence activated cell sorting (FACS)-based selections from yeast-displayed fragment libraries, using 3 different surface display configurations, produced a 200-amino-acid N-terminal fragment (with 9 mutations relative to APEX2) called "AP" and a 50-amino-acid C-terminal fragment called "EX". AP and EX fragments were each inactive on their own but were reconstituted to give peroxidase activity when driven together by a molecular interaction. We demonstrate sAPEX reconstitution in the mammalian cytosol, on engineered RNA motifs within a non-coding RNA scaffold, and at mitochondria-endoplasmic reticulum contact sites.

Site-specific protein cleavage is essential for many protein-production protocols and typically requires proteases. We report the development of a chemical protein-cleavage method that is achieved through the use of a sequence-specific nickel-assisted cleavage (SNAC)-tag. We demonstrate that the SNAC-tag can be inserted before both water-soluble and membrane proteins to achieve fusion protein cleavage under biocompatible conditions with efficiency comparable to that of enzymes, and that the method works even when enzymatic cleavages fail.

The current translation of peptides identified through the one-bead one-compound (OBOC) technology into positron emission tomography (PET) imaging agents is a slow process, with a major delay between ligand identification and subsequent lead optimization. This work aims to streamline the development process of 18F-peptide based PET imaging agents to target the integrin αvβ₆. By directly identify αvβ₆⁻targeting peptides from a 9-mer 4-fluorobenzoyl peptide library using the on-bead two-color (OBTC) cell-screening assay, a total of 185 peptide beads were identified and 5 beads sequenced for further evaluation. The lead peptide 1 (VGDLTYLKK(FB), IC50 = 0.45 ± 0.06 μM, 25% stable in serum at 1 h) was further modified at the N-, C-, and bi-termini. C-terminal PEGylation increased the metabolic stability (>95% stable), but decreased binding affinity (IC50 = 3.7 ± 1 μM) was noted. C-terminal extension (1i, VGDLTYLKK(FB)KVART) significantly increased binding affinity for integrin αvβ₆ (IC50 = 0.021 ± 0.002 μM), binding selectivity for αvβ₆-expressing cells (3.1 ± 0.8:1), and the serum stability (>99% stable). Our results demonstrate the challenges in optimizing OBOC-derived peptides, indicate both termini of 1 are sensitive to modifications, and show that further modification of 1 is necessary to demonstrate utility as an 18F-peptide imaging agent.

In this Research Article, a novel inkjet printing technique, micro impact printing (MI printing), is applied for the first time to combinatorial peptide microarray synthesis on amine functionalized microdisc arrays through standard Fmoc chemistry. MI printing shows great advantages in combinatorial peptide microarray synthesis compared with other printing techniques, including (1) a disposable cartridge; (2) a small spot size (80 μm) increases array density; (3) minimal loading volume (0.6 μL) and dead volume (

Using a de novo peptide inhibitor, Corza6 (C6), we demonstrate that the human voltage-gated proton channel (hHv1) is the main pathway for H+ efflux that allows capacitation in sperm and permits sustained reactive oxygen species (ROS) production in white blood cells (WBCs). C6 was identified by a phage-display strategy whereby ∼1 million novel peptides were fabricated on an inhibitor cysteine knot (ICK) scaffold and sorting on purified hHv1 protein. Two C6 peptides bind to each dimeric channel, one on the S3-S4 loop of each voltage sensor domain (VSD). Binding is cooperative with an equilibrium affinity (Kd) of ∼1 nM at -50 mV. As expected for a VSD-directed toxin, C6 inhibits by shifting hHv1 activation to more positive voltages, slowing opening and speeding closure, effects that diminish with membrane depolarization.

The 2017 Dagstuhl Seminar on Computational Proteomics provided an opportunity for a broad discussion on the current state and future directions of the generation and use of peptide tandem mass spectrometry spectral libraries. Their use in proteomics is growing slowly, but there are multiple challenges in the field that must be addressed to further increase the adoption of spectral libraries and related techniques. The primary bottlenecks are the paucity of high quality and comprehensive libraries and the general difficulty of adopting spectral library searching into existing workflows. There are several existing spectral library formats, but none captures a satisfactory level of metadata; therefore, a logical next improvement is to design a more advanced, Proteomics Standards Initiative-approved spectral library format that can encode all of the desired metadata. The group discussed a series of metadata requirements organized into three designations of completeness or quality, tentatively dubbed bronze, silver, and gold. The metadata can be organized at four different levels of granularity: at the collection (library) level, at the individual entry (peptide ion) level, at the peak (fragment ion) level, and at the peak annotation level. Strategies for encoding mass modifications in a consistent manner and the requirement for encoding high-quality and commonly seen but as-yet-unidentified spectra were discussed. The group also discussed related topics, including strategies for comparing two spectra, techniques for generating representative spectra for a library, approaches for selection of optimal signature ions for targeted workflows, and issues surrounding the merging of two or more libraries into one. We present here a review of this field and the challenges that the community must address in order to accelerate the adoption of spectral libraries in routine analysis of proteomics datasets.

Abstract Anticancer peptides (ACPs) are rising as a new strategy for cancer therapy. However, traditional laboratory screening to find and identify novel ACPs from hundreds to thousands of peptides is costly and time consuming. Here, a sequential procedure is applied to identify candidate ACPs from a computer‐generated peptide library inspired by alpha‐lactalbumin, a milk protein with known anticancer properties. A total of 2688 distinct peptides, 5–25 amino acids in length, are generated from alpha‐lactalbumin. In silico ACP screening using the physicochemical and structural filters and three machine learning models lead to the top candidate peptides ALA‐A1 and ALA‐A2. In vitro screening against five human cancer cell lines supports ALA‐A2 as the positive hit. ALA‐A2 selectively kills A549 lung cancer cells in a dose‐dependent manner, with no hemolytic side effects, and acts as a cell penetrating peptide without membranolytic effects. Sequential window acquisition of all theorical fragment ions‐proteomics and functional validation reveal that ALA‐A2 induces autophagy to mediate lung cancer cell death. This approach to identify ALA‐A2 is time and cost‐effective. Further investigations are warranted to elucidate the exact intracellular targets of ALA‐A2. Moreover, these findings support the use of larger computational peptide libraries built upon multiple proteins to further advance ACP research and development.

Objective: Despite of antiviral drugs and successful treatment, an effective vaccine against hepatitis C virus (HCV) infection is still required. Recently, bioinformatic methods same as prediction algorithms, have greatly contributed to the use of peptides in the design of immunogenic vaccines. Therefore, finding more conserved sites on the surface glycoproteins (E1 and E2) of HCV, as major targets to design an effective vaccine against genetically different viruses in each genotype was the goal of the study. Materials and Methods: In this experimental study, 100 entire sequences of E1 and E2 were retrieved from the NCBI website and analyzed in terms of mutations and critical sites by Bioedit 7.7.9, MEGA X software. Furthermore, HCV-1a samples were obtained from some infected people in Iran, and reverse transcriptase-polymerase chain reaction (RTPCR) assay was optimized to amplify their E1 and E2 genes. Moreover, all three-dimensional structures of E1 and E2 downloaded from the PDB database were analyzed by YASARA. In the next step, three interest areas of humoral immunity in the E2 glycoprotein were evaluated. OSPREY3.0 protein design software was performed to increase the affinity to neutralizing antibodies in these areas. Results: We found the effective in silico binding affinity of residues in three broadly neutralizing epitopes of E2 glycoprotein. First, positions that have substitution capacity were detected in these epitopes. Furthermore, residues that have high stability for substitution in these situations were indicated. Then, the mutants with the strongest affinity to neutralize antibodies were predicted. I414M, T416S, I422V, I414M-T416S, and Q412N-I414M-T416S substitutions theoretically were exhibited as mutants with the best affinity binding. Conclusion: Using an innovative filtration strategy, the residues of E2 epitopes which have the best in silico binding affinity to neutralizing antibodies were exhibited and a distinct peptide library platform was designed. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Infection by enterotoxigenic Escherichia coli (ETEC) causes severe watery diarrhea and dehydration in humans. Heat-labile enterotoxin (LT) is a major virulence factor produced by ETEC. LT is one of AB 5 -type toxins, such as Shiga toxin (Stx) and cholera toxin (Ctx), and the B-subunit pentamer is responsible for high affinity binding to the LT-receptor, ganglioside GM1, through multivalent interaction. In this report, we found that Glu51 of the B-subunit plays an essential role in receptor binding compared with other amino acids, such as Glu11, Arg13, and Lys91, all of which were previously shown to be involved in the binding. By targeting Glu51, we identified four tetravalent peptides that specifically bind to the B-subunit pentamer with high affinity by screening tetravalent random-peptide libraries, which were tailored to bind to the B-subunit through multivalent interaction. One of these peptides, GGR-tet, efficiently inhibited the cell-elongation phenotype and the elevation of cellular cAMP levels, both induced by LT. Furthermore, GGR-tet markedly inhibited LT-induced fluid accumulation in the mouse ileum. Thus, GGR-tet represents a novel therapeutic agent against ETEC infection. • Glu51 of the heat-labile enterotoxin (LT) B-subunit is essential in receptor binding. • GGR-tet is a tetravalent peptide that targets Glu51 of the B-subunit. • GGR-tet inhibits the toxicity of LT in cells. • GGR-tet markedly inhibits fluid accumulation in the mouse ileum caused by LT. [ABSTRACT FROM AUTHOR]

Heparan sulfate (HS) is a complex linear polysaccharide that modulates a wide range of biological functions. Elucidating the structure-function relationship of HS has been challenging. Here we report the generation of an HS-mutant mouse lung endothelial cell library by systematic deletion of HS genes expressed in the cell. We used this library to (1) determine that the strictly defined fine structure of HS, not its overall degree of sulfation, is more important for FGF2-FGFR1 signaling; (2) define the epitope features of commonly used anti-HS phage display antibodies; and (3) delineate the fine inter-regulation networks by which HS genes modify HS and chain length in mammalian cells at a cell-type-specific level. Our mutant-cell library will allow robust and systematic interrogation of the roles and related structures of HS in a cellular context.

Protein engineering by directed evolution can alter proteins' structures, properties, and functions. However, membrane proteins, despite their importance to living organisms, remain relatively unexplored as targets for protein engineering and directed evolution. This gap in capabilities likely results from the tendency of membrane proteins to aggregate and fail to overexpress in bacteria cells. For example, the membrane protein caveolin-1 has been implicated in many cell signaling pathways and diseases, yet the full-length protein is too aggregation-prone for detailed mutagenesis, directed evolution, and biophysical characterization. Using a phage-displayed library of full-length caveolin-1 variants, directed evolution with alternating subtractive and functional selections isolated a full-length, soluble variant, termed cavsol, for expression in E. coli. Cavsol folds correctly and binds to its known protein ligands HIV gp41, the catalytic domain of cAMP-dependent protein kinase A, and the polymerase I and transcript release factor. As expected, cavsol does not bind off-target proteins. Cellular studies show that cavsol retains the parent protein's ability to localize at the cellular membrane. Unlike truncated versions of caveolin, cavsol forms large, oligomeric complexes consisting of approximately >50 monomeric units without requiring additional cellular components. Cavsol's secondary structure is a mixture of α-helices and β-strands. Isothermal titration calorimetry experiments reveal that cavsol binds to gp41 and PKA with low micromolar binding affinity (KD). In addition to the insights into caveolin structure and function, the approach applied here could be generalized to other membrane proteins.

Cell penetrating peptides (CPPs) offer great potential to deliver therapeutic molecules to previously inaccessible intracellular targets. However, many CPPs are inefficient and often leave their attached cargo stranded in the cell's endosome. We report a versatile platform for the isolation of peptides delivering a wide range of cargos into the cytoplasm of cells. We used this screening platform to identify multiple "Phylomer" CPPs, derived from bacterial and viral genomes. These peptides are amenable to conventional sequence optimization and engineering approaches for cell targeting and half-life extension. We demonstrate potent, functional delivery of protein, peptide, and nucleic acid analog cargos into cells using Phylomer CPPs. We validate in vivo activity in the cytoplasm, through successful transport of an oligonucleotide therapeutic fused to a Phylomer CPP in a disease model for Duchenne's muscular dystrophy. This report thus establishes a discovery platform for identifying novel, functional CPPs to expand the delivery landscape of druggable intracellular targets for biological therapeutics.

Peptides and analogs such as peptide nucleic acids (PNA) are promising tools and therapeutics, but the cell membrane remains a barrier to intracellular targets. Conjugation to classical cell penetrating peptides (CPPs) such as pTat48-60 (tat) and pAntp43-68 (penetratin) facilitates delivery; however, efficiencies are low. Lack of explicit design principles hinders rational improvement. Here, we use synthetic molecular evolution (SME) to identify gain-of-function CPPs with dramatically improved ability to deliver cargoes to cells at low concentration. A CPP library containing 8192 tat/penetratin hybrid peptides coupled to an 18-residue PNA is screened using the HeLa pTRE-LucIVS2 splice correction reporter system. The daughter CPPs identified are one to two orders of magnitude more efficient than the parent sequences at delivery of PNA, and also deliver a dye cargo and an anionic peptide cargo. The significant increase in performance following a single iteration of SME demonstrates the power of this approach to peptide sequence optimization.

The specificity of tyrosine kinases is attributed predominantly to localization effects dictated by non-catalytic domains. We developed a method to profile the specificities of tyrosine kinases by combining bacterial surface-display of peptide libraries with next-generation sequencing. Using this, we showed that the tyrosine kinase ZAP-70, which is critical for T cell signaling, discriminates substrates through an electrostatic selection mechanism encoded within its catalytic domain (Shah et al., 2016). Here, we expand this high-throughput platform to analyze the intrinsic specificity of any tyrosine kinase domain against thousands of peptides derived from human tyrosine phosphorylation sites. Using this approach, we find a difference in the electrostatic recognition of substrates between the closely related Src-family kinases Lck and c-Src. This divergence likely reflects the specialization of Lck to act in concert with ZAP-70 in T cell signaling. These results point to the importance of direct recognition at the kinase active site in fine-tuning specificity.

Enzymes that modify the proteome, referred to as post-translational modifying (PTM) enzymes, are central regulators of cellular signaling. Determining the substrate specificity of PTM enzymes is a critical step in unraveling their biological functions both in normal physiological processes and in disease states. Advances in peptide chemistry over the last century have enabled the rapid generation of peptide libraries for querying substrate recognition by PTM enzymes. In this article, we highlight various peptide-based approaches for analysis of PTM enzyme substrate specificity. We focus on the application of these technologies to proteases and also discuss specific examples in which they have been used to uncover the substrate specificity of other types of PTM enzymes, such as kinases. In particular, we highlight our multiplex substrate profiling by mass spectrometry (MSP-MS) assay, which uses a rationally designed, physicochemically diverse library of tetradecapeptides. We show how this method has been applied to PTM enzymes to uncover biological function, and guide substrate and inhibitor design. We also briefly discuss how this technique can be combined with other methods to gain a systems-level understanding of PTM enzyme regulation and function.