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Discover how PEPperPRINT Peptide Microarray products have been used in different fields of research.

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Identification of Zika Virus NS1-Derived Peptides with Potential Applications in Serological Tests

Prudencio, Carlos Roberto; Gomes da Costa, Vivaldo; Rocha, Leticia Barboza; Costa, Hernan Hermes Monteiro; Orts, Diego José Belato; da Silva Santos, Felipe Rocha; Rahal, Paula; Lino, Nikolas Alexander Borsato; da Conceição, Pâmela Jóyce Previdelli; Bittar, Cintia; Machado, Rafael Rahal Guaragna; Durigon, Edison Luiz; Araujo, João Pessoa; Polatto, Juliana Moutinho; da Silva, Miriam Aparecida; de Oliveira, Joyce Araújo; Mitsunari, Thais; Pereira, Lennon Ramos; Andreata-Santos, Robert; de Souza Ferreira, Luís Carlos; Luz, Daniela; Piazza, Roxane Maria Fontes
Viruses.
Feb 2023
10.3390/v15030654
Zika virus (ZIKV), a mosquito-borne pathogen, is an emerging arbovirus associated with sporadic symptomatic cases of great medical concern, particularly among pregnant women and newborns affected with neurological disorders. Serological diagnosis of ZIKV infection is still an unmet challenge due to the co-circulation of the dengue virus, which shares extensive sequence conservation of structural proteins leading to the generation of cross-reactive antibodies. In this study, we aimed to obtain tools for the development of improved serological tests for the detection of ZIKV infection. Polyclonal sera (pAb) and a monoclonal antibody (mAb 2F2) against a recombinant form of the ZIKV nonstructural protein 1 (NS1) allowed the identification of linear peptide epitopes of the NS1 protein. Based on these findings, six chemically synthesized peptides were tested both in dot blot and ELISA assays using convalescent sera collected from ZIKV-infected patients. Two of these peptides specifically detected the presence of ZIKV antibodies and proved to be candidates for the detection of ZIKV-infected subjects. The availability of these tools opens perspectives for the development of NS1-based serological tests with enhanced sensitivity regarding other flaviviruses.

Exploring the Immunodominant Epitopes of SARS-CoV-2 Nucleocapsid Protein as Exposure Biomarker

Vashisht, Kapil; Goyal, Bharti; Pasupureddy, Rahul; Na, Byoung-Kuk; Shin, Ho-Joon; Sahu, Dibakar; De, Sajal; Chakraborti, Soumyananda; Pandey, Kailash C
Feb 2023
10.7759/cureus.34827

Funneling modulatory peptide design with generative models: Discovery and characterization of disruptors of calcineurin protein-protein interactions

Tubiana, Jérôme; Adriana-Lifshits, Lucia; Nissan, Michael; Gabay, Matan; Sher, Inbal; Sova, Marina; Wolfson, Haim J.; Gal, Maayan
PLoS Comput Biol.
Feb 2023
10.1371/journal.pcbi.1010874
Design of peptide binders is an attractive strategy for targeting “undruggable” protein-protein interfaces. Current design protocols rely on the extraction of an initial sequence from one known protein interactor of the target protein, followed by in-silico or in-vitro mutagenesis-based optimization of its binding affinity. Wet lab protocols can explore only a minor portion of the vast sequence space and cannot efficiently screen for other desirable properties such as high specificity and low toxicity, while in-silico design requires intensive computational resources and often relies on simplified binding models. Yet, for a multivalent protein target, dozens to hundreds of natural protein partners already exist in the cellular environment. Here, we describe a peptide design protocol that harnesses this diversity via a machine learning generative model. After identifying putative natural binding fragments by literature and homology search, a compositional Restricted Boltzmann Machine is trained and sampled to yield hundreds of diverse candidate peptides. The latter are further filtered via flexible molecular docking and an in-vitro microchip-based binding assay. We validate and test our protocol on calcineurin, a calcium-dependent protein phosphatase involved in various cellular pathways in health and disease. In a single screening round, we identified multiple 16-length peptides with up to six mutations from their closest natural sequence that successfully interfere with the binding of calcineurin to its substrates. In summary, integrating protein interaction and sequence databases, generative modeling, molecular docking and interaction assays enables the discovery of novel protein-protein interaction modulators.

Reactivity Graph Yields Interpretable IgM Repertoire Signatures as Potential Tumor Biomarkers

Ferdinandov, Dilyan; Kostov, Viktor; Hadzhieva, Maya; Shivarov, Velizar; Petrov, Peter; Bussarsky, Assen; Pashov, Anastas Dimitrov
IJMS.
Jan 2023
10.3390/ijms24032597
Combining adaptive and innate immunity induction modes, the repertoire of immunoglobulin M (IgM) can reflect changes in the internal environment including malignancies. Previously, it was shown that a mimotope library reflecting the public IgM repertoire of healthy donors (IgM IgOme) can be mined for efficient probes of tumor biomarker antibody reactivities. To better explore the interpretability of this approach for IgM, solid tumor-related profiles of IgM reactivities to linear epitopes of actual tumor antigens and viral epitopes were studied. The probes were designed as oriented planar microarrays of 4526 peptide sequences (as overlapping 15-mers) derived from 24 tumor-associated antigens and 209 cancer-related B cell epitopes from 30 viral antigens. The IgM reactivity in sera from 21 patients with glioblastoma multiforme, brain metastases of other tumors, and non-tumor-bearing neurosurgery patients was thus probed in a proof-of-principle study. A graph representation of the binding data was developed, which mapped the cross-reactivity of the mixture of IgM (poly)specificities, delineating different antibody footprints in the features of the graph—neighborhoods and cliques. The reactivity graph mapped the major features of the IgM repertoire such as the magnitude of the reactivity (titer) and major cross-reactivities, which correlated with blood group reactivity, non-self recognition, and even idiotypic specificities. A correlation between an aspect of this image of the IgM IgOme, namely, small cliques reflecting rare self-reactivities and the capacity of subsets of the epitopes to separate the diagnostic groups studied was found. In this way, the graph representation helped the feature selection in its filtering step and provided reduced feature sets, which, after recursive feature elimination, produced a classifier containing 51 peptide reactivities separating the three diagnostic groups with an unexpected efficiency. Thus, IgM IgOme approaches to repertoire studies is greatly augmented when self/viral antigens are used and the data are represented as a reactivity graph. This approach is most general, and if it is applicable to tumors in immunologically privileged sites, it can be applied to any solid tumors, for instance, breast or lung cancer.

Humoral Immune Response Profile of COVID-19 Reveals Severity and Variant-Specific Epitopes: Lessons from SARS-CoV-2 Peptide Microarray

Acharjee, Arup; Ray, Arka; Salkar, Akanksha; Bihani, Surbhi; Tuckley, Chaitanya; Shastri, Jayanthi; Agarwal, Sachee; Duttagupta, Siddhartha; Srivastava, Sanjeeva
Viruses.
Jan 2023
10.3390/v15010248
The amaranthine scale of the COVID-19 pandemic and unpredictable disease severity is of grave concern. Serological diagnostic aids are an excellent choice for clinicians for rapid and easy prognosis of the disease. To this end, we studied the humoral immune response to SARS-CoV-2 infection to map immunogenic regions in the SARS-CoV-2 proteome at amino acid resolution using a high-density SARS-CoV-2 proteome peptide microarray. The microarray has 4932 overlapping peptides printed in duplicates spanning the entire SARS-CoV-2 proteome. We found 204 and 676 immunogenic peptides against IgA and IgG, corresponding to 137 and 412 IgA and IgG epitopes, respectively. Of these, 6 and 307 epitopes could discriminate between disease severity. The emergence of variants has added to the complexity of the disease. Using the mutation panel available, we could detect 5 and 10 immunogenic peptides against IgA and IgG with mutations belonging to SAR-CoV-2 variants. The study revealed severity-based epitopes that could be presented as potential prognostic serological markers. Further, the mutant epitope immunogenicity could indicate the putative use of these markers for diagnosing variants responsible for the infection.

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