Biacore 3000 evaluation software

Manufactured by Cytiva

The Biacore 3000 Evaluation Software is a computer program that is used to analyze data generated by the Biacore 3000 instrument, a surface plasmon resonance (SPR) system. The software is designed to process and interpret the real-time interaction data collected during experiments conducted on the Biacore 3000 platform.

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Lab products found in correlation

Glycine, by GE Healthcare (2 mentions) Biacore 3000, by GE Healthcare (1 mentions) Cm5 sensor chip, by GE Healthcare (1 mentions) Phosphoric acid, by GE Healthcare (1 mentions) Cm5 biacore chip, by Cytiva (1 mentions)

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Biacore 3000 (169 citations) Biacore Evaluation Software (20 citations) Evaluation software (13 citations)

4 protocols using biacore 3000 evaluation software

Kinetic Analysis of Anti-PspA Antibodies

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In order to kinetically analyze the binding activity of anti-PspA mouse antibodies 139G3, 140G1, 140G11 and 140H1, the binding activity was measured by surface plasmon resonance method (SPR). Three different recombinant PspA proteins (PspA-D39, PspA-BAA-658 and PspA-TIGR4) were immobilized on different CM5 sensor chips (GE Healthcare Bio-Sciences) using an amine coupling method. Anti-PspA antibodies were then diluted in two-fold serial dilutions (40 nM to 1.25 nM or 20 nM to 0.625 nM concentration ranges) and added to the coated sensor chips at a flow rate of 30 μL/min using a Biacore 3000 (GE Healthcare Bio-Sciences). Bivalent binding modeling was used to analyze the binding of each mAb (Biacore 3000 Evaluation software, Biacore). As a result, an association rate constant ka1, a dissociation rate constant kd1, and a dissociation constant K_D1 (kd/ka), as well as an association rate constant ka2, a dissociation rate constant kd2, and a dissociation constant K_D2 (kd/ka), for each individual antibody were obtained.

Kristian S.A., Ota T., Bubeck S.S., Cho R., Groff B.C., Kubota T., Destito G., Laudenslager J., Koriazova L., Tahara T, & Kanda Y. (2016). Generation and Improvement of Effector Function of a Novel Broadly Reactive and Protective Monoclonal Antibody against Pneumococcal Surface Protein A of Streptococcus pneumoniae. PLoS ONE, 11(5), e0154616.

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SPR Binding of Nanoparticles to Tumor ECM

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For SPR binding experiments to tumor ECM protein chips, nanoparticle samples were assayed at a flow rate of 20 μl/min with an injection time of 3 min followed by a 2.5 min wait for dissociation, before chip regeneration with 10 mM glycine, pH 1.75 (GE Healthcare). Nanoparticle binding was assayed with nanoparticle concentrations of 1 mg/ml diluted in running buffer. Data were analyzed using Biacore 3000 Evaluation Software, where data from reference flow path was subtracted from the experimental flow path data to give the final sensorgrams.

Wadajkar A.S., Dancy J.G., Carney C.P., Hampton B.S., Ames H.M., Winkles J.A., Woodworth G.F, & Kim A.J. (2019). Leveraging Surface Plasmon Resonance to Dissect the Interfacial Properties of Nanoparticles: Implications for Tissue Binding and Tumor Penetration. Nanomedicine : nanotechnology, biology, and medicine, 20, 102024.

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Nanoparticle-serum protein interactions

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The 10× normal mouse serum was diluted to 1× using the HBS-N buffer. The biodegradable PLGA-PVA, PLGA-ChA, PLGA-F127, and PLGA-PEG nanoparticles were first incubated with 1× mouse blood serum proteins (4–8 mg/ml) for 1 h at 37 °C. The blood serum protein-coated nanoparticles (1 mg/ml) were assayed at a flow rate of 20 μl/min with an injection time of 3 min followed by a 2.5 min wait for dissociation, before chip regeneration with 10 mM glycine, pH 1.75. In addition, the binding of 10× diluted blood serum was assayed with the same condition as above. Data were analyzed using Biacore 3000 Evaluation Software as described above, with additional subtraction of the blood serum binding data from blood serum protein-coated nanoparticle binding data.

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Nanoparticle Binding Affinity to Fn14 Evaluated by SPR

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Nanoparticle binding affinities to Fn14 extracellular domain was evaluated by SPR using a Biacore 3000 instrument at 25°C. The Fn14 extracellular domain (Cell Sciences, Canton, MA) was conjugated to a CM5 Biacore chip, with three different Fn14 ligand RU values ranging from 50 to 300. The first flow path (Fc1) was activated and blocked with ethanolamine to serve as a reference for each binding run, as suggested per manufacturer’s protocol. The running buffer was degassed 10 mM HEPES buffer (pH 7.4) containing 150 mM NaCl, 0.05% surfactant P-20 with 50 µM EDTA (HBS-P+). For SPR experiments, samples were run at a flow rate of 20 µL/min with an injection time of 3 min followed by a 2.5 min wait time for dissociation, before chip regeneration with either 100 mM phosphoric acid, pH 3 or 10 mM glycine, pH 1.75 (GE Healthcare). IgG isotype (25 nM) was used as a negative control and ITEM4 (25 nM) as a positive control. Nanoparticle binding was assayed with particle concentrations ranging between 1 µg/mL and 200 µg/mL diluted in running buffer. Data were analyzed using Biacore 3000 Evaluation Software, where data from Fc1 was subtracted from the Fc2, Fc3, and Fc4 data to give the final sensorgrams. Equilibrium binding affinities (K_D) were calculated as previously described [38 (link)].

Schneider C.S., Perez J.G., Cheng E., Zhang C., Mastorakos P., Hanes J., Winkles J.A., Woodworth G.F, & Kim A.J. (2014). Minimizing the Non-specific Binding of Nanoparticles to the Brain Enables Active Targeting of Fn14-positive Glioblastoma Cells. Biomaterials, 42, 42-51.

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