Please use this identifier to cite or link to this item: 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
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