The Experts below are selected from a list of 1101 Experts worldwide ranked by ideXlab platform
Luiz C. G. Freitas - One of the best experts on this subject based on the ideXlab platform.
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designing an enzyme based nanobiosensor using molecular modeling techniques
Physical Chemistry Chemical Physics, 2011Co-Authors: Eduardo De Faria Franca, Fabio L Leite, Richard A Cunha, Osvaldo N. Oliveira, Luiz C. G. FreitasAbstract:Nanobiosensors can be built via functionalization of atomic force microscopy (AFM) tips with Biomolecules capable of interacting with the analyte on a substrate, and the detection being performed by measuring the force between the Immobilized Biomolecule and the analyte. The optimization of such sensors may require multiple experiments to determine suitable experimental conditions for the immobilization and detection. In this study we employ molecular modeling techniques to assist in the design of nanobiosensors to detect herbicides. As a proof of principle, the properties of acetyl co-enzyme A carboxylase (ACC) were obtained with molecular dynamics simulations, from which the dimeric form in an aqueous solution was found to be more suitable for immobilization owing to a smaller structural fluctuation than the monomeric form. Upon solving the nonlinear Poisson–Boltzmann equation using a finite-difference procedure, we found that the active sites of ACC exhibited a positive surface potential while the remainder of the ACC surface was negatively charged. Therefore, optimized biosensors should be prepared with electrostatic adsorption of ACC onto an AFM tip functionalized with positively charged groups, leaving the active sites exposed to the analyte. The preferential orientation for the herbicides diclofop and atrazine with the ACC active site was determined by molecular docking calculations which displayed an inhibition coefficient of 0.168 μM for diclofop, and 44.11 μM for atrazine. This binding selectivity for the herbicide family of diclofop was confirmed by semiempirical PM6 quantum chemical calculations which revealed that ACC interacts more strongly with the herbicide diclofop than with atrazine, showing binding energies of −119.04 and +8.40 kcal mol−1, respectively. The initial measurements of the proposed nanobiosensor validated the theoretical calculations and displayed high selectivity for the family of the diclofop herbicides.
Eduardo De Faria Franca - One of the best experts on this subject based on the ideXlab platform.
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designing an enzyme based nanobiosensor using molecular modeling techniques
Physical Chemistry Chemical Physics, 2011Co-Authors: Eduardo De Faria Franca, Fabio L Leite, Richard A Cunha, Osvaldo N. Oliveira, Luiz C. G. FreitasAbstract:Nanobiosensors can be built via functionalization of atomic force microscopy (AFM) tips with Biomolecules capable of interacting with the analyte on a substrate, and the detection being performed by measuring the force between the Immobilized Biomolecule and the analyte. The optimization of such sensors may require multiple experiments to determine suitable experimental conditions for the immobilization and detection. In this study we employ molecular modeling techniques to assist in the design of nanobiosensors to detect herbicides. As a proof of principle, the properties of acetyl co-enzyme A carboxylase (ACC) were obtained with molecular dynamics simulations, from which the dimeric form in an aqueous solution was found to be more suitable for immobilization owing to a smaller structural fluctuation than the monomeric form. Upon solving the nonlinear Poisson–Boltzmann equation using a finite-difference procedure, we found that the active sites of ACC exhibited a positive surface potential while the remainder of the ACC surface was negatively charged. Therefore, optimized biosensors should be prepared with electrostatic adsorption of ACC onto an AFM tip functionalized with positively charged groups, leaving the active sites exposed to the analyte. The preferential orientation for the herbicides diclofop and atrazine with the ACC active site was determined by molecular docking calculations which displayed an inhibition coefficient of 0.168 μM for diclofop, and 44.11 μM for atrazine. This binding selectivity for the herbicide family of diclofop was confirmed by semiempirical PM6 quantum chemical calculations which revealed that ACC interacts more strongly with the herbicide diclofop than with atrazine, showing binding energies of −119.04 and +8.40 kcal mol−1, respectively. The initial measurements of the proposed nanobiosensor validated the theoretical calculations and displayed high selectivity for the family of the diclofop herbicides.
Chihkung Lee - One of the best experts on this subject based on the ideXlab platform.
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an integrated platform for Biomolecule interaction analysis
Proceedings of SPIE, 2013Co-Authors: Chiaming Jan, Peii Tsai, Shinting Chou, Shusheng Lee, Chihkung LeeAbstract:We developed a new metrology platform which can detect real-time changes in both a phase-interrogation mode and intensity mode of a SPR (surface plasmon resonance). We integrated a SPR and ellipsometer to a biosensor chip platform to create a new biomolecular interaction measurement mechanism. We adopted a conductive ITO (indium-tinoxide) film to the bio-sensor platform chip to expand the dynamic range and improve measurement accuracy. The thickness of the conductive film and the suitable voltage constants were found to enhance performance. A circularly polarized ellipsometry configuration was incorporated into the newly developed platform to measure the label-free interactions of recombinant human C-reactive protein (CRP) with Immobilized Biomolecule target monoclonal human CRP antibody at various concentrations. CRP was chosen as it is a cardiovascular risk biomarker and is an acute phase reactant as well as a specific prognostic indicator for inflammation. We found that the sensitivity of a phaseinterrogation SPR is predominantly dependent on the optimization of the sample incidence angle. The effect of the ITO layer effective index under DC and AC effects as well as an optimal modulation were experimentally performed and discussed. Our experimental results showed that the modulated dynamic range for phase detection was 10E-2 RIU based on a current effect and 10E-4 RIU based on a potential effect of which a 0.55 (°/RIU) measurement was found by angular-interrogation. The performance of our newly developed metrology platform was characterized to have a higher sensitivity and less dynamic range when compared to a traditional full-field measurement system.
Fabio L Leite - One of the best experts on this subject based on the ideXlab platform.
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designing an enzyme based nanobiosensor using molecular modeling techniques
Physical Chemistry Chemical Physics, 2011Co-Authors: Eduardo De Faria Franca, Fabio L Leite, Richard A Cunha, Osvaldo N. Oliveira, Luiz C. G. FreitasAbstract:Nanobiosensors can be built via functionalization of atomic force microscopy (AFM) tips with Biomolecules capable of interacting with the analyte on a substrate, and the detection being performed by measuring the force between the Immobilized Biomolecule and the analyte. The optimization of such sensors may require multiple experiments to determine suitable experimental conditions for the immobilization and detection. In this study we employ molecular modeling techniques to assist in the design of nanobiosensors to detect herbicides. As a proof of principle, the properties of acetyl co-enzyme A carboxylase (ACC) were obtained with molecular dynamics simulations, from which the dimeric form in an aqueous solution was found to be more suitable for immobilization owing to a smaller structural fluctuation than the monomeric form. Upon solving the nonlinear Poisson–Boltzmann equation using a finite-difference procedure, we found that the active sites of ACC exhibited a positive surface potential while the remainder of the ACC surface was negatively charged. Therefore, optimized biosensors should be prepared with electrostatic adsorption of ACC onto an AFM tip functionalized with positively charged groups, leaving the active sites exposed to the analyte. The preferential orientation for the herbicides diclofop and atrazine with the ACC active site was determined by molecular docking calculations which displayed an inhibition coefficient of 0.168 μM for diclofop, and 44.11 μM for atrazine. This binding selectivity for the herbicide family of diclofop was confirmed by semiempirical PM6 quantum chemical calculations which revealed that ACC interacts more strongly with the herbicide diclofop than with atrazine, showing binding energies of −119.04 and +8.40 kcal mol−1, respectively. The initial measurements of the proposed nanobiosensor validated the theoretical calculations and displayed high selectivity for the family of the diclofop herbicides.
Richard A Cunha - One of the best experts on this subject based on the ideXlab platform.
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designing an enzyme based nanobiosensor using molecular modeling techniques
Physical Chemistry Chemical Physics, 2011Co-Authors: Eduardo De Faria Franca, Fabio L Leite, Richard A Cunha, Osvaldo N. Oliveira, Luiz C. G. FreitasAbstract:Nanobiosensors can be built via functionalization of atomic force microscopy (AFM) tips with Biomolecules capable of interacting with the analyte on a substrate, and the detection being performed by measuring the force between the Immobilized Biomolecule and the analyte. The optimization of such sensors may require multiple experiments to determine suitable experimental conditions for the immobilization and detection. In this study we employ molecular modeling techniques to assist in the design of nanobiosensors to detect herbicides. As a proof of principle, the properties of acetyl co-enzyme A carboxylase (ACC) were obtained with molecular dynamics simulations, from which the dimeric form in an aqueous solution was found to be more suitable for immobilization owing to a smaller structural fluctuation than the monomeric form. Upon solving the nonlinear Poisson–Boltzmann equation using a finite-difference procedure, we found that the active sites of ACC exhibited a positive surface potential while the remainder of the ACC surface was negatively charged. Therefore, optimized biosensors should be prepared with electrostatic adsorption of ACC onto an AFM tip functionalized with positively charged groups, leaving the active sites exposed to the analyte. The preferential orientation for the herbicides diclofop and atrazine with the ACC active site was determined by molecular docking calculations which displayed an inhibition coefficient of 0.168 μM for diclofop, and 44.11 μM for atrazine. This binding selectivity for the herbicide family of diclofop was confirmed by semiempirical PM6 quantum chemical calculations which revealed that ACC interacts more strongly with the herbicide diclofop than with atrazine, showing binding energies of −119.04 and +8.40 kcal mol−1, respectively. The initial measurements of the proposed nanobiosensor validated the theoretical calculations and displayed high selectivity for the family of the diclofop herbicides.
