This research was supported by a grant from the Binational Science Foundation (BSF) to S.K.S. and N.Q.

NOTE: The recombinant proteins used in this study, Hsp90 and Cdc37, were commercially obtained (see Table of Materials).
1. Chip activation
NOTE: All materials to be used in the experiment are listed in the Table of Materials. Filter all prepared solutions through a sterile 0.2 &#956;m filter.
<ol>
	<li>Prepare 1-Ethyl-3-(3-dimethylamino propyl) carbodiimide (EDC) solution by adding 2 mg of EDC to 2.5 mL of 1 M 2-(N-morpholino) ethane sulfonic acid (MES) buffer (pH = 6.0) in a 15 mL tube. Prepare N-Hydroxysulfosuccinimide (sulfo-NHS) solutions by adding 6 mg of sulfo-NHS to 2.5 mL of 1 M MES buffer (pH = 6.0) in a separate 15 mL tube.&#8239;Aliquot 50 &#181;L of each solution in independent tubes and store at -20 &#176;C for future use.</li>
	<li>Mix equal volumes of EDC sand sulfo-NHS solution (50&#8239;&#181;L of EDC + 50&#8239;&#181;L of sulfo-NHS) by pipetting up and down (do not vortex). 
	NOTE: &#8239;The mixed solution of EDC/sulfo-NHS must be used within 30 min to maintain effective cross-linking for proper chip functionalization.</li>
	<li>Place the biosensor chip (5.7 cm x 2.4 cm; see Table of Materials) supplied by the company in a glass Petri dish with a fitted lid. All the functionalization steps involved in chip activation are suggested to be done within the Petri dish. Apply 50&#8239;&#181;L of 1 M MES buffer (pH = 6.0) to the biosensor chip, incubate for 1 min at room temperature, and then aspirate the buffer.</li>
	<li>Apply 50&#8239;&#181;L&#8239;of EDC/sulfo-NHS solution immediately&#8239;to the sensor chip. Cover the Petri dish and incubate for 15 min&#8239;at room temperature.&#8239; Aspirate EDC/sulfo-NHS solution from the chip.</li>
	<li>Rinse the chip once with 50&#8239;&#181;L of 1 M MES buffer (pH = 6.0); aspirate the MES buffer.</li>
</ol>
2. Target protein immobilization
<ol>
	<li>Rinse the chip 2x with&#8239;50 &#181;L of 1x PBS (pH = 7.4). Aspirate the PBS from the chip and add the&#8239;target molecule, Hsp90 (50&#8239;&#181;L; 500&#8239;nM). 
	NOTE: &#8239;Buffer mismatch may ruin the entire experiment; hence, before the experiment, it is important to make sure that the target molecule is in the same buffer as that used for calibration (e.g.,&#160;1x PBS (pH = 7.4)). If needed, perform a buffer exchange by overnight dialysis before the experiment. In this experiment, overnight dialysis was performed for both recombinant proteins, Hsp90 and Cdc37, against 1x PBS (pH = 7.4; see Table of Materials) with proper buffer exchange at 4 &#176;C. The concentration of the target material (Hsp90 in this case) may vary according to different experimental protocols and the nature of target materials (protein/peptide/ligands).</li>
	<li>Cover the glass Petri dish and incubate for 30 min at room temperature. Aspirate the solution containing the target molecule and rinse 3x with&#8239;50 &#181;L of 1x PBS (pH = 7.4). Aspirate the 1x PBS (pH = 7.4) solution from the chip.</li>
	<li>Add&#8239;50&#8239;&#181;L of Quench 1 (3.9 mM amino-PEG5-alcohol in 1x PBS (pH = 7.4)) solution to the chip.&#8239;Cover the glass Petri dish&#8239;and incubate for 15 min at room temperature. Aspirate the Quench 1 solution from the chip.</li>
	<li>Add&#8239;50&#8239;&#181;L of Quench 2 (1 M ethanolamine (pH = 8.5)) solution to the chip. Cover the glass Petri dish&#8239;and incubate for 15 min at room temperature. Aspirate Quench 2 solution from the chip and rinse the chip 5x using 50 &#181;L of 1x PBS, leaving the last PBS droplet on the sensor.</li>
</ol>
3. Preparing analyte samples
<ol>
	<li>Prepare analyte dilution series for Cdc37 in the desired concentration range. For the first experiment, the following concentrations were used: 25 nM, 50 nM, 100 nM, 200 nM, 400 nM, 800 nM, 1,000 nM, 2,000 nM, 3,000 nM, and 5,000 nM. For the second experiment, a different set of concentrations ranging from 0.4 nM to 200 nM was used.</li>
	<li>Design the experiment to include at least eight different analyte concentrations to obtain a reliable KD value. Prepare the different dilutions of the analyte protein in the same buffer as that used for calibration and target protein; here it is 1x PBS (pH = 7.4).</li>
</ol>
4. Loading of the activated biosensor chip into the FEB device
NOTE: The FEB device consists of a reader featured with LED light indications and a cartridge to insert the biosensor chip.
<ol>
	<li>After target protein immobilization, insert the activated chip into the cartridge of the device, which is connected via USB to a computer. After the chip insertion, a green LED light will be displayed on the reader indicating that the FEB device is ready for the experiment. Install the automated software (see Table of Materials) supplied by the company on the computer, to which the FEB device is connected, to monitor the experiment step by step as described below.</li>
</ol>
5. Run the experiment
<ol>
	<li>Press the Run Experiment module on the automated software and choose 10 Points with Regeneration or any other desired protocol. Fill in the following details:&#8239;operator name, experiment&#8239;name, date (e.g., Yana, Hsp90 + Cdc37, 14.03.2021); regeneration buffer (e.g., PBS buffer); immobilized target (e.g., Hsp90); analyte in solution (e.g., Cdc37). See Supplementary Figure S1 for details.</li>
	<li>Press the Begin the Experiment button displayed on the software and follow the instructions shown by the automated software as described below. 
	NOTE: The software is fully automated, user-friendly, and guides the user throughout the experiment step by step. A pop-up window will appear on the screen with instructions to proceed further at each step of the experiment. The software will provide instructions for each repetitive step consecutively from calibration, analyte association, dissociation, regeneration, and wash (5x) for each analyte concentration throughout the experiment.</li>
	<li>Perform instrument calibration. To do so, aspirate the remaining PBS solution from the chip and apply 50 &#181;L of calibration buffer (1x PBS; pH = 7.4). Press the Continue button and wait for 5 min until the calibration step is finished. The software displays the endpoint determined for the calibration step (5 min) with a warning alarm to follow-up.</li>
	<li>Next, perform an analyte association. To do so, aspirate the calibration buffer from the chip and apply 50 &#181;L of the lowest analyte concentration (25 nM of Cdc37). Press the Continue button and wait for 5 min until the association step is finished. The software displays the endpoint for the association step (5 min) with a warning alarm to proceed.</li>
	<li>Perform an analyte dissociation. To do so, aspirate the analyte solution from the chip and apply 50 &#181;L of the dissociation buffer (1x PBS; pH = 7.4). Press the Continue button and wait for 5 min until the dissociation step duration (5 min) is finished. The software displays the endpoint for the dissociation step (5 min) with a warning alarm to follow-up.</li>
	<li>Next, perform chip regeneration. Aspirate the dissociation solution from the chip and apply 50 &#181;L of regeneration buffer (1x PBS; pH = 7.4). Press the Continue button and wait for 30 s until the regeneration step duration (30 s) is finished. The software displays the endpoint for the regeneration step (30 s) with a warning alarm to follow-up.</li>
	<li>Finally, wash the chip. Aspirate the regeneration solution from the chip and apply 50 &#181;L of wash buffer (1x PBS; pH = 7.4) to the chip. Aspirate the solution from the chip and repeat this 5x. Leave the last drop of wash buffer on the chip and press the Continue button and wait for 30 s until the wash step duration is finished in the software display. 
	&#8203;NOTE: The software displays the endpoint for the wash step (30 s) with a warning alarm to proceed with the next cycle of the experiment.</li>
	<li>Repeat the steps for each analyte concentration used; the five steps of calibration, analyte association, dissociation, regeneration, and wash (5x) constitute one cycle. For the experiment shown here, we performed 10 cycles for 10 analyte concentrations (ranging from 25 nM to 5,000 nM or 0.4 nM to 200 nM; Figure 2).</li>
</ol>
6. Analysis
<ol>
	<li>Press the Analysis button seen at the top of the automated analysis software at the end of the experiment. A display window containing all the experimental points will appear. In the window, ensure that the analyte concentrations used for the prescribed protocol are correct.</li>
	<li>Press the Run Analysis button to generate the KD value automatically. The software generates a Hill fit plot by plotting the analyte concentrations against the corresponding I-Responses from which the dissociation constant at equilibrium, KD value, is calculated.</li>
	<li>Export the raw data for analysis in other statistical analysis software by using the data review/export software as described below.
	<ol>
		<li>Copy the R1R file created automatically at the end of the experiment (e.g.,&#160;Hsp90 + Cdc37 14.03.2021) to a new folder on the desktop. Open the Data Review/Export software supplied by the company (see Supplementary Figure S2A).</li>
		<li>Click on Data Processing &#62; Process R1R files &#62; OK on the home screen of the data review/export software.</li>
		<li>Select the folder containing R1R files created on the desktop in step 6.3.1. and press the OK button. This creates a copy of the original R1R data, to review and edit the data without overriding the original file.</li>
		<li>Press the data processing icon seen at the home screen of the data review/export software. Press Load Processed R1R Files &#62; OK. Select the same folder created in step 6.3.1 containing processed R1R files. Press OK. At this step, the folder containing the experiment files is ready to be reviewed.</li>
		<li>At the home screen of data review/export software, press Data Analysis. Select Calibration &#62; Calibrate edited R1R files &#62; OK (see Supplementary Figure S2B). This step calibrates all the data points according to the first calibration step, to create a baseline.</li>
		<li>At the home screen of data review/export software, press Data Analysis. Select Review and Edit R1R Files &#62; OK. Review the data points, delete points, or add steps by using the Delete/Add Step button. Make sure all the steps are in the correct place, e.g., the calibration step is on the baseline, the association step is at the peak (see Supplementary Figure S3), and then press the Save button to save all the changes made.</li>
		<li>At the home screen of data review/export software, press Data Analysis. Select Analyze/Plot Data, choose the steps to export (see Supplementary Figure S4). Add each association step (e.g.,&#160;step 2, step 7, and so on) after subtracting the calibration step (e.g.,step 1, step 6, and so on) to the export list before exporting the data.</li>
		<li>Press Export this Data. The software generates a spreadsheet file containing the I-Response for each analyte concentration data point from each transistor (if all transistors are working, we will have three different I-response values for each concentration point). Use this spreadsheet file to further analyze the data in the statistical software.</li>
	</ol>
	</li>
	<li>Open the statistical analysis software. Create an XY table with three Y values; press Create. The data for this table (X, Y values) is copied from the spreadsheet file created in step 6.3.8. The x-axis corresponds to analyte concentration (depending on the concentration used), and the three Y values correspond to the I-Responses, obtained from the Data Review/Export software supplied by the company.</li>
	<li>Press Analyze this Data. Choose XY Analyses &#62; Nonlinear Regression (Curve Fit) &#62; Binding Saturation &#62; One Site &#62; Total. The software will automatically analyze the data, generate the KD value, and create a graph of the data points.</li>
</ol>

The authors declare no conflicts of interest, financial or otherwise.

In this study, the feasibility of using the FEB technology (a real-time kinetic characterization approach) was evaluated to determine the biomolecular interaction between Hsp90 and Cdc37. The initial exploratory experiment (first experiment) suggested that choosing the proper analyte concentrations is a critical part of the experiment and that the experiment should be designed by including concentration points above and below the KD value, which were predicted based on the data available in the literature....

Biomolecular interactions: 
Proteins are essential parts of organisms and participate in numerous molecular pathways such as cell metabolism, cell structure, cell signaling, immune responses, cell adhesion, and more. While some proteins perform their function(s) independently, most proteins interact with other proteins using a binding interface to coordinate proper biological activity1.
Biomolecular interactions can mainly be classified based on the distinct structural and functional characteristics of proteins involved2, for example, based on the protein surfaces, the complex stability, or the persistence of interactions3. Identifying essential proteins and their roles in biomolecular interactions is vital for understanding biochemical mechanisms at the molecular level4. Currently, there are various approaches to detect these interactions5:&#160;in vitro6, in silico7, in live cells8,&#160;ex vivo9, and in vivo10&#160;with each having its own strengths and weaknesses.
The in vivo assays are performed using the whole animal as an experimental tool11, and the ex vivo assays are performed on tissue extracts or whole organs (e.g., heart, brain, liver) in a controlled external environment by providing minimal alterations in natural conditions.&#160;The most common application of in vivo and ex vivo studies is to evaluate the pharmacokinetics, pharmacodynamics, and toxicity effects of potential pharmacological agents before human trials by ensuring their overall safety and efficacy12.
Biomolecular interactions can also be detected within living cells. Imaging live cells allow us to observe dynamic interactions as they execute the reactions of a particular biochemical pathway13. Moreover, detection techniques, such as bioluminescence or fluorescence resonance energy transfer, can provide information about where and when these interactions occur within the cell14. Although detection in live cells offers crucial details, these detection methodologies rely on optics and labels, which may not reflect the native biology; they are also less controlled than in vitro methods and require specialized expertise to perform15.
The in silico computational methods are primarily used for large-scale screening of target molecules before the in vitro experiments. Computational prediction methods, computer-based databases, molecular docking, quantitative structure-activity relationships, and other molecular dynamics simulation approaches are among the well-established in silico tools16. Compared to laborious experimental techniques, the in silico tools can easily make predictions with high sensitivity, but with reduced accuracy in predictive performance17.
In vitro assays are performed with microorganisms or biological molecules outside of their standard biological context. Portraying biomolecular interactions through in vitro methods is critical to understanding protein functions and the biology behind the complex network of cell functioning. The preferred assay methodology is chosen according to the protein&#39;s intrinsic properties, kinetic values, and the mode and intensity of interactions18,19.
The Hsp90/Cdc37 interaction: 
The chaperone-kinase pathway, connecting Hsp90 and Cdc37, is a promising therapeutic target in tumor biology20. Hsp90 plays a central role in cell cycle control, protein assembly, cell survival, and signaling pathways. Proteins that rely on Hsp90 for their functions are delivered to Hsp90 for complexation through a co-chaperone, such as Cdc37. The Hsp90/Cdc37 complex controls the folding of most protein kinases and serves as a hub for a multitude of intracellular signaling networks21. It is a promising anti-tumor target due to its elevated expression in various malignancies, including acute myeloblastic leukemia, multiple myeloma, and hepatocellular carcinoma22,23.
Commonly used in vitro biomolecular interaction detection techniques 
Co-immunoprecipitation (co-IP) is a technique relying on antigen-antibody specificity to identify biologically relevant interactions24. The primary disadvantage of this method is its inability to detect low-affinity interactions and kinetic values24. Biophysical methods such as isothermal titration calorimetry (ITC), surface plasmon resonance (SPR), biolayer interferometry (BLI), and FEB technology are preferred to determine the kinetic values.
ITC is a biophysical detection method based on the determination of binding energy along with a complete thermodynamics analysis to characterize biomolecular interactions25. The primary advantage of ITC is that it does not require any labeling or fixation of the target protein. The main difficulties encountered by ITC are the high concentration of target protein required for one experiment and the difficulty in analyzing non-covalent complexes due to small binding enthalpies26. Both SPR and BLI are label-free biophysical techniques that rely on the immobilization of the target molecule on the sensor surface, followed by subsequent injections of the analyte over the immobilized target27,28. In SPR, alterations in the refractive index during biomolecular interactions are measured27; in BLI, the interference in reflected light is recorded in real-time as a change in wavelength as a function of time28. Both SPR and BLI share common advantages of offering high specificity, sensitivity, and detection capabilities29. In both methods, the target protein is immobilized on biosensor surfaces, and hence, there may be some loss of the native conformation of the target, which makes it difficult to discriminate between specific vs. non-specific interactions30. BLI uses expensive disposable fiber-optic biosensors to immobilize the target, and is, therefore, a costly technique31. Compared to these well-established biomolecular detection tools, FEB technology offers a reliable and label-free platform by using low nanomolar concentrations for biomolecular detection in real-time with kinetic characterization. The FEB technology also overcomes the bubbling challenges faced in ITC and is more cost-effective compared to SPR or BLI.
The field-effect transistor (FET) based biosensors is an emerging field for detecting biomolecular interactions by offering varied biomedical applications. In the FET system, targets are immobilized to the biosensor chips and interactions are detected by changes in conductance32. The unique feature to be considered in the development of an efficient electronic biosensor is the physicochemical properties such as the semi-conductive nature and chemical stability of the coating material used to fabricate the sensor surface33. Conventional materials like silicon used for FET have limited the sensitivity of sensors because it requires oxide layers sandwiched between the transistor channel and a specific environment for proper functioning34. Moreover, silicon transistors are sensitive to high salt environments, thus making it hard to measure biological interactions in their natural environment. The graphene-based biosensor is presented as an alternative as it offers excellent chemical stability and electric field. Since graphene is a single atomic layer of carbon, it is both extremely sensitive as a semi-conductor and chemically compatible with biological solutions; both of these qualities are desirable to generate compatible electronic biosensors35. The remarkable ultrahigh loading potential of biomolecules offered by graphene-coated biosensors lead to the development of graphene-based biosensors FEB technology.
Principle of FEB technology: FEB is a label-free biomolecular detection technique that measures the electric current through the graphene biosensor to which the binding targets are immobilized. Interactions between the immobilized protein and the analyte result in alterations in current that are monitored in real-time, enabling accurate kinetic measurements36.
Instrumentation: The FEB system comprises a graphene field-effect transistor (gFET) sensor chip and an electronic reader that applies a constant voltage throughout the experiment (Figure 1). The analyte is applied in solution to the target protein immobilized on the biosensor surface. When an interaction occurs, an alteration in the current is measured and recorded in real-time. As the analyte concentration increases, the fraction of bound analyte will also increase, causing higher alternations in the current. Using the automated analysis software provided with the instrument (Table of Materials), I-Response is measured and recorded in terms of biosensing units (BU)37. I-Response is defined as the alteration in the current (I) through the biosensor chip measured in real-time upon the interaction of the immobilized target with the analyte. The FEB automated analysis software can analyze both the I-Response and C-Response to dynamic interaction events, where the C-Response records the alterations in the capacitance (C). The variations in both the I-Response and C-Response correspond directly to the fraction of bound analyte and can be further analyzed to generate KD values. The automated analysis software&#39;s default preference is I-Response.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/63495/63495fig01.jpg" /> 
Figure 1: Overview of the experimental setup. (A) Graphene-based chip and an electronic reader. (B) An overview of the chip components. The chip is attached to two electrodes that supply current to the system. The surface of the chip is covered with graphene, which when activated can bind the target. <a href="https://www.jove.com/files/ftp_upload/63495/63495fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Methodology: 
Initially, the activated biosensor chip is inserted into the FEB device (Figure 1) followed by the execution of the steps outlined below: (1) Calibration: The experiment starts with system calibration using 1x phosphate-buffered saline (PBS; pH = 7.4) to create the baseline equilibration response. (2) Association: The analyte is introduced in the chip, and the I-Response is monitored until binding saturation is reached. (3) Dissociation: The analyte is dissociated using 1x PBS. (4) Regeneration: Remnants of the analyte are removed using 1x PBS. (5) Washing: A total of five washes are performed using 1x PBS for the thorough removal of the bound and unbound analytes from the chip.
Analysis: 
Data analysis is performed using the fully automated software provided with the instrument. The automated analysis software generates a Hill fit plot with a KD value. The Hill fit plot describes the association of an analyte to the target protein as a function of analyte concentrations. The concentration at which a half-maximal response is achieved is proportional to the KD value. A low KD value represents high binding affinity and vice versa.
To validate the data obtained from the FEB experiment, I-Responses are extracted from each readout point for each analyte concentration using the data review/export software and can be exported to other statistical analysis software (see Table of Materials) as explained below.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Automated analysis software</td>
			<td>Agile plus software, Cardea (Nanomed)</td>
			<td>NA 
			CAS number: NA</td>
			<td>Referred to in the text as the automated analysis software supplied with the instrument. Generates automated analysis.</td>
		</tr>
		<tr>
			<td>COOH-BPU (Biosensing Processing Unit)</td>
			<td>Agile plus software, Cardea (Nanomed)</td>
			<td>NA 
			CAS number: NA</td>
			<td>biosensor chip</td>
		</tr>
		<tr>
			<td>Data review software</td>
			<td>Datalign 1.0, Cardea (Nanomed)</td>
			<td>NA 
			CAS number: NA</td>
			<td>Referred to as the supplied data review software in the text. Supplied with the instrument and allows to review and export the information data points.</td>
		</tr>
		<tr>
			<td>Dialysis bag</td>
			<td>CelluSep,&#160; Membrane filtration products</td>
			<td>T2-10-15 
			CAS number: NA</td>
			<td>T2 tubings (6,000-8,000 MWCO), (10 mm fw, 6.4mm &#216;, 0.32ml/cm, 15m)</td>
		</tr>
		<tr>
			<td>EDC (1-Ethyl-3-(3-dimethylamino propyl) carbodiimide)</td>
			<td>Cardea (Nanomed)</td>
			<td>EDC160322-02 
			CAS number: 25952-53-8</td>
			<td>White powder</td>
		</tr>
		<tr>
			<td>ITC (Isothermal titration calorimetry) system</td>
			<td>Microcal-PEAQ-ITC (Malvern, United Kingdom)</td>
			<td>NA 
			CAS number: NA</td>
			<td></td>
		</tr>
		<tr>
			<td>MES (2-(N-morpholino) ethane sulfonic acid) buffer</td>
			<td>Merck</td>
			<td>M3671-50G 
			CAS number: 4432-31-9</td>
			<td>White powder</td>
		</tr>
		<tr>
			<td>NHS (N-Hydroxysulfosuccinimide) chips</td>
			<td>Cardea (Nanomed)</td>
			<td>NA 
			CAS number: NA</td>
			<td>Graphene-based chip</td>
		</tr>
		<tr>
			<td>PBS (Phosphate-buffered saline) X 10</td>
			<td>Bio-Lab</td>
			<td>001623237500&#160; 
			CAS number: 7758-11-4</td>
			<td>Liquid transparent solution</td>
		</tr>
		<tr>
			<td>Pipete</td>
			<td>Thermo Scientific</td>
			<td>11855231 
			CAS number: NA</td>
			<td>Finnpipette F3 5-50 &#181;L, yellow</td>
		</tr>
		<tr>
			<td>Quench 1 (3.9 mM amino-PEG5-alcohol in 1 X PBS)</td>
			<td>Cardea (Nanomed)</td>
			<td>0105-001-002-001 
			CAS number: NA</td>
			<td>Liquid, transparent solution</td>
		</tr>
		<tr>
			<td>Quench 2 (1 M ethanolamine (pH=8.5))</td>
			<td>Cardea (Nanomed)</td>
			<td>0105-001-003-001 
			CAS number: NA</td>
			<td>Liquid, transparent solution</td>
		</tr>
		<tr>
			<td>Recombinant protein Cdc37</td>
			<td>Abcam</td>
			<td>ab256157 
			CAS number: NA</td>
			<td></td>
		</tr>
		<tr>
			<td>Recombinant protein Hsp90 beta</td>
			<td>Abcam</td>
			<td>ab80033 
			CAS number: NA</td>
			<td></td>
		</tr>
		<tr>
			<td>Spreadsheet</td>
			<td>Excel, Microsoft office</td>
			<td>NA 
			CAS number: NA</td>
			<td></td>
		</tr>
		<tr>
			<td>Statistical software</td>
			<td>GraphPad, Prism</td>
			<td>NA 
			CAS number: NA</td>
			<td>Referred to as the other statistical software. Sigma plot, phyton or other statistical programes may also be used</td>
		</tr>
		<tr>
			<td>Sulfo-NHS</td>
			<td>Cardea (Nanomed)</td>
			<td>NHS160321-07 
			CAS number: 106627-54-7</td>
			<td>White powder</td>
		</tr>
		<tr>
			<td>Tips</td>
			<td>Alex red</td>
			<td>LC 1093-800-000 
			CAS number: NA</td>
			<td>Tip 1-200 &#181;l, in bulk, 1,000 pcs</td>
		</tr>
	</tbody>
</table>

exploring biomolecular interaction between the molecular chaperone hsp90 and its client protein kinase cdc37 using field-effect biosensing technology

Biomolecular interactions play versatile roles in numerous cellular processes&#160;by regulating and coordinating functionally relevant biological events. Biomolecules such as proteins, carbohydrates, vitamins, fatty acids, nucleic acids, and enzymes are fundamental building blocks of living beings; they assemble into complex networks in biosystems to synchronize a myriad of life events. Proteins typically utilize complex interactome networks to carry out their functions; hence it is mandatory to evaluate such interactions to unravel their importance in cells at both cellular and organism levels. Toward this goal, we introduce a rapidly emerging technology, field-effect biosensing (FEB), to determine specific biomolecular interactions. FEB is a benchtop, label-free, and reliable biomolecular detection technique to determine specific interactions and uses high-quality electronic-based biosensors. The FEB technology can monitor interactions in the nanomolar range due to the biocompatible nanomaterials used on its biosensor surface. As a proof of concept, the protein-protein interaction (PPI) between heat shock protein 90 (Hsp90) and cell division cycle 37 (Cdc37) was elucidated. Hsp90 is an ATP-dependent molecular chaperone that plays an essential role in the folding, stability, maturation, and quality control of many proteins, thereby regulating multiple vital cellular functions. Cdc37 is regarded as a protein kinase-specific molecular chaperone, as it specifically recognizes and recruits protein kinases to Hsp90 to regulate their downstream signal transduction pathways. As such, Cdc37 is considered a co-chaperone of Hsp90. The chaperone-kinase pathway (Hsp90/Cdc37 complex) is hyper-activated in multiple malignancies promoting cellular growth; therefore, it is a potential target for cancer therapy. The present study demonstrates the efficiency of FEB technology using the Hsp90/Cdc37 model system. FEB detected a strong PPI between the two proteins (KD values of 0.014 &#181;M, 0.053 &#181;M, and 0.072 &#181;M in three independent experiments). In summary, FEB is a label-free and cost-effective PPI detection platform, which offers fast and accurate measurements.

Results from experiment 1: 
The target protein Hsp90 (500 nM) was immobilized to the chip following the target immobilization protocol as described above. For the first experiment, 10 concentrations of the analyte protein, Cdc37, ranging from 25 nM to 5,000 nM, were prepared based on the data available in the literature (see Table 1).
The steps of the experiment can be monitored in real-time by following the alterations occurring in the I-Response (<stron...

Watch this Scientific Journal Video about Exploring Biomolecular Interaction Between the Molecular Chaperone Hsp90 and Its Client Protein Kinase Cdc37 using Field-Effect Biosensing Technology at JoVE.

Exploring Biomolecular Interaction Between the Molecular Chaperone Hsp90 and Its Client Protein Kinase Cdc37 using Field-Effect Biosensing Technology

Field-effect biosensing (FEB) is a label-free technique for detecting biomolecular interactions. It measures the electric current through the graphene biosensor to which the binding targets are immobilized. The FEB technology was used to evaluate biomolecular interactions between Hsp90 and Cdc37 and a strong interaction between the two proteins was detected.

Biomolecular interactions play versatile roles in numerous cellular processes&#160;by regulating and coordinating functionally relevant biological events. ...

exploring-biomolecular-interaction-between-molecular-chaperone-hsp90

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Biochemistry

3.1K Views.  Bar-Ilan University. Field-effect biosensing (FEB) is a label-free technique for detecting biomolecular interactions. It measures the electric current through the graphene biosensor to which the binding targets are immobilized. The FEB technology was used to evaluate biomolecular interactions between Hsp90 and Cdc37 and a strong interaction between the two proteins was detected.

Video: Exploring Biomolecular Interaction Between the Molecular Chaperone Hsp90 and Its Client Protein Kinase Cdc37 using Field-Effect Biosensing Technology

Method for Identifying Small Molecule Inhibitors of the Protein-protein Interaction Between HCN1 and TRIP8b

Hyperpolarization-activated cyclic nucleotide-gated (HCN) channels are expressed ubiquitously throughout the brain, where they function to regulate the excitability of neurons. The subcellular distribution of these channels in pyramidal neurons of hippocampal area CA1 is regulated by tetratricopeptide repeat-containing Rab8b interacting protein (TRIP8b), an auxiliary subunit. Genetic knockout of HCN pore forming subunits or TRIP8b, both lead to an increase in antidepressant-like behavior, suggesting that limiting the function of HCN channels may be useful as a treatment for Major Depressive Disorder (MDD). Despite significant therapeutic interest, HCN channels are also expressed in the heart, where they regulate rhythmicity. To circumvent off-target issues associated with blocking cardiac HCN channels, our lab has recently proposed targeting the protein-protein interaction between HCN and TRIP8b in order to specifically disrupt HCN channel function in the brain. TRIP8b binds to HCN pore forming subunits at two distinct interaction sites, although here the focus is on the interaction between the tetratricopeptide repeat (TPR) domains of TRIP8b and the C terminal tail of HCN1. In this protocol, an expanded description of a method for purifying TRIP8b and executing a high throughput screen to identify small molecule inhibitors of the interaction between HCN and TRIP8b, is described. The method for high throughput screening utilizes a Fluorescence Polarization (FP) -based assay to monitor the binding of a large TRIP8b fragment to a fluorophore-tagged eleven amino acid peptide corresponding to the HCN1 C terminal tail. This method allows &#39;hit&#39; compounds to be identified based on the change in the polarization of emitted light. Validation assays are then performed to ensure that &#39;hit&#39; compounds are not artifactual.

The interaction between HCN channels and their auxiliary subunit has been identified as a therapeutic target in Major Depressive Disorder. Here, a fluorescence polarization-based method for identifying small molecule inhibitors of this protein-protein interaction, is presented.

Hyperpolarization-activated cyclic nucleotide-gated (HCN) channels are expressed ubiquitously throughout the brain, where they function to regulate the ...

Assaying Protein Kinase Activity with Radiolabeled ATP

Protein kinases are able to govern large-scale cellular changes in response to complex arrays of stimuli, and much effort has been directed at uncovering allosteric details of their regulation. Kinases comprise signaling networks whose defects are often hallmarks of multiple forms of cancer and related diseases, making an assay platform amenable to manipulation of upstream regulatory factors and validation of reaction requirements critical in the search for improved therapeutics. Here, we describe a basic kinase assay that can be easily adapted to suit specific experimental questions including but not limited to testing the effects of biochemical and pharmacological agents, genetic manipulations such as mutation and deletion, as well as cell culture conditions and treatments to probe cell signaling mechanisms. This assay utilizes radiolabeled [&#947;-32P] ATP, which allows for quantitative comparisons and clear visualization of results, and can be modified for use with immunoprecipitated or recombinant kinase, specific or typified substrates, all over a wide range of reaction conditions.

Protein kinases are highly evolved signaling enzymes and scaffolds that are critical for inter- and intracellular signal transduction. We present a protocol for measuring kinase activity through the use of radiolabeled adenosine triphosphate ([&#947;-32P] ATP), a reliable method to aid in elucidation of cellular signaling regulation.

Protein kinases are able to govern large-scale cellular changes in response to complex arrays of stimuli, and much effort has been directed at uncovering ...

Human Peripheral Blood Neutrophil Isolation for Interrogating the Parkinson's Associated LRRK2 Kinase Pathway by Assessing Rab10 Phosphorylation

The leucine rich repeat kinase 2 (LRRK2) is the most frequently mutated gene in hereditary Parkinson&#8217; disease (PD) and all pathogenic LRRK2 mutations result in hyperactivation of its kinase function. Here, we describe an easy and robust assay to quantify LRRK2 kinase pathway activity in human peripheral blood neutrophils by measuring LRRK2-controlled phosphorylation of one of its physiological substrates, Rab10 at threonine 73. The immunoblotting analysis described requires a fully selective and phosphospecific antibody that recognizes the Rab10 Thr73 epitope phosphorylated by LRRK2, such as the MJFF-pRab10 rabbit monoclonal antibody. It uses human peripheral blood neutrophils, because peripheral blood is easily accessible and neutrophils are an abundant and homogenous constituent. Importantly, neutrophils express relatively high levels of both LRRK2 and Rab10. A potential drawback of neutrophils is their high intrinsic serine protease activity, which necessitates the use of very potent protease inhibitors such as the organophosphorus neurotoxin diisopropylfluorophosphate (DIFP) as part of the lysis buffer. Nevertheless, neutrophils are a valuable resource for research into LRRK2 kinase pathway activity in vivo and should be considered for inclusion into PD biorepository collections.

Mutations in the leucine rich repeat kinase 2 gene (LRRK2) cause hereditary Parkinson&#8217;s disease. We have developed an easy and robust method for assessing LRRK2-controlled phosphorylation of Rab10 in human peripheral blood neutrophils. This may help identify individuals with increased LRRK2 kinase pathway activity.

The leucine rich repeat kinase 2 (LRRK2) is the most frequently mutated gene in hereditary Parkinson&#8217; disease (PD) and all pathogenic LRRK2 ...

Identification of Novel CK2 Kinase Substrates Using a Versatile Biochemical Approach

The study of kinase-substrate relationships is essential to gain a complete understanding of the functions of these enzymes and their downstream targets in both physiological and pathological states. CK2 is an evolutionarily conserved serine/threonine kinase with a growing list of hundreds of substrates involved in multiple cellular processes. Due to its pleiotropic properties, identifying and characterizing a comprehensive set of CK2 substrates has been particularly challenging and remains a hurdle in the study of this important enzyme. To address this challenge, we have devised a versatile experimental strategy that enables the targeted enrichment and identification of putative CK2 substrates. This protocol takes advantage of the unique dual co-substrate specificity of CK2 allowing for specific thiophosphorylation of its substrates in a cell or tissue lysate. These substrate proteins are subsequently alkylated, immunoprecipitated, and identified by liquid chromatography/tandem mass spectrometry (LC-MS/MS). We have previously used this approach to successfully identify CK2 substrates from Drosophila ovaries and here we extend the application of this protocol to human glioblastoma cells, illustrating the adaptability of this method to investigate the biological roles of this kinase in various model organisms and experimental systems.

The objective of this protocol is to label, enrich, and identify substrates of protein kinase CK2 from a complex biological sample such as a cell lysate or tissue homogenate. This method leverages unique aspects of CK2 biology for this purpose.

The study of kinase-substrate relationships is essential to gain a complete understanding of the functions of these enzymes and their downstream targets ...

Studying RNA Interactors of Protein Kinase RNA-Activated during the Mammalian Cell Cycle

Protein kinase RNA-activated (PKR) is a member of the innate immune response proteins and recognizes the double-stranded secondary structure of viral RNAs. When bound to viral double-stranded RNAs (dsRNAs), PKR undergoes dimerization and subsequent autophosphorylation. Phosphorylated PKR (pPKR) becomes active and induces phosphorylation of the alpha subunit of eukaryotic initiation factor 2 (eIF2&#945;) to suppress global translation. Increasing evidence suggests that PKR can be activated under physiological conditions such as during the cell cycle or under various stress conditions without infection. However, our understanding of the RNA activators of PKR is limited due to the lack of a standardized experimental method to capture and analyze PKR-interacting dsRNAs. Here, we present an experimental protocol to specifically enrich and analyze PKR bound RNAs during the cell cycle using HeLa cells. We utilize the efficient crosslinking activity of formaldehyde to fix PKR-RNA complexes and isolate them via immunoprecipitation. PKR co-immunoprecipitated RNAs can then be further processed to generate a high-throughput sequencing library. One major class of PKR-interacting cellular dsRNAs is mitochondrial RNAs (mtRNAs), which can exist as intermolecular dsRNAs through complementary interaction between the heavy-strand and the light-strand RNAs. To study the strandedness of these duplex mtRNAs, we also present a protocol for strand-specific qRT-PCR. Our protocol is optimized for the analysis of PKR-bound RNAs, but it can be easily modified to study cellular dsRNAs or RNA-interactors of other dsRNA binding proteins.

We present experimental approaches for studying RNA-interactors of double-stranded RNA binding protein kinase RNA-activated (PKR) during the mammalian cell cycle using HeLa cells. This method utilizes formaldehyde to crosslink RNA-PKR complexes and immunoprecipitation to enrich PKR-bound RNAs. These RNAs can be further analyzed through high-throughput sequencing or qRT-PCR.

Protein kinase RNA-activated (PKR) is a member of the innate immune response proteins and recognizes the double-stranded secondary structure of viral ...

Characterization at the Molecular Level using Robust Biochemical Approaches of a New Kinase Protein

Extensive whole genome sequencing has identified many Open Reading Frames (ORFs) providing many potential proteins. These proteins may have important roles for the cell and may unravel new cellular processes. Among proteins, kinases are major actors as they belong to cell signaling pathways and have the ability to switch on or off many processes crucial to the fate of the cell, such as cell growth, division, differentiation, motility, and death.
In this study, we focused on a new potential kinase protein, LIMK2-1. We demonstrated its existence by Western Blot using a specific antibody. We evaluated its interaction with an upstream regulating protein using coimmunoprecipitation experiments. Coimmunoprecipitation is a very powerful technique able to detect the interaction between two target proteins. It may also be used to detect new partners of a bait protein. The bait protein may be purified either via a tag engineered to its sequence or via an antibody specifically targeting it. These protein complexes may then be separated by SDS-PAGE (Sodium Dodecyl Sulfate PolyAcrylamide Gel) and identified using mass spectrometry. Immunoprecipitated LIMK2-1 was also used to test its kinase activity in vitro by &#947;[32P] ATP labeling. This well-established assay may use many different substrates, and mutated versions of the bait may be used to assess the role of specific residues. The effects of pharmacological agents may also be evaluated since this technique is both highly sensitive and quantitative. Nonetheless, radioactivity handling requires particular caution. Kinase activity may also be assessed with specific antibodies targeting the phospho group of the modified amino acid. These kinds of antibodies are not commercially available for all the phospho modified residues.

We characterized a new kinase protein using robust biochemical approaches: Western Blot analysis with a dedicated specific antibody on different cell lines and tissues, interactions by coimmunoprecipitation experiments, kinase activity detected by Western Blot using a phospho-specific antibody and by &#947;[32P] ATP labeling.

Extensive whole genome sequencing has identified many Open Reading Frames (ORFs) providing many potential proteins. These proteins may have important ...

Kinase Inhibitor Screening In Self-assembled Human Protein Microarrays

The screening of kinase inhibitors is crucial for better understanding properties of a drug and for the identification of potentially new targets with clinical implications. Several methodologies have been reported to accomplish such screening. However, each has its own limitations (e.g., the screening of only ATP analogues, restriction to using purified kinase domains, significant costs associated with testing more than a few kinases at a time, and lack of flexibility in screening protein kinases with novel mutations). Here, a new protocol that overcomes some of these limitations and can be used for the unbiased screening of kinase inhibitors is presented. A strength of this method is its ability to compare the activity of kinase inhibitors across multiple proteins, either between different kinases or different variants of the same kinase. Self-assembled protein microarrays generated through the expression of protein kinases by a human-based in vitro transcription and translation system (IVTT) are employed. The proteins displayed on the microarray are active, allowing for measurement of the effects of kinase inhibitors. The following procedure describes the protocol steps in detail, from the microarray generation and screening to the data analysis.

A detailed protocol for the generation of self-assembled human protein microarrays for the screening of kinase inhibitors is presented.

The screening of kinase inhibitors is crucial for better understanding properties of a drug and for the identification of potentially new targets with ...

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation

Dynamic protein-protein interactions control cellular behavior, from motility to DNA replication to signal transduction. However, monitoring dynamic interactions among multiple proteins in a protein interaction network is technically difficult. Here, we present a protocol for Quantitative Multiplex Immunoprecipitation (QMI), which allows quantitative assessment of fold changes in protein interactions based on relative fluorescence measurements of Proteins in Shared Complexes detected by Exposed Surface epitopes (PiSCES). In QMI, protein complexes from cell lysates are immunoprecipitated onto microspheres, and then probed with a labeled antibody for a different protein in order to quantify the abundance of PiSCES. Immunoprecipitation antibodies are conjugated to different MagBead spectral regions, which allows a flow cytometer to differentiate multiple parallel immunoprecipitations and simultaneously quantify the amount of probe antibody associated with each. QMI does not require genetic tagging and can be performed using minimal biomaterial compared to other immunoprecipitation methods. QMI can be adapted for any defined group of interacting proteins, and has thus far been used to characterize signaling networks in T cells and neuronal glutamate synapses. Results have led to new hypothesis generation with potential diagnostic and therapeutic applications. This protocol includes instructions to perform QMI, from the initial antibody panel selection through to running assays and analyzing data. The initial assembly of a QMI assay involves screening antibodies to generate a panel, and empirically determining an appropriate lysis buffer. The subsequent reagent preparation includes covalently coupling immunoprecipitation antibodies to MagBeads, and biotinylating probe antibodies so they can be labeled by a streptavidin-conjugated fluorophore. To run the assay, lysate is mixed with MagBeads overnight, and then beads are divided and incubated with different probe antibodies, and then a fluorophore label, and read by flow cytometry. Two statistical tests are performed to identify PiSCES that differ significantly between experimental conditions, and results are visualized using heatmaps or node-edge diagrams.

Quantitative Multiplex Immunoprecipitation (QMI) uses flow cytometry for sensitive detection of differences in the abundance of targeted protein-protein interactions between two samples. QMI can be performed using a small amount of biomaterial, does not require genetically engineered tags, and can be adapted for any previously defined protein interaction network.

Dynamic protein-protein interactions control cellular behavior, from motility to DNA replication to signal transduction. However, monitoring dynamic ...

Monitoring Protein-RNA Interaction Dynamics In Vivo at High Temporal Resolution Using &#967;CRAC

The interaction between RNA-binding proteins (RBPs) and their RNA substrates exhibits fluidity and complexity. Within its lifespan, a single RNA can be bound by many different RBPs that will regulate its production, stability, activity, and degradation. As such, much has been done to understand the dynamics that exist between these two types of molecules. A particularly important breakthrough came with the emergence of &#8216;cross-linking and immunoprecipitation&#8217; (CLIP). This technique allowed stringent investigation into which RNAs are bound by a particular RBP. In short, the protein of interest is UV cross-linked to its RNA substrates in vivo, purified under highly stringent conditions, and then the RNAs covalently cross-linked to the protein are converted into cDNA libraries and sequenced. Since its conception, many derivative techniques have been developed in order to make CLIP amenable to particular fields of study. However, cross-linking using ultraviolet light is notoriously inefficient. This results in extended exposure times that make the temporal study of RBP-RNA interactions impossible. To overcome this issue, we recently designed and built much-improved UV irradiation and cell harvesting devices. Using these new tools, we developed a protocol for time-resolved analyses of RBP-RNA interactions in living cells at high temporal resolution: Kinetic CRoss-linking and Analysis of cDNAs (&#967;CRAC). We recently used this technique to study the role of yeast RBPs in nutrient stress adaptation. This manuscript provides a detailed overview of the &#967;CRAC method and presents recent results obtained with the Nrd1 RBP.

Kinetic cross-linking and analysis of cDNA is a method that allows investigation of the dynamics of protein-RNA interactions in living cells at high temporal resolution. Here the protocol is described in detail, including the growth of yeast cells, UV cross-linking, harvesting, protein purification, and next generation sequencing library preparation steps.

The interaction between RNA-binding proteins (RBPs) and their RNA substrates exhibits fluidity and complexity. Within its lifespan, a single RNA can be ...

Studies of Chaperone-Cochaperone Interactions using Homogenous Bead-Based Assay

Targeting the heat shock protein 90 (Hsp90)-cochaperone interactions provides the possibility to specifically regulate Hsp90-dependent intracellular processes. The conserved MEEVD pentapeptide at the C-terminus of Hsp90 is responsible for the interaction with the tetratricopeptide repeat (TPR) motif of co-chaperones. FK506-binding protein (FKBP) 51 and FKBP52 are two similar TPR-motif co-chaperones involved in steroid hormone-dependent diseases with different functions. Therefore, identifying molecules specifically blocking interactions between Hsp90 and FKBP51 or FKBP52 provides a promising therapeutic potential for several human diseases. Here, we describe the protocol for an amplified luminescent proximity homogenous assay to probe interactions between Hsp90 and its partner co-chaperones FKBP51 and FKBP52. First, we have purified the TPR motif-containing proteins FKBP51 and FKBP52 in glutathione S-transferase (GST)-tagged form. Using the glutathione-linked donor beads with GST-fused TPR-motif proteins and the acceptor beads coupled with a 10-mer C-terminal peptide of Hsp90, we have probed protein-protein interactions in a homogeneous environment. We have used this assay to screen small molecules to disrupt Hsp90-FKBP51 or Hsp90-FKBP52 interactions and identified potent and selective Hsp90-FKBP51 interaction inhibitors.

This protocol presents a technique for probing protein-protein interactions using glutathione-linked donor beads with GST-fused TPR-motif co-chaperones and acceptor beads coupled with an Hsp90-derived peptide. We have used this technique to screen small molecules to disrupt Hsp90-FKBP51 or Hsp90-FKBP52 interactions and identified potent and selective Hsp90-FKBP51 interaction inhibitors.

Targeting the heat shock protein 90 (Hsp90)-cochaperone interactions provides the possibility to specifically regulate Hsp90-dependent intracellular ...