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Biomolecular Interaction Analysis Using an Optical Surface Plasmon Resonance Biosensor: The Marquardt Algorithm vs Newton Iteration Algorithm.

Hu J, Ma L, Wang S, Yang J, Chang K, Hu X, Sun X, Chen R, Jiang M, Zhu J, Zhao Y - PLoS ONE (2015)

Bottom Line: A number of experimental data may lead to complicated real-time curves that do not fit well to the kinetic model.The association and dissociation rate constants, ka, kd and the affinity parameters for the biomolecular interaction, KA, KD, were experimentally obtained 6.969×10(5) mL·g(-1)·s(-1), 0.00073 s(-1), 9.5466×10(8) mL·g(-1) and 1.0475×10(-9) g·mL(-1), respectively from the injection of the HBsAg solution with the concentration of 16 ng·mL(-1).The kinetic constants were evaluated distinctly by using the obtained data from the curve-fitting results.

View Article: PubMed Central - PubMed

Affiliation: Department of Electrical Engineering, Henan Agricultural University, Zhengzhou, China; State Key Laboratory of Wheat and Maize Crop Science, Zhengzhou, China.

ABSTRACT
Kinetic analysis of biomolecular interactions are powerfully used to quantify the binding kinetic constants for the determination of a complex formed or dissociated within a given time span. Surface plasmon resonance biosensors provide an essential approach in the analysis of the biomolecular interactions including the interaction process of antigen-antibody and receptors-ligand. The binding affinity of the antibody to the antigen (or the receptor to the ligand) reflects the biological activities of the control antibodies (or receptors) and the corresponding immune signal responses in the pathologic process. Moreover, both the association rate and dissociation rate of the receptor to ligand are the substantial parameters for the study of signal transmission between cells. A number of experimental data may lead to complicated real-time curves that do not fit well to the kinetic model. This paper presented an analysis approach of biomolecular interactions established by utilizing the Marquardt algorithm. This algorithm was intensively considered to implement in the homemade bioanalyzer to perform the nonlinear curve-fitting of the association and disassociation process of the receptor to ligand. Compared with the results from the Newton iteration algorithm, it shows that the Marquardt algorithm does not only reduce the dependence of the initial value to avoid the divergence but also can greatly reduce the iterative regression times. The association and dissociation rate constants, ka, kd and the affinity parameters for the biomolecular interaction, KA, KD, were experimentally obtained 6.969×10(5) mL·g(-1)·s(-1), 0.00073 s(-1), 9.5466×10(8) mL·g(-1) and 1.0475×10(-9) g·mL(-1), respectively from the injection of the HBsAg solution with the concentration of 16 ng·mL(-1). The kinetic constants were evaluated distinctly by using the obtained data from the curve-fitting results.

No MeSH data available.


Related in: MedlinePlus

The fitting results obtained from both Newton Iteration algorithm and Marquardt algorithm.The data marked with a triangle is obtained in the average of more than three sets of measurement results in RU, and the fitted curve was marked with a solid line. A. The curve-fitting using the Newton Iteration algorithm with the initial value of 0.0095, B. The curve-fitting using the Newton Iteration algorithm with the initial value of 0.011, C. The curve-fitting using the Marquardt algorithm with the initial value of 0.0095, D. The curve-fitting using the Marquardt algorithm with the initial value of 0.011.
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pone.0132098.g002: The fitting results obtained from both Newton Iteration algorithm and Marquardt algorithm.The data marked with a triangle is obtained in the average of more than three sets of measurement results in RU, and the fitted curve was marked with a solid line. A. The curve-fitting using the Newton Iteration algorithm with the initial value of 0.0095, B. The curve-fitting using the Newton Iteration algorithm with the initial value of 0.011, C. The curve-fitting using the Marquardt algorithm with the initial value of 0.0095, D. The curve-fitting using the Marquardt algorithm with the initial value of 0.011.

Mentions: The curve-fitting obtained from using both Newton Iteration algorithm and Marquardt algorithm was shown in Fig 2.


Biomolecular Interaction Analysis Using an Optical Surface Plasmon Resonance Biosensor: The Marquardt Algorithm vs Newton Iteration Algorithm.

Hu J, Ma L, Wang S, Yang J, Chang K, Hu X, Sun X, Chen R, Jiang M, Zhu J, Zhao Y - PLoS ONE (2015)

The fitting results obtained from both Newton Iteration algorithm and Marquardt algorithm.The data marked with a triangle is obtained in the average of more than three sets of measurement results in RU, and the fitted curve was marked with a solid line. A. The curve-fitting using the Newton Iteration algorithm with the initial value of 0.0095, B. The curve-fitting using the Newton Iteration algorithm with the initial value of 0.011, C. The curve-fitting using the Marquardt algorithm with the initial value of 0.0095, D. The curve-fitting using the Marquardt algorithm with the initial value of 0.011.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4493042&req=5

pone.0132098.g002: The fitting results obtained from both Newton Iteration algorithm and Marquardt algorithm.The data marked with a triangle is obtained in the average of more than three sets of measurement results in RU, and the fitted curve was marked with a solid line. A. The curve-fitting using the Newton Iteration algorithm with the initial value of 0.0095, B. The curve-fitting using the Newton Iteration algorithm with the initial value of 0.011, C. The curve-fitting using the Marquardt algorithm with the initial value of 0.0095, D. The curve-fitting using the Marquardt algorithm with the initial value of 0.011.
Mentions: The curve-fitting obtained from using both Newton Iteration algorithm and Marquardt algorithm was shown in Fig 2.

Bottom Line: A number of experimental data may lead to complicated real-time curves that do not fit well to the kinetic model.The association and dissociation rate constants, ka, kd and the affinity parameters for the biomolecular interaction, KA, KD, were experimentally obtained 6.969×10(5) mL·g(-1)·s(-1), 0.00073 s(-1), 9.5466×10(8) mL·g(-1) and 1.0475×10(-9) g·mL(-1), respectively from the injection of the HBsAg solution with the concentration of 16 ng·mL(-1).The kinetic constants were evaluated distinctly by using the obtained data from the curve-fitting results.

View Article: PubMed Central - PubMed

Affiliation: Department of Electrical Engineering, Henan Agricultural University, Zhengzhou, China; State Key Laboratory of Wheat and Maize Crop Science, Zhengzhou, China.

ABSTRACT
Kinetic analysis of biomolecular interactions are powerfully used to quantify the binding kinetic constants for the determination of a complex formed or dissociated within a given time span. Surface plasmon resonance biosensors provide an essential approach in the analysis of the biomolecular interactions including the interaction process of antigen-antibody and receptors-ligand. The binding affinity of the antibody to the antigen (or the receptor to the ligand) reflects the biological activities of the control antibodies (or receptors) and the corresponding immune signal responses in the pathologic process. Moreover, both the association rate and dissociation rate of the receptor to ligand are the substantial parameters for the study of signal transmission between cells. A number of experimental data may lead to complicated real-time curves that do not fit well to the kinetic model. This paper presented an analysis approach of biomolecular interactions established by utilizing the Marquardt algorithm. This algorithm was intensively considered to implement in the homemade bioanalyzer to perform the nonlinear curve-fitting of the association and disassociation process of the receptor to ligand. Compared with the results from the Newton iteration algorithm, it shows that the Marquardt algorithm does not only reduce the dependence of the initial value to avoid the divergence but also can greatly reduce the iterative regression times. The association and dissociation rate constants, ka, kd and the affinity parameters for the biomolecular interaction, KA, KD, were experimentally obtained 6.969×10(5) mL·g(-1)·s(-1), 0.00073 s(-1), 9.5466×10(8) mL·g(-1) and 1.0475×10(-9) g·mL(-1), respectively from the injection of the HBsAg solution with the concentration of 16 ng·mL(-1). The kinetic constants were evaluated distinctly by using the obtained data from the curve-fitting results.

No MeSH data available.


Related in: MedlinePlus