User Guide Measuring Protein-Binding Affinities with Fluidity One-W Systems Published on September 6th, 2021 This workflow and its products described here are for research use only and is not to be used for any other purposes, including, but not limited to, in vitro diagnostics, clinical diagnostics, or use in humans. The document and its content are proprietary to Fluidic Analytics and is intended for use only in connection with the products described herein and for no other purposes. DOWNLOAD USER GUIDE 1. About this Getting Started Guide This “Getting Started Guide” provides generic guidance for users who want to characterize protein interactions by generating affinity binding curves with their proteins of choice. The guide provides a generic protocol to be used on Fluidity One-W systems that can be easily adapted for any protein and includes helpful tips and tricks to successfully analyze protein interactions. 2. Protein-protein interactions Proteins play critical roles in the human body, maintaining and regulating the structure and function of tissues and organs. Ultimately, proteins are responsible for nearly every task of cellular life. To deliver this task, more than 75% of proteins interact with at least one other. Understanding these interactions on a quantitative level is therefore essential to predict biological function, understand the effects of the disruption of normal cellular functions in human disease and subsequently help develop and optimize successful vaccines, drugs and treatments. 2.1 Why measure binding affinity? While the identification of protein interactions is certainly important, understanding how strong these interactions are and how they impact biological function can be even more critical. Researchers therefore typically measure binding affinity to develop a more comprehensive understanding of the intermolecular interactions that drive biological processes and cellular pathways. Determination of binding affinities is also important to researchers studying structural biology and structure-function relationships. In addition, understanding affinity and determining whether candidate drugs bind their target with high selectivity and specificity is crucial in the drug development process to guide the selection of drug candidates for further investigation. Measuring binding affinity is of importance when: Investigating antigen/antibody interactions Characterizing binding epitopes Evaluating and ranking drug candidates Characterizing protein complexes Assessing the effect of buffers and other biological solutions on affinity 2.2 The dissociation constant (KD) quantifies binding affinity Binding affinity is a measure of how tightly two molecules bind to each other and is typically reported by the equilibrium dissociation constant (KD). The smaller the KD value, the greater the strength with which the two binding partners bind to each other and vice versa. This “Getting Started Guide” describes how to determine binding affinities of two generic proteins on Fluidity One-W systems by measuring the protein-complex formation A + B <> AB and determining the KD value in which [A]eq and [B]eq are the equilibrium concentrations of the unbound proteins A and B and [AB]eq is the equilibrium concentration of the protein complex. 3. Measuring binding affinity on Fluidity One-W systems The Fluidity One-W systems are microfluidic devices that measure changes in hydrodynamic radius (Rh) directly in solution using microfluidic diffusional sizing (MDS). MDS exploits the well understood relationship between molecule size and diffusion rate to enable absolute size measurements. If two proteins bind to each other, the absolute size of the complex is larger than the size of the individual binding partners, which is what is being detected by MDS. In practice, Fluidity One-W systems measure the size increase of a fluorescently labeled probe protein when it binds to an unlabeled target protein. Thus, by mixing a constant concentration of fluorescently labeled probe with the unlabeled target at increasing concentrations, an equilibrium binding curve will be generated (Figure 1). From the binding curve, a KD value can be obtained using non-linear least squares fitting to the following equation Here, Rh is the measured Rh value, Rh,unbound is the Rh of the unbound labeled probe, Rh,complex is the Rh of the complex, and [A] and [B] are the total concentrations of labeled probe and unlabeled target, respectively. Figure 1: General features of an equilibrium binding curve measured by Fluidity One-W systems. In this example, the fluorescently labeled probe (protein A) in the unbound form displays an Rh of 3 nm whereas the AB complex shows an Rh of 6 nm. Each of the 12 data points has a constant concentration of fluorescently labeled probe of 10 nM and various concentrations of unlabeled target. The KD value can be deduced from the equilibrium binding curve by non-linear least squares fit. The Fluidity One-W systems will provide KD values as well as a fitted binding curve automatically once data acquisition is complete. Visually, the KD can be estimated from the inflection point of the binding curve. As measurements on Fluidity One-W systems are performed in-solution, the data obtained from these protein–target interaction assays are representative of a near-native state. Fluidic Analytic’s technology can analyze proteins in simple aqueous buffers (Fluidity One-W) as well as in complex biological backgrounds such as cell lysates or plasma (Fluidity One-W Serum). 4. Equilibrium binding affinity measurements to determine the KD value of bimolecular protein–protein interactions – overview Performing equilibrium binding experiments that yield an accurate KD value requires upfront knowledge of the approximate KD. In many cases this information might not be available and therefore requires a range-finding experiment to identify the concentrations of fluorescently labeled probe and unlabeled target required to ensure that both a pre-transition and a post-transition plateau are well defined in the binding curve. 4.1 Range-finding experiment Range-finding experiments can be carried out with a limited number of data points to save time and material. The experiments should cover at least three orders of magnitude in concentration of the unlabeled target. The concentration of the labeled probe should be kept as low as possible. This ensures that the binding curve covers both the pre-transition baseline as well as the post-transition plateau, both of which are required for accurate KD determination. Figure 2: Identifying the correct concentration range for the titration of unlabeled target B. If the KD is unknown it is best to choose a low concentration of fluorescently labeled probe and test a wide range of concentrations of target to ensure the binding curve covers both the pre-transition baseline as well as the post-transition plateau, both of which are required for accurate KD determination. For A) the concentration range of the target that is covered is too low, for B) the concentration range is ideal, for C) the concentration range that is covered is too high. Both too low and too high concentration ranges of the target will result in an inaccurate KD values. In addition to finding optimal probe and target concentrations, the range finding experiment can also be used to ensure that the binding reaction is fully equilibrated. If equilibrium is established, the first series of measurements should fall in line with the results of the second series and the two curves of the repeat runs will overlap. 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