A Biophysical Toolkit for Molecular Interactions


Intermolecular interactions inside and around the cell are key to maintain basic cell homeostasis and to sense and react to external stimuli. Moreover, the action of therapeutics and other xenobiotics occurs through physical interactions of these agents with biomolecules present in the cell or tissue, thereby interfering with the ‘native’ interactions of the biomolecules. Biophysical characterisation of molecular interactions is a bottom‐up reductionist approach that implies measuring the physicochemical properties of the interacting species (two biomacromolecules or a biomacromolecule and a small‐molecule ligand) in order to quantify the binding strength (thermodynamics) and association and dissociation speed (kinetics) between them. A large variety of macroscopic experimental techniques are available and constitute a biophysical toolkit to study molecular interactions in vitro. Among others, isothermal titration calorimetry, surface plasmon resonance, analytical ultracentrifugation, nuclear magnetic resonance, microscale thermophoresis, thermal shift and fluorescence‐based methods are most commonly used.

Key Concepts

  • The strength (affinity) and speed (kinetics) of interactions between biomolecules can be quantified using biophysical experimental methods.
  • Isothermal titration calorimetry (ITC), fluorescence and nuclear magnetic resonance (NMR) spectroscopies, thermal shift assay (TSA), analytical ultracentrifugation (AUC), microscale thermophoresis (MST) and surface plasmon resonance (SPR) are arguably the most used and versatile techniques to study binding in vitro and constitute a biophysical toolkit.
  • Equilibrium affinity constants can be robustly obtained by titration using ITC, fluorescence, NMR, MST, AUC and SPR.
  • Kinetic information can be obtained from time‐resolved fluorescence spectroscopy and SPR methods. The recently developed kinITC method allows obtaining kinetic information from ITC data.
  • Biophysical techniques can tackle the study of a wide range of systems and great progress has been made in the characterisation of interactions taking place at the cell membrane.
  • Basically, all biophysical methods can be automatised to screen for small‐molecule ligands of proteins and other macromolecules, providing starting points for chemical biology and drug discovery.

Keywords: biomolecular interactions; binding affinity; binding kinetics; isothermal titration calorimetry; surface plasmon resonance; analytical ultracentrifugation; nuclear magnetic resonance spectroscopy; microscale thermophoresis; thermal shift assay; fluorescence spectroscopy

Figure 1. ITC study of the human aspartate transcarbamoylase (ATCase) homotrimeric domain of the CAD protein, binding to its CP (carbamoyl phosphate) substrate and the PALA (N‐phosphonacetyl‐l‐aspartate) inhibitor. (a) CP binds exothermically and (b) PALA binds endothermically. Upper panels show the thermograms and lower plots show the binding isotherms (normalised heat per injection as a function of the molar ratio ligand/protein). Nonlinear fitting analysis was performed using three‐site noncooperative (for CP) and cooperative (for PALA) binding models, yielding the indicated intrinsic site‐specific dissociation constants. The substrate CP binds with the same affinity to three independent binding sites while only two of the three active sites show high affinity for the inhibitor PALA (negative cooperativity). Adapted from Ruiz‐Ramos et al. () © Elsevier.
Figure 2. Fluorescence methods to characterise binding affinity and kinetics. (a, b) Titrations of mant‐GTP (guanosine triphosphate) probe (200 nM) with FtsZ protein from Bacillus subtilis using fluorescence intensity and anisotropy, respectively. Lines in each case correspond to the best fit to the data for a 1:1 binding. (c) Chemical structures of small ligands tested in the displacement assay. (d) Displacement curves of mant‐GTP (500 nM) from FtsZ (300 nM binding sites) with unmodified GTP and with these molecules, measured by fluorescence anisotropy. Compounds were checked not to interact with the mant‐GTP probe. The solid lines are best fits to the data according to a single site competition model. (e) Kinetics of binding of mant‐GDP (guanosine diphosphate) (1 μM) to Apo‐FtsZ (10 μM) fitted to a single exponential; the empty symbols are a control measurement of mant‐GDP mixed with buffer. (f) Kinetics of dissociation of mant‐GDP from FtsZ. The mant‐GDP‐FtsZ complex was formed by adding 2 μM Apo‐FtsZ to 1 μM mant‐GDP and at time 0, the solution was mixed 1:1 with 400 μM GTP; the grey line is a control of mant‐GDP alone. Data were fitted to a single exponential. (d–f) Modified from Ruiz‐Avila et al. () and from Huecas et al. () © American Chemical Society.
Figure 3. Differential scanning fluorimetry. (a) Fluorescence intensity versus temperature for protein thermal unfolding in the presence of the fluorescent dye SYPRO orange (represented as an aromatic ring). The fluorescence of the dye (excited by light of 492 nm and represented by green arrows) is quenched in the aqueous buffer where the protein is folded. As the temperature increases, the protein unfolds and its hydrophobic parts (white areas) become solvent exposed, resulting in a strong fluorescence emission at 610 nm (represented by red arrows) by the dye molecules bound to them. Tm is calculated by fitting the experimental data points (circles) to simple equations such as the indicated Boltzmann equation (LL and UL represent, respectively, the lower and upper limits of the dye‐emitted fluorescence intensity and a denotes the slope of the curve within Tm). Adapted from Niesen et al. () © Nature Publishing Group. (b) Stabilisation of His‐PA1 and His‐PTIP proteins upon complex formation measured by nanoDSF. The His‐PA1/His‐PTIP complex has a Kd of 7.1 ± 2.4 nM at 25 °C as measured by ITC. His‐PA1 binding stabilises His‐PTIP by more than 15 °C. The fluorescence intensity ratio at 350 and 330 nm for the individual proteins (note that no thermal transition is observed for isolated His‐PA1) and their complex are fit to a polynomial function to extract the Tm values (upper panel). The lower panel represents the first derivative of the polynomial function and its maximum corresponds to the Tm. Two replicates per sample are overlaid. Adapted from Starnes et al. () © Cold Spring Harbor Laboratory Press.
Figure 4. Sedimentation velocity boundaries collected at 42 000 rpm and 20 °C corresponding to (a) protein p6 dimer (22 kDa), (b) DNA (deoxyribonucleic acid, fragment L 256 base pairs duplex) and (c) the p6–DNA mixture. Absorbance was measured at the selected wavelength (in most of the cases at 255 or 275 nm). (d) The resulting sedimentation coefficient distributions [c(s)] obtained after boundary analysis of protein p6 (dotted line), DNA (dashed line) and p6–DNA mixture (solid line). (e) Sedimentation equilibrium gradients taken at 5000 rpm and 20 °C of protein p6 (black circles), DNA (triangles) and p6–DNA mixture (white circles), equilibrated in 0.05 M NaCl buffer. Continuous lines represent the best‐fit single‐species model that accounts for the experimental data as described in the text. The lower panel shows the best‐fit residuals distribution. (f) Binding isotherms of protein p6 to DNA at low‐salt (black triangles) and high‐salt (white triangles) buffers measured by sedimentation equilibrium. Protein p6 dimer binds noncooperatively to 11 dimer sites within the DNA (the maximal binding capacity is 22 mol of p6 monomer per mole of DNA). The x‐axis corresponds to free protein concentration. Error bars represent ±2SD. Adapted from Alcorlo et al. () © Elsevier.
Figure 5. Microscale thermophoresis determination of protein–peptide binding affinity. (a) Fluorescence time traces for the spindle checkpoint protein complex Bub1(1‐533)‐Bub3 interacting with an MDITp repeat (or pMELT12 peptide), one of the multiple phosphorylated MELT motifs of the outer kinetochore or KNL1 protein, as recorded with a Monolith NT.115 instrument. The concentration of the fluorescently labelled Bub1(1‐533)‐Bub3 (cysteine red labelled) was kept constant at 12.5 nM, and the concentration of the pMELT12 peptide varied from 2.44 nM to 20 μM. MST (microscale thermophoresis) traces at increasing ligand concentrations are colour coded from red to blue. The subsequent processes that affect the recorded fluorescence are labelled from I to V and described in the main text. (b) Binding titrations of two single phosphorylated MELT repeats to fluorescently labelled Bub1(1‐533)/Bub3. pMELT12 shows low micromolar affinity, Kd = 579 ± 133 nM (red circles), while pMELT18 (blue triangles) does not show binding. Lines represent best fits of the data points using the law of mass action (for pMELT12) or the average of experimental data points (for pMELT18). The error bars represent the SD of each data point calculated from three independent thermophoresis experiments (for pMELT12) or the SD of the data points (for pMELT18). Adapted from Zhang et al. () © Nature Publishing Group.
Figure 6. Affinity determination of a small molecule binding telomeric DNA (deoxyribonucleic acid) quadruplexes using receptor‐observed NMR (nuclear magnetic resonance). (a) Representation of the chemical shift changes in the imino region of the 1H NMR spectrum of a telomeric DNA guanine quadruplex model (dTERRA2, a bimolecular symmetric quadruplex, at 33 μM) upon titration with a small‐molecule compound (MW = 322 g mol−1). A–F refer to the six imino signals detected in the 1H NMR spectrum of dTERRA2 and their positions are indicated in the free DNA (lower spectrum) and in the presence of 370 μM compound (upper spectrum). (b) Best nonlinear fits for determination of dissociation constants. Independent fit of three most affected imino signals of dTERRA2 upon compound titration yield Kd values of 130 ± 13 μM (A), 121 ± 20 μM (B) and 111 ± 15 μM (F). Adapted from Garavís et al. () © American Chemical Society.
Figure 7. Binding analysis of protein–DNA interactions using SPR (surface plasmon resonance). (a) SPR sensorgrams (thick traces) of a DNA‐binding protein (BUD) injected at increasing concentrations (0.4, 0.8, 1.6 and 3.2 nM) over its biotin/streptavidin‐immobilised target DNA and determination of Kd from the ratio of kinetic rate constants, obtained from best‐fit (thin lines) kinetic analysis. (b) A different DNA‐binding protein (TALE) binds BUD DNA target with 5000‐fold weaker affinity (Kd = 1 μM, as obtained from best fit of the concentration dependence of steady‐state responses at different concentrations, insert). The BUDs (BUrrH Domains) are highly specific DNA‐binding proteins with a simple amino acid to base code and thus promising tools for genome engineering applications. Adapted from Stella et al. () © International Union of Crystallography.


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Further Reading

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Santiveri, Clara M, López‐Méndez, Blanca, Huecas, Sonia, Alfonso, Carlos, Luque‐Ortega, Juan R, and Campos‐Olivas, Ramón(Jan 2017) A Biophysical Toolkit for Molecular Interactions. In: eLS. John Wiley & Sons Ltd, Chichester. http://www.els.net [doi: 10.1002/9780470015902.a0027015]