Biacore 8k+

Manufactured by Cytiva

The Biacore 8k+ is a label-free, real-time interaction analysis instrument that enables the study of biomolecular interactions. It measures binding kinetics and affinity between molecules in a sample using surface plasmon resonance (SPR) technology.

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Lab products found in correlation

Biacore insight, by Cytiva (14 mentions) Biacore t200, by Cytiva (6 mentions) Biacore 8k, by Cytiva (5 mentions) Biacore 8k instrument, by Cytiva (3 mentions) Insight evaluation software, by Cytiva (2 mentions) Biacore insight evaluation software, by Cytiva (2 mentions) Biacore s200, by Cytiva (1 mentions) Cm5 chip, by Cytiva (1 mentions) 8k instrument, by Cytiva (1 mentions) Insight evaluation, by Cytiva (1 mentions) S200 evaluation software, by Cytiva (1 mentions) Biacore 8k, by GE Healthcare (1 mentions) Series s sensor chip cm5, by GE Healthcare (1 mentions) Hbs p, by GE Healthcare (1 mentions) Series s protein a chip, by Cytiva (1 mentions) Series s sensor chip cm5, by Cytiva (1 mentions) Biacore 8k insights evaluation software, by Cytiva (1 mentions) His capture kit, by Cytiva (1 mentions)

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Biacore 8K (384 citations) Biacore 8K instrument (36 citations) BIAcore 8K system (12 citations) Biacore 8K SPR system (3 citations) Biacore 8K SPR instrument (2 citations) Biacore 8K control software 2.0.1 (2 citations) Biacore 8K surface plasmon resonance instrument (2 citations) Biacore 8K Insights Evaluation Software (2 citations) Biacore 8K Evaluation Software 3.0 (1 citations)

33 protocols using biacore 8k+

Surface Plasmon Resonance Analysis of PEAK Protein Interactions

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SPR binding studies of PEAK PRM peptides to CrkII^NSH3 were performed using a Biacore S200 Instrument (Cytiva). Purified CrkII^NSH3 was diluted to 5 µg ml⁻¹ in 10 mM sodium acetate pH 4.0 and amine coupled at 25 °C to a Series S CM5 sensor chip, in HBS-N running buffer (20 mM HEPES pH 7.4, 150 mM NaCl) to a final immobilization level of 1100–1400 response units (RU), followed by surface deactivation using 1 M ethanolamine. A blank activation/deactivation was used for the reference surface. Peptide binding studies were performed at 20 °C in HBS-TP running buffer (20 mM HEPES pH 7.4, 150 mM NaCl, 1 mM TCEP, 0.005% (v/v) Tween-P20). Peptides were first prepared as 10 mM stocks in water: PEAK PRM peptides: PEAK3^54–66, PEAK1^1150–1162, PEAK2^709–721, PEAK2^809–821; or PEAK tandem motif peptides: PEAK3^{tandem, 54–74}, PEAK3^{tandem,54–74}-pS69, PEAK1^{tandem,1152–1171}, PEAK1^{tandem,1152–1171}-pT1165, PEAK2^{tandem,812–831}, and PEAK2^{tandem,812–831}-pS826, phosphorylated or non-phosphorylated in the 14-3-3 motif. Peptide stocks were further diluted to in running buffer to 10 or 20 µM and prepared as a 11-point concentration series (2-fold serial dilution, 100 µM–100 nM for PEAK PRM peptides, or 20 µM–20 nM for PEAK tandem motif peptides). Samples were injected in a multi-cycle run (flow rate 30 µl min⁻¹, contact time of 60 s, dissociation 120 s) without regeneration. Sensorgrams were double referenced, and steady-state binding data fitted using a 1:1 binding model using Biacore S200 Evaluation Software (Cytiva, v. 1.1). Representative sensorgrams and fitted dissociation constant (K_D) values, depicted as mean ± S.E.M. (n ≥ 3 independent experiments) or mean ± S.D. (n = 2), are shown in Supplementary Data 1–6 (SPR data).
SPR binding studies of PEAK tandem peptides to 14-3-3 isoforms were performed using a Biacore S200 Instrument (Cytiva). Immobilization of 14-3-3 isoforms (14-3-3γ, 14-3-3ε, 14-3-3σ, and 14-3-3η; diluted to 10 µg ml⁻¹ in 10 mM sodium acetate pH 4.0) was performed as described for CrkII^NSH3 at 20 °C to a final immobilization level 1800–2900 RU. Binding studies were run using PEAK tandem peptides (11-point concentration series, 2-fold serial dilution; 10 µM–10 nM for PEAK3^tandem-pS69, 20 µM–20 nM for all other peptides). SPR binding experiments and steady-state data analysis were performed as described for CrkII^NSH3. Representative sensorgrams and fitted dissociation constant (K_D) values, depicted as mean ± S.E.M. (n ≥ 3 independent experiments), are shown in Supplementary Data 1–6 (SPR data).
PEAK proteins and adapters proteins (full length or individual domains) were biotinylated using EZ-Link™ NHS-PEG4-Biotin (Thermo Fisher) at a 1:1 molar ratio (100 µM) for 1 h at room temperature, then excess biotin was removed by buffer exchange using a Zeba™ Spin Desalting Column (Thermo Fisher) into HBS-T buffer (20 mM HEPES pH 7.4, 150 mM NaCl, 1 mM TCEP).
SPR binding studies of PEAK pY phosphopeptides to CrkII/Grb2 and sub-domains. Binding studies were performed using a Biacore 8K+ Instrument (Cytiva) and analyzed using Biacore Insight Evaluation Software (v. 3.0.12.15655). Biotinylated adapter proteins (Grb2^FL, Grb2^SH2, CrkII^SH2, CrkII^FL monomer, CrkII^FL dimer) were immobilized using a biotin CAPture kit (Cytiva) in HBS-TP running buffer at 20 °C. Binding studies and steady-state data analysis using PEAK pY peptides (consensus SH2-pY peptide; PEAK3^23–38-pY²⁴ peptide and PEAK1^1106–1121-pY¹¹⁰⁷ peptide) were performed as described for CrkII^NSH3 with the following modifications: HBS-PT running buffer was supplemented with 2% DMSO to reduce nonspecific interactions and an additional regeneration step (60 s injection of 1 M NaCl) was included between cycles. Representative sensorgrams and fitted dissociation constant (K_D) values, depicted as mean ± S.E.M. (n ≥ 3 independent experiments), are shown in Supplementary Data 1–6 (SPR data).
SPR binding studies of PEAK proteins to full length CrkII/Grb2 and sub-domains were performed using a Biacore 8K+ Instrument (Cytiva) and analyzed using Biacore Insight Evaluation Software (v. 3.0.12.15655). Biotinylated PEAK3^FL (14-3-3 complex), PEAK1^IDR1 and PEAK2^IDR1 purified from insect cells and PEAK3^FL (no bound 14-3-3) purified from E.coli, were phosphorylated using recombinant Src kinase as previously described. Biotinylated PEAK proteins (with or without Src phosphorylation; 500 nM in HBS-TP) were immobilized using a biotin CAPture kit (Cytiva) in HBS-TP running buffer at 20 °C. Binding studies and steady-state data analysis were performed as described for CrkII^NSH3 with the inclusion of an additional surface regeneration step (60 s injection of 1 M NaCl) between cycles. For Grb2^FL, Grb2^SH2, CrkII^SH2, CrkII^FL monomer and CrkII^FL dimer, to reduce nonspecific interactions the HBS-TP running buffer was supplemented with additional NaCl to a final concentration of 500 mM.
Binding studies for 14-3-3ɣ were undertaken in the same way in multi cycle mode (8 point, 3-fold serial dilution series, 0.46–1000 nM, 60 s contact time, 300 s dissociation). Of the PEAKs, only PEAK3^FL purified from insect cells was observed to bind recombinant 14-3-3ɣ, irrespective of Src phosphorylation of PEAK3^FL. This is consistent with the biotinylated PEAK3^FL purified from insect cells being prepared from a complex bound to endogenous 14-3-3 and phosphorylation of this sample at S69 in the tandem site by MS analysis. The availability of this site to reversibly bind recombinant 14-3-3ɣ in these SPR experiments indicates that, under the constant flow conditions of the SPR experiment, the majority of insect cell-derived 14-3-3 was able to dissociate from immobilized PEAK3^FL. Some insect-cell derived 14-3-3 may remain captured on the sensor surface, however this did not appear to significantly influence binding interactions, as similar data were obtained for PEAK3^FL expressed in E.coli that did not bind 14-3-3. An accurate K_D could not be determined for 14-3-3ɣ to insect cell derived PEAK3^FL, due to the bivalence of this interaction that does not fit a 1:1 kinetic model. However, fitting using a bivalent analyte model suggests a high-affinity interaction with likely K_D ≪ 1 µM, consistent with the qualitatively slow dissociation kinetics observed.
Representative sensorgrams and fitted dissociation constant (K_D) values, depicted as mean ± S.D. (n = 2 independent experiments) or ±S.E.M. (n ≥ 3 independent experiments), are shown in the Supplementary Information and full SPR data can be found in Supplementary Data 1–6.

Roy M.J., Surudoi M.G., Kropp A., Hou J., Dai W., Hardy J.M., Liang L.Y., Cotton T.R., Lechtenberg B.C., Dite T.A., Ma X., Daly R.J., Patel O, & Lucet I.S. (2023). Structural mapping of PEAK pseudokinase interactions identifies 14-3-3 as a molecular switch for PEAK3 signaling. Nature Communications, 14, 3542.

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Biacore Assay for RTA Compound Affinity

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The affinity of all compounds in the RTA focused library was measured using Biacore 8K⁺ using the same conditions as previously reported.^{43 (link)} Biacore 8K⁺ has eight channels with two flow cells (Fc) in each channel. RTA was immobilized on Fc2 of a CM5 chip at 5800 to 6000 RU using the amine coupling method. Fc1 was activated and blocked without RTA using the same method as Fc2 as reference. Compounds were passed over Fc1 and Fc2 in all eight channels in parallel. Data were analyzed using the Biacore Insight Evaluation Software with DMSO correction. The binding sensorgrams of Fc1 were subtracted from Fc2 to correct for the buffer mismatch. The buffer alone was subtracted from all sensorgrams at different concentrations to correct for any baseline drift. The running buffer was PBS-P (20 mM phosphate, 2.7 mM KCl, 137 mM NaCl, and 0.05% surfactant P20, pH 7.4) with 2% DMSO. Fragments at 0.7, 2.1, 6.2, 18.5, 55.6, 166.7, and 500 μM were passed over both surfaces at 30 μL/min for 60 s and dissociation for another 60 s. There was no nonspecific binding with any of the compounds tested.

Li X.P., Harijan R.K., Cao B., Kahn J.N., Pierce M., Tsymbal A.M., Roberge J.Y., Augeri D, & Tumer N.E. (2021). Synthesis and Structural Characterization of Ricin Inhibitors Targeting Ribosome Binding Using Fragment-Based Methods and Structure-Based Design. Journal of medicinal chemistry, 64(20), 15334-15348.

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Binding Affinities of Herbal Compounds

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The binding affinities of Paeoniflorin, Emodin, and Rhein to hACE2, SARS-CoV-2 S-RBD, and MMP9 were assessed using the Biacore 8K+ instrument (Cytiva, America). Proteins hACE2, SARS-CoV-2 S-RBD, and MMP9, all sourced from Sino Biological, Beijing, China, were immobilized on a CM5 sensor chip. The immobilization levels for these proteins were approximately 10,000 response units (RU). A series of compound concentrations, each containing 5% DMSO, were sequentially introduced into the channel to ascertain binding affinity. The dissociation constants (K D ) for the compounds were calculated by fitting the data to a steady-state affinity model using the Biacore 8K+ Evaluation Software.
In the competitive inhibition assays, hACE2 or S-RBD proteins were immobilized on the CM5 sensor chip via amine-coupling, with immobilization levels around 3,000 RU. Paeoniflorin and Rhein were initially injected for pre-incubation with hACE2 or S-RBD proteins, respectively. Subsequent injections of 5 nM S-RBD or 30 nM hACE2 were administered to evaluate their interaction with hACE2 or S-RBD in the presence of Paeoniflorin or Rhein. The efficacy of inhibition was determined by comparing response units with and without the active compounds.

Tian C., Zhao J., Wang Q., Luo K., Zhao S., Li J., Wan L., Ma K., Yao C., Zhou Y., & Li M. (2024). Exploring the Therapeutic Efficacy: Unveiling the Active Compounds of Huashi Baidu Granules Against COVID-19.

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Multicycle Kinetics of Anti-mβc mAbs

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Multicycle kinetics was performed on a Biacore 8K+ instrument (Biacore Life Sciences, Cytiva) to determine the binding affinities for anti-mβc mAbs. A Series S CM5 sensor chip (Cytiva) was used together with an EDC/NHS amine coupling kit (Cytiva) to immobilize anti-His antibodies to ~13,000 RU on flow cells 1 and 2 as per manufacturer instructions. Commercially available HBS-EP+ buffer (10 mM HEPES, 150 mM NaCl, 3 mM EDTA, 0.05% surfactant P20) was used as running buffer and to dilute the ligand and analyte. Recombinant mβc (1 μg/mL) was captured for 30 s at a rate of 10 µL/min on the surface of flow cell 2, while flow cell 1 was left unmodified and served as the reference surface for subtracting buffer contributions to the binding signal. The soluble common beta ECD containing a C-terminal His tag was used to condition the chip in separate cycles at 1 µg/mL for 30 s with a flow rate of 10 µL/min, prior to ligand capture. MAbs were diluted to 1 nM in HBS-EP+ and assessed using a series of 5 analyte concentrations from 1 nM to 62.5 pM. Association of each analyte was performed over 300 s, followed by dissociation for 600 s. The sensor surface was regenerated between runs using 10 mM glycine pH 1.5 for 60 s at a flow rate of 30 µL/min. Binding assays were conducted at 37 °C. Data were corrected by subtraction of blank runs, and sensorgram curves were fitted using a 1:1 binding model in the Biacore Insight Evaluation Software (Biacore Life Sciences, Cytiva). Dissociation (k_d) kinetic rate constants were derived based on the local fit at each concentration.

Panagides N., Zacchi L.F., De Souza M.J., Morales R.A., Karnowski A., Liddament M.T., Owczarek C.M., Mahler S.M., Panousis C., Jones M.L, & Fercher C. (2022). Evaluation of Phage Display Biopanning Strategies for the Selection of Anti-Cell Surface Receptor Antibodies. International Journal of Molecular Sciences, 23(15), 8470.

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Annexin A6 Binding Kinetics to Lipid Bilayers

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All SPR studies were performed on a Biacore 8K+ instrument (Cytiva) at 25°C. A series S L1 chip (lipophilic groups are covalently attached to carboxymethylated dextran, making the surface suitable for direct attachment of lipid membrane vesicles) (Cytiva) was used for the annexin A6/lipid interaction studies. Briefly, the L1 sensor chip was equilibrated in running buffer (10 mM HEPES, pH 7.4, 150 mM NaCl) and conditioned with two 30-second injections of 40 mM octyl glucoside at 10 μL/min before liposome immobilization (75 (link)). We captured 0.5 mM +PS and –PS liposomes (flow rate 2 μL/min) onto the active and reference flow cell surfaces, respectively, to approximately 10,000 RU to form the lipid bilayer. This was followed by two 60-second injections of 10 mM NaOH at 10 μL/min to remove any unbound liposomes on the L1 chip. Initially, the Ca²⁺ dependence of annexin A6 binding to +PS and –PS lipid was tested. The CaCl₂ concentration in the running buffer was varied between 0 and 2.5 mM (0, 26, 52, 104, 208, 417, 833, or 2500 μM), and the binding signal RU and kinetics of the annexin A6/lipid interactions were analyzed. This was followed by dose-response kinetics studies on the annexin A6/+PS lipid interactions at 100 μM CaCl₂. Since –PS showed very minimal binding at 100 μM CaCl₂, it was used as a negative control lipid and captured on the reference flow cell surface. +PS was captured on the active flow cell surface. Parallel dose-response kinetics was run with 8 concentrations (0.78–100 nM) at 2-fold dilutions on 8 channels of the sensor chip. annexin A6 was injected at 50 μL/min with association time of 240 seconds and dissociation time of 600 seconds. We analyzed all data using Biacore Insight Evaluation software (ver. 3.0.12; Cytiva). Raw sensorgrams were reference-subtracted and blank-buffer-subtracted before kinetic and affinity analysis to account for nonspecific binding and injection artifacts. Association (K_A/M/s) and dissociation (K_D/s) rate constants and binding affinity (K_D) values were determined using a 1:1 kinetics binding model. The closeness of fit between the experimental data and fitted curves was assessed using χ² (average squared residual).

Demonbreun A.R., Bogdanovic E., Vaught L.A., Reiser N.L., Fallon K.S., Long A.M., Oosterbaan C.C., Hadhazy M., Page P.G., Joseph P.R., Cowen G., Telenson A.M., Khatri A., Sadleir K.R., Vassar R, & McNally E.M. (2022). A conserved annexin A6–mediated membrane repair mechanism in muscle, heart, and nerve. JCI Insight, 7(14), e158107.

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Kinetics and Affinity Characterization of Anti-TfR1 Antibodies

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Example 5

Kinetics and affinity values from evaluation of anti-TfR1 Fab fragments, in chimeric rabbit and humanized forms, binding to recombinant human and cyno transferrin receptor extracellular domains was evaluated using SPR.

SPR results were obtained using a Biacore 8K+ (Cytiva) with a CM5 sensor chip (Series S, Cytiva) prepared for capture of histidine-tagged ligands according to the manufacturer's protocol (His Capture Kit; Cytiva). Running buffer was 10 mM HEPES, 150 mM NaCl, 3 mM EDTA, 0.05% bovine serum albumin, 0.005% surfactant P20, pH 7.4, flowed at 30 ul/min. For kinetics and affinity determination, recombinant human or cyno monkey TfR1 ECD-His was captured at 15-20 sensor response units (RU) and Fab fragments were serially injected at 0.78, 3.1, 12.5, 50, and 200 nM for 4 min each (in single-cycle kinetics mode) followed by 15 min of buffer flow to monitor dissociation. For Tf competition binding analysis, human or cyno TfR1 ECD-His was captured at 25-40 RU followed by an injection of either buffer or 1 mM holo human transferrin (Sigma T0665) for 4 min, serial 3 min injections of Fabs at 50 and 500 nM with or without 1 mM holo human transferrin, respectively, and dissociation was monitored for 10 min. The capture surface was regenerated after each cycle with 2×1 min injections of 10 mM glycine, pH 1.5. SPR responses, reference subtracted against the signal from sensor surfaces with no TfR1 and against cycles injecting buffer instead of Fab. Kinetics and affinity parameters were determined by fitting the data to a 1:1 binding model using the Biacore Insight Evaluation Software (Cytiva).

TfR1 ECD protein was captured on the SPR sensor surface. Association rates (k_a), dissociation rates (10, and corresponding equilibrium dissociation constants (K_D) were determined from fitting SPR binding responses from serial injections of Fab (at 0.78-200 nM) to a 1:1 binding model. Table 16 shows the affinity and kinetics parameters for each Fab tested.

TABLE 16

Affinity and kinetics parameters for anti-TfR1 antibodies tested

Human TfR1 ECDCyno TfR1 ECD

k_ak_dK_Dk_ak_dK_D

Anti-TfR1 Fab(/M/s)(1/s)(nM)(/M/s)(1/s)(nM)

Rabbit ANTIBODY-A chi Fab1.92E+051.01E−035.23.17E+059.25E−0329

ANTIBODY-A HC-H2C hIgG18.62E+051.03E−031.21.60E+066.74E−034.2

Fab′(1C)/LC-LO hKappa

ANTIBODY-A HC-H2C hIgG17.73E+059.47E−041.26.56E+061.95E−023.0

Fab′(1C)/LC-L1 hKappa

ANTIBODY-A HC-H2C hIgG19.52E+052.13E−032.21.76E+061.37E−027.8

Fab′(1C)/LC-L2 hKappa

ANTIBODY-A HC-H3C hIgG18.35E+051.20E−031.44.10E+061.03E−022.5

Fab′(1C)/LC-LO hKappa

ANTIBODY-A HC-H3C hIgG11.02E+061.26E−031.22.58E+061.06E−024.1

Fab′(1C)/LC-L1 hKappa

ANTIBODY-A HC-H3C hIgG18.86E+052.15E−032.42.16E+061.78E−028.3

Fab′(1C)/LC-L2 hKappa

ANTIBODY-A HC-H4C hIgG18.87E+058.78E−040.991.75E+065.83E−033.3

Fab′(1C)/LC-LO hKappa

ANTIBODY-A HC-H4C hIgG19.83E+058.94E−040.914.40E+061.14E−022.6

Fab′(1C)/LC-L1 hKappa

ANTIBODY-A HC-H4C hIgG19.31E+051.48E−031.62.16E+061.34E−026.2

Fab′(1C)/LC-L2 hKappa

Rabbit ANTIBODY-B chi Fab9.92E+045.73E−045.82.83E+054.36E−041.5

ANTIBODY-B HC-H1 hIgG19.47E+044.53E−0347.88.83E+041.05E−0312

Fab′(1C)/LC-L2 hKappa

ANTIBODY-B HC-H2 hIgG18.32E+043.28E−0339.41.29E+051.13E−038.7

Fab′(1C)/LC-L2 hKappa

ANTIBODY-B HC-H3 hIgG19.15E+045.95E−0365.01.43E+051.72E−0312

Fab′(1C)/LC-L2 hKappa

ANTIBODY-B HC-H4 hIgG11.34E+051.55E−0311.62.28E+055.08E−042.2

Fab′(1C)/LC-L2 hKappa

ANTIBODY-B HC-H0C2.44E+053.43E−0314.12.10E+051.36E−036.5

hIgG1 Fab′(1C)/LC-L2 hKappa

ANTIBODY-B HC-H1C1.71E+051.15E−036.73.15E+054.25E−041.3

hIgG1 Fab′(1C)/LC-L2 hKappa

ANTIBODY-B HC-H2C1.70E+059.99E−045.84.45E+054.72E−041.1

hIgG1 Fab′(1C)/LC-L2 hKappa

ANTIBODY-B HC-H3C2.00E+051.47E−037.43.48E+056.08E−041.7

hIgG1 Fab′(1C)/LC-L2 hKappa

ANTIBODY-B HC-H4C2.23E+057.67E−043.43.98E+052.79E−040.7

hIgG1 Fab′(1C)/LC-L2 hKappa

US11827702B2. Anti-transferrin receptor antibodies and uses thereof (2023-11-28). Biogen MA Inc. [US]. Inventors: Isin Dalkilic-Liddle [US], Benjamin A. Smith [US], Karl J. M. Hanf [US], Fang Qian [US], R. Blake Pepinsky [US], Thomas O. Cameron [US].

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Optimizing Feline IgG1a Binding to FcRn

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Example 5

Several feline IgG1a variants (S252W, L309V, Q311V, S428Y, S428Y+Q311V, S428Y+254R, S428Y+L309V, S428Y+Q311V+T286E, S428Y+Q311V+E380T, S428Y+L309V+T286E, and S428Y+L309V+E380T) were evaluated for binding kinetics to feline FcRn (GenBank KF773786 [feline FcRn large subunit p51] and European Nucleotide Archive AY829266.1 [feline beta-2-microglulin]) at pH 5.9. EU numbering was used to identify the positions (FIG. 4). In this study, the feline Fc variants carrying single amino acid substitutions or a combination of amino acid substitutions were synthesized into the feline IgG1a (Kanai et al., 2000, Vet. Immunol. Immunopathol. 73:53) using the variable domain described by Gearing D P et al. (2016, J Vet Intern Med, 30:1129). The synthesized feline IgGa variant DNAs were subcloned into a mammalian expression vector and transiently transfected into CHO cells. The conditioned media were purified using protein A chromatography.

For the feline FcRn binding experiments, all assays were completed on a Biacore 8K+ system at 25° C. In this set of experiments, antibodies were immobilized using standard amine coupling reagents to Series S C1 sensor chips. A mixture of 200 mmol/L 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide hydrochloride (EDC) and 50 mmol/L N-Hydroxysuccinimide (NHS) was injected for 420 seconds to activate the surface. Then, antibodies were injected at a concentration of 0.5 to 2 μg/ml in 10 mM sodium acetate pH 5.0 for 120 seconds. Finally, 1 M ethanolamine was injected for 420 seconds. The running buffer was 1×PBS-P+(Cytiva, Cat #28995084) adjusted to pH 5.9.

To evaluate the binding affinity of the feline IgG1a variants to feline FcRn at pH 5.9, a range of concentrations from 1.56-2000 nM of feline FcRn were chosen and injected in single cycle mode. The concentrations of feline FcRn tested for each variant are shown below in Table 10.

TABLE 10

Concentrations of feline FcRn used for each feline IgG1a variant

Concentrations of

VariantFcRn [nM]

Wild-type31.25, 125, 500, 2000

FelineIgG1a-S252W1.56, 6.25, 25, 100

FelineIgG1a-L309V31.25, 125, 500, 2000

FelineIgG1a-Q311V31.25, 125, 500, 2000

FelineIgG1a-S428Y7.81, 31.25, 125, 500

FelineIgG1a-S428Y-Q311V7.81, 31.25, 125, 500

FelineIgG1a-S428Y-S254R7.81, 31.25, 125, 500

FelineIgG1a-S428Y-L309V7.81, 31.25, 125, 500

FelineIgG1a-S428Y-Q311V-T286E1.56, 6.25, 25, 100

FelineIgG1a-S428Y-Q311V-E380T1.56, 6.25, 25, 100

FelineIgG1a-S428Y-L309V-T286E1.56, 6.25, 25, 100

FelineIgG1a-S428Y-E308W-E380T1.56, 6.25, 25, 100

Four concentrations per antibody were injected at 5 μl/min for 90 seconds, followed by 180 seconds dissociation. Each concentration series was injected three times in this format, with at least three buffer-only cycles for proper reference subtraction. The surface was regenerated with two injections of 1×PBS-P+, pH 7.4 for 30 seconds, followed by a 60 second wait command. Three startup cycles were included to stabilize the surface prior to analysis.

Data were evaluated using Insight Evaluation Software by fitting to a 1:1 kinetic interaction model, or by fitting to steady state affinity. Quality metrics including the U-value and T-value were used to select the accepted parameters. A U-value of less than 15 was considered acceptable for kinetic rate constants, while a T-value of greater than 100 was considered acceptable for kinetic rate constants. Where these values are outside the range, the steady state affinity parameters are considered acceptable.

The kinetic data for the feline IgG1a variants are shown below in Table 11 and the sensorgrams are shown in FIGS. 49A-49L.

TABLE 11

Feline IgG1a variants and feline FcRn binding kinetics

Variantk_ak_dK_DMethod for fitting data

Wild-type1.06E−06Steady state affinity

FelineIgG1a-S252W1.06E+064.24E−034.01E−091.1 kinetic interaction model

FelineIgG1a-L309V4.27E−07Steady state affinity

FelineIgG1a-Q311V3.34E−07Steady state affinity

FelineIgG1a-S428Y9.02E+056.42E−027.18E−081:1 kinetic interaction model

FelineIgG1a-S428Y-Q311V8.27E+052.66E−023.22E−081:1 kinetic interaction model

FelineIgG1a-S428Y-S254R1.15E+069.31E−028.12E−081:1 kinetic interaction model

FelineIgG1a-S428Y-L309V8.80E+053.10E−023.53E−081:1 kinetic interaction model

FelineIgG1a-S428Y-Q311V-T285E1.27E+067.78E−036.11E−091:1 kinetic interaction model

FelineIgG1a-S428Y-Q311V-E380T1.60E+063.22E−022.01E−081:1 kinetic interaction model

FelineIgG1a-S428Y-L309V-T286E1.34E+067.02E−035.26E−091:1 kinetic interaction model

FelineIgG1a-S428Y-L309V-E380T1.63E+063.34E−022.06E−081:1 kinetic interaction model

US11498953B2. Compositions for increasing half-life of a therapeutic agent in felines and methods of use (2022-11-15). Invetx, Inc. [US]. Inventors: William Brondyk [US], Brett Chevalier [US], Juergen Horn [US], Madhusudan Natarajan [US].

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Engineered Canine IgG Fc Variants Enhance FcRn Binding

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Example 9

Several canine IgGB variants (A426Y, A426Y+T286L, A426Y+D312P, A426Y+Y436H, A426Y+T286L+Y436H, A426H, A426H+T286L, A426H+T286Y, A426H+D312P, A426H+Y436H, and wild-type) were evaluated for binding kinetics to canine FcRn (UniProtKB-E2ROL6 [canine large subunit FcRn] and UniProtKB-E2RN10 [canine beta-2-microglobulin]) at pH 5.9. EU numbering was used to identify the positions (FIG. 28). In this study, the canine Fc variants carrying single amino acid substitutions or a combination of amino acid substitutions were synthesized into the canine IgGB (GENBANK accession number AAL35302.1) format using the variable domain described by Gearing D P et al. (2013, BMC Veterinary Research, 9:226). The synthesized canine IgGB DNAs were subcloned into a mammalian expression vector and transiently transfected into CHO cells. The conditioned media were purified using protein A chromatography.

For the canine FcRn binding experiments, all assays were completed on a Biacore 8K+ system at 25° C. In the above examples (e.g. Examples 6 and 7), we measured the affinity of IgG variants to canine FcRn by amine-coupling of IgGs to a Biacore CM5 biosensor chip which has been demonstrated by Abdiche et al., 2015 (mAbs, 7:331) to underestimate the affinity of Fc variants to FcRn compared to when using a Series S C1 biosensor. In this set of experiments, to obtain a more accurate measurement of FcRn affinity, all antibodies were immobilized using standard amine coupling reagents to Series S C1 sensor chips. A mixture of 200 mmol/L 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide hydrochloride (EDC) and 50 mmol/L N-Hydroxysuccinimide (NETS) was injected for 420 seconds to activate the surface. Then, antibodies were injected at a concentration of 0.5 to 2 μg/ml in 10 mM sodium acetate pH 5.0 for 120 seconds. Finally, 1M ethanolamine was injected for 420 seconds. The running buffer was 1×PBS-P+(Cytiva, Cat #28995084) adjusted to pH 5.9.

To evaluate the binding affinity of the canine IgGB variants to canine FcRn at pH 5.9, a range of concentrations from 1.56-2000 nM of canine FcRn were chosen and injected in single cycle mode. The concentrations of canine FcRn tested for each variant are shown below in Table 20.

TABLE 20

Concentrations of canine FcRn used for each IgGB variant

VariantConcentrations of FcRn [nM]

Wild-type31.25, 125, 500, 2000

A426Y15.625, 62.5, 250, 1000

A426Y + T286L7.8125, 31.25, 125, 500

A426Y + D312P7.8125, 31.25, 125, 500

A426Y + Y436H7.8125, 31.25, 125, 500

A426Y + T286L + Y436H1.56, 6.25, 25, 100

A426H15.625, 62.5, 250, 1000

A426H + T286L3.9, 15.625, 62.5, 250

A426H + T286Y3.9, 15.625, 62.5, 250

A426H + D312P7.8125, 31.25, 125, 500

A426H + Y436H15.625, 62.5, 250, 1000

The kinetic data for the ten variants are shown below in Table 21 and the sensorgrams are shown in FIGS. 30A-30K.

TABLE 21

Canine IgGB variants and canine FcRn binding kinetics

VariantkakdKDMethod for fitting data

Wild-type9.51E−07Steady state affinity

A426Y8.78E+051.13E−011.29E−071:1 kinetic interaction model

A426Y + T286L1.03E+064.36E−024.23E−081:1 kinetic interaction model

A426Y + D312P1.10E+064.97E−024.51E−081:1 kinetic interaction model

A426Y + Y436H1.06E+066.08E−025.77E−081:1 kinetic interaction model

A426Y + T286L + Y436H5.67E+064.12E−027.26E−091:1 kinetic interaction model

A426H1.24E+061.42E−011.15E−071:1 kinetic interaction model

A426H + T286L1.16E+064.17E−023.58E−081:1 kinetic interaction model

A426H + T286Y1.34E+062.86E−022.13E−081:1 kinetic interaction model

A426H + D312P1.31E+065.32E−024.05E−081:1 kinetic interaction model

A426H + Y436H8.08E+051.30E−011.61E−071:1 kinetic interaction model

Example 11

In order to provide insights on the molecular mechanisms of the canine IgGB Fc variants binding to canine FcRn, a structural model of canine IgGB Fc in complex with canine FcRn was created using MOE software (Molecular Operating Environment (MOE), 2020.09; Chemical Computing Group ULC, 1010 Sherbrooke St. West, Suite #910, Montreal, QC, Canada, H3A 2R7, 2020) based on the co-crystal structure of human FcRn in complex with the YTE-Fc domain (PDB ID:4NOU). Mutations were incorporated into the modeled structure in MOE and energy minimized with the Amber14:EHT forcefield. The Canine Fc-FcRn interaction distances were measured using Pymol software (The PyMOL Molecular Graphics System, Version 1.2r3pre, Schrödinger, LLC).

The canine Fc positions of 286, 426 and 436 which have variants that increase the affinity to canine FcRn at low pH are shown in FIG. 34.

The canine IgGB A426H variant is shown in FIG. 35 and position 426 is too distant to directly interact with FcRn. The model predicts that A426H causes a steric clash with Y436 which displaces it into a more favorable conformation for binding FcRn. The canine A426Y is shown in FIG. 36 and similar to A426H, it is too distant to directly interact with FcRn and shifts Y436 into a more favorable conformation for binding to FcRn.

The canine IgGB Y436H variant is shown in FIG. 37. Changing position 436 residue to a His has slight predicted changes to adjacent residues. The difference in charge is likely what is driving the tighter binding. The lack of charge on H436 at neutral pH similar to the hydrophobic/aromatic Y436 is predicted to drive adjacent residues to remain in an unfavorable environment for binding. However, the more hydrophilic/positively charge nature of protonated His436 provides a more attractive interface for residues such as E135 in FcRn large subunit.

The canine IgGB T286L variant is shown in FIG. 38 and is not directly interacting with canine beta-2-microglobulin in FcRn. However, any hydrophobic interactions present would be strengthened by changing a threonine to leucine. The observation is consistent with the increased affinities of T286Y, T286F, and T286W variants to canine FcRn at low pH, as shown in Examples 4 and 5.

The combination of A426Y, Y436H and T286L variants on the canine IgGB Fc has been modeled (FIG. 39). The steric clash between A426Y and Y436H variants is predicted to cause 436 to move into a position more favorable for binding. This is may be additive with the effect of pH dependence of the His. T286L is too far away to appear be directly influenced by 426 and 436 mutations. The in vitro binding data of the triple variant (A426Y, Y436H and T286L) to canine FcRn at low pH in Example 9 is consistent with the model that the combination of the three variants increases the FcRn affinity in an additive manner.

US11434276B2. Polypeptides with altered binding to neonatal Fc receptor (FcRn) and methods of use (2022-09-06). Invetx, Inc. [US]. Inventors: William Brondyk [US], Brett Chevalier [US], Juergen Horn [US], Madhusudan Natarajan [US].

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SPR Analysis of PD-1, RXRα, and Ligand Interactions

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The SPR binding assays were analyzed with Biacore 8K+ (Biacore (Uppsala, Sweden), Cytiva). The materials used in the SPR assays were purchased from Cytiva. PD-1 and RXRα were, respectively, immobilized on a CM5 sensor chip by using standard amine coupling at 25 °C with running buffer HBS-EP (20 mM HEPES buffer, 2.7 mM NaCl, 137 mM KCl, 1 mM EDTA, 0.05% surfactant P20, pH 7.4). The reference flow cell was activated and blocked in the absence of the protein. The immobilization level of PD-1 and RXRα were all about 1500 RU. Different concentrations of PDL1, PPARα, and FXR were serially injected into the channel to evaluate the binding affinity. Then, 5 µM cyc2-1 and cyc2-3 were, respectively, added to each concentration gradient of PDL1, PPARα, and FXR to detect the effect of the peptide on the binding affinities of PD1-PDL1, RXRα-PPARα, and RXRα-FXR.

Qing X., Wang Q., Xu H., Liu P, & Lai L. (2023). Designing Cyclic-Constrained Peptides to Inhibit Human Phosphoglycerate Dehydrogenase. Molecules, 28(17), 6430.

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Structural and Binding Analysis of SARS-CoV-2 Spike Protein

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Samples of Arbidol 1 and derivatives were purchased from ChemDiv, including 1 (1635-0087), 1b (8015-5742) and 1c (H027-0218C) and 1d (H027-0205C). Other compounds were purchased from Selleck Chemicals, including Clofazimine 2 (S4107), Toremifene 3 (S1776), Ecliptasaponin A 4 (S9403) and Ivermectin (S1351). While Toremifene Citrate (S1776) and Ivermectin (S1351) came as a stock solution in 10 mM DMSO, all other purchased compounds were prepared as a standard 10 mM DMSO stock solution from an exact known weight (mg) of each compound. Compound DMSO stock solutions were prepared from the same source of DMSO used in the SPR experiments to minimize observed bulk responses in compound injections.
All SPR experiments were performed at Reaction Biology Corporation (Malvern, PA, USA) using a Biacore 8K+ (Cytiva) instrument with high sensitivity [32 (link)]. For immobilizations, a “series S” and “SA” sensor chips (Cytiva) were used to capture Avi-tag biotinylated protein samples of the SARS-CoV-2 Spike protein. Two biotinylated recombinant samples of the Spike protein were purchased from Acro Biosystems: a full-length trimeric SARS-CoV-2 Spike construct with the D614G mutation (Biotinylated SARS-CoV-2 S protein, catalog number SPN-C82E3) and a trimeric construct of the SARS-CoV-2 S2 segment (Biotinylated SARS-CoV-2 S2 protein, catalog number S2N-C52E8). The experimental design aims to compare a full-length Spike trimer to an equivalent trimeric S2 construct, and the two constructs utilized were the best available equivalents that were biotinylated and resulted in successful immobilizations and subsequent SPR binding experiments. Both constructs incorporate a series of substitutions that stabilize the folded trimeric prefusion conformation. The full-length construct with the D614G mutation (catalog number SPN-C82E3) contains Proline substitutions (F817P, A892P, A899P, A942P, K986P, V987P) to stabilize the trimeric prefusion state and Alanine substitutions (R683A and R685A) to remove the furin cleavage site. The S2 construct (catalog number S2N-C52E8) contains the same series of Proline substitutions (F817P, A892P, A899P, A942P, K986P, V987P) to stabilize the folded trimeric conformation and minimize the formation of misfolded aggregates during protein production. The S2 construct is shown by the vendor to reliably bind a Spike S2 subunit antibody (Human IgG1) by Avitag ELISA assays (Acro Biosystems, 1 Innovation Way, Newark, DE 19711, USA), where the full-length construct (catalog number SPN-C82E3) is shown by the vendor to reliably bind ACE2 and an Anti-Spike RBD neutralizing antibody (Human IgG1) (Cat. No. SAD-S35) by Avitag ELISA. The series of substitutions in both constructs act to stabilize the full-length folded trimer, as well as to stabilize the folded S2 trimer that reliably binds to a Spike S2 subunit antibody. Under our best conditions after immobilization, both constructs were able to demonstrate binding of small molecules, which diminished over time (after two hours) as is often observed for some folded proteins that may become unfolded over time once immobilized on the biosensor surface. Thus, while we do not know for sure if the exact folded structure of the two constructs is the same, SPR evidence from small-molecule binding experiments suggest that the immobilized samples are folded trimers rather than an unfolded immobilized peptide, which may aggregate on a biosensor surface.
Numerous attempts were made to prepare the biosensor surface and optimize the assay conditions to improve the quality of the binding data (See Section 3). The protein samples were immobilized on the SA chips using a 5 (mL/min) flow rate with a running buffer composed of PBS with 0.05% Tween 20, resulting in ranges of 3000–5000 RU. Following immobilization, both the sample surface and the reference channel surface were blocked with biotin to attempt to minimize non-specific binding. In the first round of assay development and initial data collection on the surfaces described above, small-molecule analytes were analyzed using running buffer composed of PBS with 0.05% Tween 20 and either a 1% DMSO or 2% DMSO solutions. Titrations of each analyte were performed using multi-cycle kinetics mode, with 200 mM as the highest concentration for a 2-fold serial dilution of 10 concentrations. In this first round of data collection, serial dilutions were performed on a plate, where the 200 mM concentration was prepared by mixing 10 mM DMSO stock solution with 0% DMSO running buffer to achieve either a 1% or 2% DMSO solution of analyte to match the running buffer.
In a final round of compound characterization using optimized conditions, a new SA chip was prepared, with the aim of facilitating collection of duplicate sensorgrams from two surfaces. Given the high lipophilicity of some of the compounds, rather than performing the dilution on the plate, the serial dilution was performed in DMSO first to avoid solubility issues. Ten concentrations were prepared in DMSO at 50× the concentration used in the assay and then transferred to the plate and mixed with the DMSO-free running buffer to achieve a 2% DMSO solution of analyte to match the 2% DMSO running buffer. Independent duplicates were compared for each compound and two separate concentration series were performed, with starting concentrations of 100 mM and 50 mM, respectively. Titrations of each analyte were performed using multi-cycle kinetics mode. All SPR data were appropriately solvent-corrected [33 (link)], reference-subtracted and analyzed while fitted to a steady-state affinity model using Biacore Insight Evaluation Software.
All molecular docking and free-energy calculations were performed using CHARMM [34 (link)] and the previously described CHARMM-based computational methods established by our laboratory [35 (link),36 (link)]. Molecular docking utilized the LPDB CHARMm force field to model small-molecule potential functions and the resulting protein–ligand interactions [37 (link),38 (link)]. As previously described, a two-step scoring approach was utilized to rank the final TOP5 poses from any docking attempt. For the final TOP5 docking poses, a final energy minimization of the protein–ligand complex was performed using the Generalized Born using Molecular Volume (GBMV) implicit solvent method [39 (link),40 (link)]. Starting from the minimized complex, minimizations of the bound and free state were performed where potential energy components (VDW), (ELEC) and solvation (SOLV) were calculated in order to approximate the free energy of binding (∆G_bind) using a linear interaction energy scoring approach with previously determined empirical generalized parameters [35 (link)]. Results using the predicted (∆G_bind) values for the TOP5 poses of each individual docking “trials” were pooled and sorted by (∆G_bind), and the top-ranked members of a geometric cluster (RMSD < 2.0 Å) were identified. Statistics for (∆G_bind) were calculated from the average and standard deviation from the three top-ranked members of a geometric cluster (RMSD < 2.0 Å) or a triplicate representing the geometric cluster. For all work performed in this study, independent docking “trials” were initiated from 20 generated conformations of a given small-molecule ligand, such that the initial geometry was entirely independent of any CHARMM-based procedure. MarvinSketch version 15.8.31 is a publicly available 3D conformation generator that was used to generate non-identical low-energy conformations [41 ].
Our laboratory had previously used a pharmacophore procedure to identify the most favorable TOP50 binding sites on the SARS-CoV-2 Spike protein S2 segment [19 (link)]. This structural analysis was performed using the 3.2 Å CryoEM structure (6vyb.pdb) of the full-length Spike protein where the ectodomain was in the “closed” state (6vxx.pdb) [42 (link)]. From this model (6vxx.pdb), molecular docking was performed using a hierarchical approach, such that 10 conformations of Clofazimine were initially docked to all 50 sites on the Spike S2 segment. Then, after identification of the TOP5 most favorable sites from this first step, more extensive sampling was used to refine the ranking of the TOP5 sites, and 20 conformations of Clofazimine were docked. Using this model (6vxx.pdb), the consensus binding mode for Cofazimine binding to the SARS-CoV-2 Spike S2 segment (Figure 3B) was used to dock 18 derivatives of Clofazimine [23 (link)]. These derivatives were modeled at five binding sites: Site 1 and Site 2 on the S2 segment as shown in (Figure 3), as well as for the lowest-energy binding sites [19 (link)] in the Nsp5 Main Protease (6w63.pdb) [43 ], Nsp13 Helicase (6jyt.pdb) [44 (link)], and the Nsp16 2′-O methyltransferase (6wkq.pdb) [45 ]. The results for docking the series into the Nsp5 Main Protease and Nsp16 are expected to represent negative controls, where Clofazimine series SAR data would not be expected to show well-modeled binding to these two sites. As our previous work has highlighted, the Nsp5 Main Protease and Nsp16 binding sites in particular [19 (link)] are thermodynamically favorable for the binding of a variety of small-molecule fragment ligands. This makes them more challenging negative control “decoy” binding sites, particularly compared to most of the possible binding sites on the S2 segment, which are less thermodynamically favorable “decoy” binding sites. The physical basis for this is that the specific molecular shape and the hydrophobicity of the Nsp5 and Nsp16 binding sites are favorable for binding hydrophobic small molecules and result in more thermodynamically favorable and more negative (∆G_bind) values when performing virtual screening of a library of compounds. All molecular graphics images of protein structures and molecular interactions were generated with UCSF Chimera [46 (link)].

Freidel M.R., Vakhariya P.A., Sardarni S.K, & Armen R.S. (2024). The Dual-Targeted Fusion Inhibitor Clofazimine Binds to the S2 Segment of the SARS-CoV-2 Spike Protein. Viruses, 16(4), 640.

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