RT Journal Article
T1 Computational Modeling of Environmental Co-exposure on Oil-Derived Hydrocarbon Overload by Using Substrate-Specific Transport Protein (TodX) with Graphene Nanostructures
A1 Oliveira, Patrícia Viera de
A1 Goulart, Luiza
A1 Santos, Cláudia Lange dos
A1 Rossato, Jussane
A1 Fagan, Solange Binotto
A1 Zanella, Ivana
A1 Cordeiro, M. Natália D. S.
A1 Ruso Beiras, Juan Manuel
A1 González Durruthy, Michael
K1 Petroleum
K1 TodX protein
K1 Graphene
K1 Molecular docking
K1 DFT-simulation
K1 Nanostructures
AB Background: Bioremediation is a biotechnology field that uses living organisms to remove contaminants from soil and water; therefore, they could be used to treat oil spills from the environment.Methods: Herein, we present a new mechanistic approach combining Molecular Docking Simulation and Density Functional Theory to modeling the bioremediation-based nanointeractions of a heterogeneous mixture of oil-derived hydrocarbons by using pristine and oxidized graphene nanostructures and the substrate-specific transport protein (TodX) from Pseudomonas putida.Results: The theoretical evidences pointing that the binding interactions are mainly based on noncovalent bonds characteristic of physical adsorption mechanism mimicking the “Trojan-horse effect”.Conclusion: These results open new horizons to improve bioremediation strategies in over-saturation conditions against oil-spills and expanding the use of nanotechnologies in the context of environmental modeling health and safety.
PB Bentham Science Publishers
YR 2020
FD 2020-07-21
LK https://hdl.handle.net/10347/43918
UL https://hdl.handle.net/10347/43918
LA eng
NO Herein, we present a new mechanistic approach combining Molecular Docking Simulation and Density Functional Theory to modeling the bioremediation-based nanointeractions of a heterogeneous mixture of oil-derived hydrocarbons by using pristine and oxidized graphene nanostructures and the substrate-specific transport protein (TodX) from Pseudomonas putida.The published manuscript is available at: https://doi.org/10.2174/1568026620666200820145412
NO This work received financial support from Fundação para a Ciência e a Tecnologia (FCT/MEC). The work of M. G.-D. and M. N. D. S. Cordeiro was supported by UID/QUI/50006/2019 with funding from FCT/MCTES through national funds. J.M.R acknowledge Xunta de Galicia (ED431B 2017/21, ED41E2018/08). Also, the authors acknowledge the financial support from the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES), CNPq, and the Centro Nacional de Processamento de Alto Desempenho (CENAPAD) for the computational time.
DS Minerva
RD 27 abr 2026