Name: exploring biomolecular interaction between the molecular chaperone hsp90 and its client protein kinase cdc37 using field-effect biosensing technology
Uploaded: 2022-03-31T13:40:00
Description: 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.

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-...

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. ...

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