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

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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.

Immunodominant antibody responses directed to SARS-CoV-2 hotspot mutation sites and risk of immune escape

Oliveira, Jamille Ramos; Ruiz, Cesar Manuel Remuzgo; Machado, Rafael Rahal Guaragna; Magawa, Jhosiene Yukari; Daher, Isabela Pazotti; Urbanski, Alysson Henrique; Schmitz, Gabriela Justamante Händel; Arcuri, Helen Andrade; Ferreira, Marcelo Alves; Sasahara, Greyce Luri; de Medeiros, Giuliana Xavier; Júnior, Roberto Carlos Vieira Silva; Durigon, Edison Luiz; Boscardin, Silvia Beatriz; Rosa, Daniela Santoro; Schechtman, Deborah; Nakaya, Helder I.; Cunha-Neto, Edecio; Gadermaier, Gabriele; Kalil, Jorge; Coelho, Verônica; Santos, Keity Souza
Front. Immunol..
Jan 2023
10.3389/fimmu.2022.1010105
Introduction Considering the likely need for the development of novel effective vaccines adapted to emerging relevant CoV-2 variants, the increasing knowledge of epitope recognition profile among convalescents and afterwards vaccinated with identification of immunodominant regions may provide important information. Methods We used an RBD peptide microarray to identify IgG and IgA binding regions in serum of 71 COVID-19 convalescents and 18 vaccinated individuals. Results We found a set of immunodominant RBD antibody epitopes, each recognized by more than 30% of the tested cohort, that differ among the two different groups and are within conserved regions among betacoronavirus. Of those, only one peptide, P44 (S415-429), recognized by 68% of convalescents, presented IgG and IgA antibody reactivity that positively correlated with nAb titers, suggesting that this is a relevant RBD region and a potential target of IgG/IgA neutralizing activity. Discussion This peptide is localized within the area of contact with ACE-2 and harbors the mutation hotspot site K417 present in gamma (K417T), beta (K417N), and omicron (K417N) variants of concern. The epitope profile of vaccinated individuals differed from convalescents, with a more diverse repertoire of immunodominant peptides, recognized by more than 30% of the cohort. Noteworthy, immunodominant regions of recognition by vaccinated coincide with mutation sites at Omicron BA.1, an important variant emerging after massive vaccination. Together, our data show that immune pressure induced by dominant antibody responses may favor hotspot mutation sites and the selection of variants capable of evading humoral response.

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