Peptide Binding Properties Research Articles

Mechanically rigid metallopeptide nanostructures achieved by highly efficient folding

AbstractNatural proteins must fold into complex three-dimensional structures to achieve excellent mechanical properties vital for biological functions, but this has proven to be exceptionally difficult to control in synthetic systems. As such, the long-standing issue of low mechanical rigidity and stability induced by misfolding constrains the physical and chemical properties of self-assembling peptide materials. Here we introduce a mixed-chirality strategy that enhances folding efficiency in topologically interlocked metallopeptide nanostructures. The orderly entanglement of heterochiral peptide-derived linkers can fold into a compact three-dimensional catenane. These folding-mediated secondary structural changes not only generate biomimetic binding pockets derived from individual peptide strands but also result in strong chiral amplification by the tight interlocking manner. Notably, this strategic ‘chirality mutation’ alters their arrangement into tertiary structures and is pivotal in achieving exceptional mechanical rigidity observed in the metallopeptide crystals, which exhibit a Young’s modulus of 157.6 GPa, approximately tenfold higher than the most rigid proteinaceous materials in nature. This unusual nature is reflected in enhanced peptide-binding properties and heightened antimicrobial activities relative to its unfolded counterpart.

The impact of micropolymorphism in Anpl-UAA on structural stability and peptide presentation

Micropolymorphism significantly shapes the peptide-binding characteristics of major histocompatibility complex class I (MHC-I) molecules, affecting the host's resistance to pathogens, which is particularly pronounced in avian species displaying the “minimal essential MHC” expression pattern. In this study, we compared two duck MHC-I alleles, Anpl-UAA*77 and Anpl-UAA*78, that exhibit markedly different peptide binding properties despite their high sequence homology. Through mutagenesis experiments and crystallographic analysis of complexes with the influenza virus-derived peptide AEAIIVAMV (AEV9), we identified a critical role for the residue at position 62 in regulating hydrogen-bonding interactions between the peptide backbone and the peptide-binding groove. This modulation affects the characteristics of the B pocket and the stability of the loop region between the 310 helix and the α1 helix, leading to significant changes in the structure and stability of the peptide-MHC-I complex (pMHC-I). Moreover, the proportion of different residues at position 62 among Anpl-UAAs may reflect the correlation between pAnpl-UAA stability and duck body temperature. This research not only advances our understanding of the Anpl-UAA structure but also deepens our insight into the impact of MHC-I micropolymorphism on peptide binding.

Strategies for converting turn-motif and cyclic peptides to small molecules for targeting protein-protein interactions.

The development of small molecules that interact with protein-protein interactions is an ongoing challenge. Peptides offer a starting point in the drug discovery process for targeting protein-interactions due to their larger, more flexible structure and the structurally diverse properties that allow for a greater interaction with the protein. The techniques for rapidly identifying potent cyclic peptides and turn-motif peptides are highly effective, but this potential has not yet transferred to approved drug candidates. By applying the properties of the peptide-protein interaction the development of small molecules for drug discovery has the potential to be more efficient. In this review, we discuss the methods that allow for the unique binding properties of peptides to proteins, and the methods deployed to transfer these qualities to potent small molecules.

SARS-CoV-2 Binding and Neutralization Properties of Peptides Derived from N-Terminus of Human ACE2.

The binding properties of synthetic and recombinant peptides derived from N-terminal part of ACE2, the main receptor for SARS-CoV-2, were evaluated. Additionally, the ability of these peptides to prevent virus entry in vitro was addressed using both pseudovirus particles decorated with the S protein, as well as through infection of Vero cells with live SARS-CoV-2 virus. Surprisingly, in spite of effective binding to S protein, all linear peptides of various lengths failed to neutralize the viral infection in vitro. However, the P1st peptide that was chemically "stapled" in order to stabilize its alpha-helical structure was able to interfere with virus entry into ACE2-expressing cells. Interestingly, this peptide also neutralized pseudovirus particles decorated with S protein derived from the Omicron BA.1 virus, in spite of variations in key amino acid residues contacting ACE2.

Machine Learning‐Assisted Clustering of Nanoparticle‐Binding Peptides and Prediction of Their Properties

AbstractBioinspired and biomimetic nanostructures have attracted tremendous interest for theranostic and nanomedicine applications. Among the strategies employed to synthesize these nanostructures, surface functionalization and biomineralization of nanomaterials using peptides stand out due to the wide availability of peptides and their variations as well as the ease of modification process. Effective peptide‐based modification of nanomaterials relies on preferential and strong binding between peptides and target nanomaterials. Therefore, the discovery and design of specific peptides with high binding affinity to nanomaterials are essential. Unfortunately, conventional peptide screening methods suffer from shortcomings which render peptide discovery time‐consuming, expensive, and cumbersome. Herein, leveraging unsupervised and supervised machine learning, a framework to accelerate peptide analysis is presented. Specifically, more than 1700 nanoparticle‐binding peptides are classified into peptide clusters to identify important peptide features to realize higher‐affinity binding. In addition, the binding and biomineralization properties of peptides are predicted with high classification accuracy, precision, and recall. This work then proposes the use of unsupervised k‐means clustering and supervised k‐nearest neighbors algorithms for grouping peptides and predicting their properties, respectively. It is anticipated that the framework originated from this study will further facilitate the rational selection and design of peptides for engineering functional bioinspired and biomimetic nanostructures.

In silico Immunogenicity Assessment for Sequences Containing Unnatural Amino Acids: A Method Using Existing in silico Algorithm Infrastructure and a Vision for Future Enhancements.

The in silico prediction of T cell epitopes within any peptide or biologic drug candidate serves as an important first step for assessing immunogenicity. T cell epitopes bind human leukocyte antigen (HLA) by a well-characterized interaction of amino acid side chains and pockets in the HLA molecule binding groove. Immunoinformatics tools, such as the EpiMatrix algorithm, have been developed to screen natural amino acid sequences for peptides that will bind HLA. In addition to commonly occurring in synthetic peptide impurities, unnatural amino acids (UAA) are also often incorporated into novel peptide therapeutics to improve properties of the drug product. To date, the HLA binding properties of peptides containing UAA are not accurately estimated by most algorithms. Both scenarios warrant the need for enhanced predictive tools. The authors developed an in silico method for modeling the impact of a given UAA on a peptide's likelihood of binding to HLA and, by extension, its immunogenic potential. In silico assessment of immunogenic potential allows for risk-based selection of best candidate peptides in further confirmatory in vitro, ex vivo and in vivo assays, thereby reducing the overall cost of immunogenicity evaluation. Examples demonstrating in silico immunogenicity prediction for product impurities that are commonly found in formulations of the generic peptides teriparatide and semaglutide are provided. Next, this article discusses how HLA binding studies can be used to estimate the binding potentials of commonly encountered UAA and "correct" in silico estimates of binding based on their naturally occurring counterparts. As demonstrated here, these in vitro binding studies are usually performed with known ligands which have been modified to contain UAA in HLA anchor positions. An example using D-amino acids in relative binding position 1 (P1) of the PADRE peptide is presented. As more HLA binding data become available, new predictive models allowing for the direct estimation of HLA binding for peptides containing UAA can be established.

Characterization of the novel HLA-A*24:191 allele and analysis of its MHC molecular modeling structure

To characterize a novel HLA allele, A*24:191, its DNA sequence, MHC modeling structure, and the possible influence of the amino-acid residue variations on the molecule. The HLA sequence was determined by Luminex PCR-SSO and PCR-SBT. Its MHC molecular structure and the possible effects of the amino-acid residue variations were modeled and analyzed with Phyre2, RCSB PDB and HistoCheck software. The PCR-SBT revealed the novel A*24:191 differs from A*24:02 in exon 2 at position 256, 265, 270 with G>C, G>C, A>T. The MHC molecular structure prediction showed that, compared with A*24:02, the 62nd residue of A*24:191 changed from the acidic E to a neutral Q, both with the side chain extending outside the α helix pointing forward the groove, (Risler's score, R=2), the 65th changed from the smaller neutral G extending inside the helix to a basic R with a long-chain extending upward outside the helix (R=52), and the 66th changed from the basic K to a neutral N both with a long side chain extending inside the groove (R=31). The above residues are located on the α helix of the α 1 domain which constituting the side wall of the peptide-binding groove. The DSS Score=3.85. From the surface image of the molecule, it can be clearly seen that the variations of the properties, sizes and configurations of the residues caused significant changes in the shape of the surface structure of the α helix. It suggested that the residue variations are likely to change the peptide binding properties as well as the TCR and antibody binding characteristics of the molecule.

Major histocompatibility IIβ diversity and peptide-binding groove properties associated with red sea bream iridovirus resistance

Major histocompatibility complex (MHC) II genes are key factors in presenting antigens derived from extracellular pathogens to CD4+ T cells. These genes are known to be associated with disease resistance in livestock, including cultured fish species. Genome-wide linkage analysis of RSIV-resistant red sea bream has revealed that MHC IIβ is linked to the RSIV-resistant trait and was suggested as a probable candidate gene responsible for the resistant trait. In the present study, diversity of the MHC IIβ gene in wild and farmed red sea bream populations was evaluated by analysis of an intronic minisatellite locus, PmaMHC2b. Haplotypes of the βI domain of MHC IIβ were identified by cloning, and linkage of minisatellite polymorphisms with haplotype was confirmed in farmed populations. Large numbers of alleles were observed in the wild population (30), while the domesticated populations showed significantly lower values (13). Thirteen haplotypes of MHC IIβ were observed; most haplotypes possessed the unique PmaMHC2b allele, but some were present in more than one PmaMHC2b allele. Each haplotype possessed a distinct amino acid sequence with no synonymous mutations. Among 16 amino acid positions involved in peptide-binding grooves, four were monomorphic and 12 polymorphic. Several positions differed in the RSIV-resistant and RSIV-susceptible phenotypes: five in hydrophilic/hydrophobic character and five in polarity. These results provide insight applicable to broodstock management and contribute to understanding RSIV resistance.

A novel RHCE*cE allele identified in a Chinese individual, encodes weakened expression of c and E antigens

A novel RHCE*cE allele identified in a Chinese individual, encodes weakened expression of c and E antigens

Individual HLA-A, -B, -C, and -DRB1 Genotypes Are No Major Factors Which Determine COVID-19 Severity.

HLA molecules are key restrictive elements to present intracellular antigens at the crossroads of an effective T-cell response against SARS-CoV-2. To determine the impact of the HLA genotype on the severity of SARS-CoV-2 courses, we investigated data from 6,919 infected individuals. HLA-A, -B, and -DRB1 allotypes grouped into HLA supertypes by functional or predicted structural similarities of the peptide-binding grooves did not predict COVID-19 severity. Further, we did not observe a heterozygote advantage or a benefit from HLA diplotypes with more divergent physicochemical peptide-binding properties. Finally, numbers of in silico predicted viral T-cell epitopes did not correlate with the severity of SARS-CoV-2 infections. These findings suggest that the HLA genotype is no major factor determining COVID-19 severity. Moreover, our data suggest that the spike glycoprotein alone may allow for abundant T-cell epitopes to mount robust T-cell responses not limited by the HLA genotype.

Unique Pathogen Peptidomes Facilitate Pathogen-Specific Selection and Specialization of MHC Alleles.

A key component of pathogen-specific adaptive immunity in vertebrates is the presentation of pathogen-derived antigenic peptides by major histocompatibility complex (MHC) molecules. The excessive polymorphism observed at MHC genes is widely presumed to result from the need to recognize diverse pathogens, a process called pathogen-driven balancing selection. This process assumes that pathogens differ in their peptidomes—the pool of short peptides derived from the pathogen’s proteome—so that different pathogens select for different MHC variants with distinct peptide-binding properties. Here, we tested this assumption in a comprehensive data set of 51.9 Mio peptides, derived from the peptidomes of 36 representative human pathogens. Strikingly, we found that 39.7% of the 630 pairwise comparisons among pathogens yielded not a single shared peptide and only 1.8% of pathogen pairs shared more than 1% of their peptides. Indeed, 98.8% of all peptides were unique to a single pathogen species. Using computational binding prediction to characterize the binding specificities of 321 common human MHC class-I variants, we investigated quantitative differences among MHC variants with regard to binding peptides from distinct pathogens. Our analysis showed signatures of specialization toward specific pathogens especially by MHC variants with narrow peptide-binding repertoires. This supports the hypothesis that such fastidious MHC variants might be maintained in the population because they provide an advantage against particular pathogens. Overall, our results establish a key selection factor for the excessive allelic diversity at MHC genes observed in natural populations and illuminate the evolution of variable peptide-binding repertoires among MHC variants.

Novel HLA-DRB1 alleles contribute risk for disease susceptibility in primary biliary cholangitis.

Primary biliary cholangitis (PBC) is a complex disease with high heritability. We investigated the association between human leukocyte antigen (HLA)-DRB1 alleles and PBC in families and sporadic cases to evaluate the genetic components of the disease. We performed whole exome sequencing in three PBC families. We genotyped HLA-DRB1 and calculated the association between HLA-DRB1 alleles and the encoding amino acid sequences with the clinical features. Ten variants harboured the HLA-DRB1 gene associated with PBC. DRB1×07:01, 14:01 and 14:05 were highly increased in PBC. Ten coding region polymorphisms were associated with PBC that encode the amino acid variants of HLA-DR β54, β59 and β66 located in the peptide-binding site of the MHC molecule. Glutamine at position 54 was confirmed as a risk amino acid, verifying the results of familial aggregation analysis of PBC families. Familial aggregation analysis indicated that HLA-DRB1 is a candidate gene for the risk of disease course. Considering that amino acid variations are critical to peptide-binding properties, they underlie the major component of MHC association with PBC.

Screening of Fv Antibodies with Specific Binding Activities to Monosodium Urate and Calcium Pyrophosphate Dihydrate Crystals for the Diagnosis of Gout and Pseudogout.

To date, medical diagnosis of gout and pseudogout has been performed by observing the crystals in the joint fluid of patients under a polarized microscope. Conventional diagnostic methods using a polarized microscope have disadvantages, such as time-consuming analysis, a high false negative rate, and difficulty in distinguishing gout with monosodium urate (MSU) crystals and pseudogout with calcium pyrophosphate dihydrate (CPPD) crystals in synovial fluids. In this study, a chromogenic assay for the diagnosis of gout and pseudogout, without the requirement of a polarized microscope and trained experts, was proposed using Fv antibodies with specific binding activities to MSU and CPPD crystals. The IgG VH chain Fv library with randomized complementarity-determining region 3 (CDR3) region was expressed on the outer membrane of Escherichia coli using autodisplay technology. The target Fv antibodies with binding activity to MSU and CPPD crystals were screened from the autodisplayed Fv library on the E. coli outer membrane, and five clones were selected. On the basis of the binding properties of the screened Fv antibodies, peptides with the selected clone of amino acid sequences of the CDR3 region (15 residues) were chemically synthesized. The binding properties of the synthetic peptides with amino acid sequences of CDR3 regions from the selected clones were analyzed using fluorescence imaging and flow cytometry, and the affinity constants (Kd) of each peptide for binding to MSU and CPPD crystals were calculated by fitting based on the isotherm model. A chromogenic assay configuration for gout and pseudogout was developed using synthetic peptides. In this chromogenic assay, synthetic peptides labeled with biotin and streptavidin-horseradish peroxidase (HRP) complex were used, and crystal detection was possible using a chromogenic reaction between HRP and a chromogenic substrate (TMB). Finally, gout and pseudogout were diagnosed by detecting MSU and CPPD crystals in the synovial fluid in the concentration range of 0-300 μg/mL.

Lasso-grafting of macrocyclic peptide pharmacophores yields multi-functional proteins

Protein engineering has great potential for devising multifunctional recombinant proteins to serve as next-generation protein therapeutics, but it often requires drastic modifications of the parental protein scaffolds e.g., additional domains at the N/C-terminus or replacement of a domain by another. A discovery platform system, called RaPID (Random non-standard Peptides Integrated Discovery) system, has enabled rapid discovery of small de novo macrocyclic peptides that bind a target protein with high binding specificity and affinity. Capitalizing on the optimized binding properties of the RaPID-derived peptides, here we show that RaPID-derived pharmacophore sequences can be readily implanted into surface-exposed loops on recombinant proteins and maintain both the parental peptide binding function(s) and the host protein function. We refer to this protein engineering method as lasso-grafting and demonstrate that it can endow specific binding capacity toward various receptors into a diverse set of scaffolds that includes IgG, serum albumin, and even capsid proteins of adeno-associated virus, enabling us to rapidly formulate and produce bi-, tri-, and even tetra-specific binder molecules.

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

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

MHC class I associations beyond HLA-B27: the peptide binding hypothesis of psoriatic arthritis and its implications for disease pathogenesis.

To provide an overview of the heterogeneous human leucocyte antigen (HLA) associations of psoriatic arthritis, their relationship to particular clinical features of the disease, and how a hypothesis of binding specific peptides could provide a unifying basis for this heterogeneity. There have been substantive advances in understanding the role of HLA molecules in binding self-peptides that select our repertoire of T cells, the specific peptide-binding properties of these HLA allotypes, and their crystallographic structure. These advances provide a means to envision the significance of the heterogeneous psoriatic arthritis HLA associations. The clinical relevance of these allotypes if heightened by emerging knowledge of their relationship to particular clinical features of the disease that serve as subphenotypes. We propose a peptide binding hypothesis of psoriatic arthritis based on a shared pattern of negative charge in the 'B' pocket of the HLA-B and HLA-C molecules encoded by the susceptibility allotypes. This hypothesis suggests that peptides characterized by the presence of arginine at position 2 or 3 are bound to the susceptibility allotypes and drive the T-cell clones selected on them to attack molecules containing these peptides located in sites of psoriatic arthritis inflammation.

Molecular mechanism for the recognition of sequence-divergent CIF peptides by the plant receptor kinases GSO1/SGN3 and GSO2

Plants use leucine-rich repeat receptor kinases (LRR-RKs) to sense sequence diverse peptide hormones at the cell surface. A 3.0-Å crystal structure of the LRR-RK GSO1/SGN3 regulating Casparian strip formation in the endodermis reveals a large spiral-shaped ectodomain. The domain provides a binding platform for 21 amino acid CIF peptide ligands, which are tyrosine sulfated by the tyrosylprotein sulfotransferase TPST/SGN2. GSO1/SGN3 harbors a binding pocket for sulfotyrosine and makes extended backbone interactions with CIF2. Quantitative biochemical comparisons reveal that GSO1/SGN3-CIF2 represents one of the strongest receptor-ligand pairs known in plants. Multiple missense mutations are required to block CIF2 binding in vitro and GSO1/SGN3 function in vivo. Using structure-guided sequence analysis we uncover previously uncharacterized CIF peptides conserved among higher plants. Quantitative binding assays with known and novel CIFs suggest that the homologous LRR-RKs GSO1/SGN3 and GSO2 have evolved unique peptide binding properties to control different developmental processes. A quantitative biochemical interaction screen, a CIF peptide antagonist and genetic analyses together implicate SERK proteins as essential coreceptor kinases required for GSO1/SGN3 and GSO2 receptor activation. Our work provides a mechanistic framework for the recognition of sequence-divergent peptide hormones in plants.

Fine mapping of the MHC region identifies major independent variants associated with Han Chinese primary biliary cholangitis

The genetic association of primary biliary cholangitis with major histocompatibility complex (MHC) has been widely confirmed among different ethnicities. To map specific MHC region variants associated with PBC in a Han Chinese cohort, we imputed HLA antigens and amino acids (AA) in 1126 PBC cases and 1770 healthy control subjects using a Han-MHC reference database. We demonstrate that HLA-DRB1 and/or HLA-DQB1 contributed the strongest signals, and that HLA-DPB1 was a separate independent locus. Regression analyses with classical HLA alleles indicate that HLA-DQB1*03:01 or HLA-DQβ1-Pro55, HLA-DPB1*17:01 or HLA-DPβ1-Asp84 and HLA-DRB1*08:03 could largely explain MHC association with PBC. Forward stepwise regression analyses with HLA amino acid variants localize the major signals to HLA-DRβ1-Ala74, HLA-DQβ1-Pro55 and HLA-DPβ1-Asp84. Electrostatic potential calculations implicated AA variations at HLA-DQβ1 position 55 and HLA-DPβ1 position 84 as critical to peptide binding properties. Furthermore, although several critical Han Chinese AA variants differed from those shown in European populations, the predicted effects on antigen binding are likely to be very similar or identical and underlie the major component of MHC association with PBC.

Cation and peptide binding properties of CML7, a calmodulin-like protein from Arabidopsis thaliana

Plants contain a large family of so-called calmodulin-like proteins (CMLs) which differ from canonical calmodulin in that they show greater variability in sequence, length, and number of EF-hand domains. The presence of this extended CML family has raised questions regarding the role of these proteins: are they functionally redundant or do they play specific functions in physiological plant processes? To answer these questions, comprehensive biochemical and structural information on CML proteins is fundamental. Among the 50 CMLs from Arabidopsis thaliana, herein we described the ability of CML7 to bind metal ions focusing on the Ca2+ and Mg2+ sensing properties, as well as on metal-induced conformational changes. Circular dichroism and nuclear magnetic resonance (NMR) studies indicated that both Ca2+ and Mg2+ stabilize CML7, as reflected in conformational rearrangements in secondary and tertiary structure and in increases in thermal stability of the protein. However, the conformational changes that binding induces differ between the two metal ions, and only Ca2+ binding controls a structural transition that leads to hydrophobic exposure, as suggested by 8-anilino-1-naphthalenesulfonic acid fluorescence. Isothermal titration calorimetry data coupled with NMR experiments revealed the presence of two high affinity Ca2+-binding sites in the C-lobe of CML7 and two weaker sites in the N-lobe. The paired nature of these CML7 EF-hands enables them to bind Ca2+ with positive cooperativity within each globular domain. Our results clearly place CML7 in the category of Ca2+ sensors. Along with this, the protein can bind to a model target peptide (melittin) in a Ca2+-dependent manner.

Comprehensive Profiling of HIV Antibody Evolution

SUMMARYThis study evaluates HIV antibody responses and their evolution during the course of HIV infection. A phage display system is used to characterize antibody binding to >3,300 HIV peptides in 57 adults with early- to late-stage infection. We find that the number of unique epitopes targeted (“antibody breadth”) increases early in infection and then stabilizes or declines. A decline in antibody breadth 9 months to 2 years after infection is associated with subsequent antiretroviral treatment (ART) initiation, and a faster decline in antibody breadth is associated with a shorter time to ART initiation. We identify 266 peptides with increasing antibody reactivity over time and 43 peptides with decreasing reactivity over time. These data are used to design a prototype four-peptide “serosignature” to predict duration of HIV infection. We also demonstrate that epitope engineering can be used to optimize peptide binding properties for applications such as cross-sectional HIV incidence estimation.