Alanine Scanning of the Unstructured Region of Ara h 2 and of a Related Mimotope Reveals Critical Amino Acids for IgE Binding.

SCOPE: The unstructured region of Ara h 2, referred to as epitope 3, contains a repeated motif, DYPSh (h = hydroxyproline) that is important for IgE binding. METHODS AND RESULTS: IgE binding assays to 20mer and shorter peptides of epitope 3, defines a 16mer core sequence containing one copy of the DPYSh motif, DEDSYERDPYShSQDP. This study performs alanine scanning of this and a related 12mer mimotope, LLDPYAhRAWTK. IgE binding, using a pool of 10 sera and with individual sera, is greatly reduced when alanine is substituted for aspartate at position 8 (D8; p < 0.01), tyrosine at position 10 (Y10; p < 0.01), and hydroxyproline at position 12 (h12; p < 0.001). IgE binding to alanine-substituted peptides of a mimotope containing the DPY_h motif confirm the critical importance of Y (p < 0.01) and h (p < 0.01), but not D. Molecular modeling of the core and mimotope suggests an h-dependent conformational basis for the recognition of these sequences by polyclonal IgE. CONCLUSIONS: IgE from pooled sera and individual sera differentially bound amino acids throughout the sequences of Epitope 3 and its mimotope, with Y10 and h12 being most important for all sera. These results are highly significant for designing hypoallergenic forms of Ara h 2.

Design of peptides with high affinity binding to a monoclonal antibody as a basis for immunotherapy.

About half of the US population is sensitized to one or more allergens, as found by a National Health and Nutrition Examination Survey (NHANES). The most common treatment for seasonal allergic responses is the daily use of oral antihistamines, which can control some of the symptoms, but are not effective for nasal congestion, and can be debilitating in many patients. Peptide immunotherapy is a promising new approach to treat allergic airway diseases. The small size of the immunogens cannot lead to an unwanted allergic reaction in sensitized patients, and the production of peptides with sufficient amounts for immunotherapy is time- and cost-effective. However, it is not known what peptides are the most effective for an immunotherapy of allergens. We previously produced a unique monoclonal antibody (mAb) E58, which can inhibit the binding of multiple groups of mAbs and human IgEs from patients affected by the major group 1 allergens of ragweed (Amb a 1) and conifer pollens (Jun a 1, Cup s 1, and Cry j 1). Here, we demonstrated that a combined approach, starting from two linear E58 epitopes of the tree pollen allergen Jun a 1 and the ragweed pollen allergen Amb a 1, and residue modifications suggested by molecular docking calculations and peptide design could identify a large number of high affinity binding peptides. We propose that this combined experimental and computational approach by structural analysis of linear IgE epitopes and peptide design, can lead to potential new candidates for peptide immunotherapy.

Synthetic proteins for COVID-19 diagnostics.

There is an urgent need for inexpensive, rapid and specific antigen-based assays to test for vaccine efficacy and detect infection with SARS-CoV-2 and its variants. We have identified a small, synthetic protein (JS7), representing a region of maximum variability within the receptor binding domain (RBD), which binds antibodies in sera from nine patients with PCR-verified COVID-19 of varying severity. Antibodies binding to either JS7 or the SARS-CoV-2 recombinant RBD, as well as those that disrupt binding between a fragment of the ACE2 receptor and the RBD, are proportional to disease severity and clinical outcome. Binding to JS7 was inhibited by linear peptides from the RBD interface with ACE2. Variants of JS7, such as E484K or N501Y, can be quickly synthesized in pure form in large quantities by automated methods. JS7 and related synthetic antigens can provide a basis for specific diagnostics for SARS-CoV-2 infections.

Validation of a phage display and computational algorithm by mapping a conformational epitope of Bla g 2.

BACKGROUND: Bla g 2, one of the major cockroach allergens, induces a strong IgE response against conformational epitopes, and on reexposure, sensitized individuals often display symptoms of allergic rhinitis and asthma. The aim of the current study was to perform a test of the efficacy of a modified phage display screening, characterization of selected phages and an automated algorithm, EpiSearch, in locating an important conformational epitope. METHODS: The monoclonal antibody 7C11, which partially inhibits the binding of patient IgE antibodies to Bla g 2, was used to screen a random peptide phage library. After 3 rounds of panning, 32 phage clones were isolated and the amino acid sequences of their peptides were determined. The relative affinity and specificity of the binding of these peptides to 7C11 were tested in ELISAs. The amino acid composition of these peptides was then matched with clusters of residues on the surface of the 3-dimensional (3D) structure of Bla g 2, using our EpiSearch algorithm. RESULTS: The amino acid sequences of the peptides on selected phages differed at only one position, occupied by 1 of 2 negatively charged residues. The two 12-mer sequences bound to 7C11 with similar avidity and specificity. There was good concordance between the residues in the 3D clusters identified from our phage display/computational method with the co-crystal structural analysis. CONCLUSION: Conformational epitopes may be mapped through screening of clones from random peptide phage display libraries and EpiSearch.

Statistical analysis of physical-chemical properties and prediction of protein-protein interfaces.

We have developed a fully automated method, InterProSurf, to predict interacting amino acid residues on protein surfaces of monomeric 3D structures. Potential interacting residues are predicted based on solvent accessible surface areas, a new scale for interface propensities, and a cluster algorithm to locate surface exposed areas with high interface propensities. Previous studies have shown the importance of hydrophobic residues and specific charge distribution as characteristics for interfaces. Here we show differences in interface and surface regions of all physical chemical properties of residues as represented by five quantitative descriptors. In the current study a set of 72 protein complexes with known 3D structures were analyzed to obtain interface propensities of residues, and to find differences in the distribution of five quantitative descriptors for amino acid residues. We also investigated spatial pair correlations of solvent accessible residues in interface and surface areas, and compared log-odds ratios for interface and surface areas. A new scoring method to predict potential functional sites on the protein surface was developed and tested for a new dataset of 21 protein complexes, which were not included in the original training dataset. Empirically we found that the algorithm achieves a good balance in the accuracy of precision and sensitivity by selecting the top eight highest scoring clusters as interface regions. The performance of the method is illustrated for a dimeric ATPase of the hyperthermophile, Methanococcus jannaschii, and the capsid protein of Human Hepatitis B virus. An automated version of the method can be accessed from our web server at http://curie.utmb.edu/prosurf.html.

Determining functionally important amino acid residues of the E1 protein of Venezuelan equine encephalitis virus.

A new method for predicting interacting residues in protein complexes, InterProSurf, was applied to the E1 envelope protein of Venezuelan equine encephalitis (VEEV). Monomeric and trimeric models of VEEV-E1 were constructed with our MPACK program, using the crystal structure of the E1 protein of Semliki forest virus as a template. An alignment of the E1 sequences from representative alphavirus sequences was used to determine physical chemical property motifs (likely functional areas) with our PCPMer program. Information on residue variability, propensity to be in protein interfaces, and surface exposure on the model was combined to predict surface clusters likely to interact with other viral or cellular proteins. Mutagenesis of these clusters indicated that the predictions accurately detected areas crucial for virus infection. In addition to the fusion peptide area in domain 2, at least two other surface areas play an important role in virus infection. We propose that these may be sites of interaction between the E1-E1 and E1-E2 subdomains of the envelope proteins that are required to assemble the functional unit. The InterProSurf method is, thus, an important new tool for predicting viral protein interactions. These results can aid in the design of new vaccines against alphaviruses and other viruses.