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https://repositorio.inpa.gov.br/handle/1/16523
Title: | Molecular dynamics and binding energy analysis of Vatairea guianensis lectin: a new tool for cancer studies |
Authors: | Cavada, B. S. Osterne, Vinicius José Silva Pinto-Junior, Vanir Reis Souza, Luis Augusto Gomes Lóssio, Cláudia Figueiredo Silva, Mayara Torquato Lima da Correia-Neto, Corneville Oliveira, Messias Vital Correia, Jorge Luís Almeida Neco, Antonio Hadson Bastos Domingos, Jorge Luiz Coelho Ferreira, Wandemberg Paiva Farias, Gil Aquino Nascimento, K. S. |
Keywords: | Carbohydrate Lectin Ligand N Acetylgalactosamine Tn Antigen Binding Affinity Cancer Research Energy Extracellular Matrix Legume Molecular Dynamics Molecular Interaction Molecular Mechanics Molecular Recognition Nonhuman Seed Plant Priority Journal Surface Area Vatairea Guianensis |
Issue Date: | 2020 |
metadata.dc.publisher.journal: | Journal of Molecular Modeling |
metadata.dc.relation.ispartof: | Volume 26, Número 2 |
Abstract: | The Tn antigen is an epitope containing N-acetyl-D-galactosamine present in the extracellular matrix of some carcinoma cells in humans, and it is often used as a biomarker. Lectins are proteins capable of binding to carbohydrates and can be used as a molecular tool to recognize antigens and to differentiate cancer cells from normal cells. In this context, the present work aimed to characterize the interaction of Vatairea guianensis seed lectin with N-acetyl-D-galactosamine and the Tn antigen by molecular dynamics and molecular mechanics/Poisson–Boltzmann solvent-accessible surface area analysis. This study revealed new interacting residues not previously identified in static analysis of the three-dimensional structures of Vatairea lectins, as well as the configuration taken by the carbohydrate recognition domain, as it interacts with each ligand. During the molecular dynamics simulations, Vatairea guianensis lectin was able to bind stably to Tn antigen, which, as seen previously for other lectins, enables its use in cancer research, diagnosis, and therapy. This work further demonstrates the efficiency of bioinformatics in lectinology. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature. |
metadata.dc.identifier.doi: | 10.1007/s00894-019-4281-3 |
Appears in Collections: | Artigos |
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