Analysis of multitemperature isothermal titration calorimetry data at very low c: Global beats van't Hoff

Combating DC-SIGN-mediated SARS-CoV-2 dissemination by glycan-mimicking polymers

Many viruses exploit the human C-type lectin receptor dendritic cell-specific ICAM-3 grabbing nonintegrin (DC-SIGN) for cell entry and virus dissemination. An inhibition of DC-SIGN-mediated virus attachment by glycan-derived ligands has, thus, emerged as a promising strategy toward broad-spectrum antiviral therapeutics. In this contribution, several cognate fragments of oligomannose- and complex-type glycans grafted onto a poly-l-lysine scaffold are evaluated as polyvalent DC-SIGN ligands. The range of selected carbohydrate epitopes encompasses linear (α- d-Man-(1→2)-α- d-Man, α- d-Man-(1→2)-α- d-Man-(1→2)-α- d-Man-(1→3)-α- d-Man) and branched (α- d-Man-(1→6)-[α- d-Man-(1→3)]-α- d-Man) oligomannosides, as well as α- l-Fuc. The thermodynamics of binding are investigated on a mono- and multivalent level to shed light on the molecular details of the interactions with the tetravalent receptor. Cellular models of virus attachment and DC-SIGN-mediated virus dissemination reveal a high potency of the presented glycopolymers in the low pico- and nanomolar ranges, respectively. The high activity of oligomannose epitopes in combination with the biocompatible properties of the poly- l-lysine scaffold highlights the potential for further preclinical development of polyvalent DC-SIGN ligands.

Applications of isothermal titration calorimetry in pure and applied research from 2016 to 2020

The last 5 years have seen a series of advances in the application of isothermal titration microcalorimetry (ITC) and interpretation of ITC data. ITC has played an invaluable role in understanding multiprotein complex formation including proteolysis-targeting chimeras (PROTACS), and mitochondrial autophagy receptor Nix interaction with LC3 and GABARAP. It has also helped elucidate complex allosteric communication in protein complexes like trp RNA-binding attenuation protein (TRAP) complex. Advances in kinetics analysis have enabled the calculation of kinetic rate constants from pre-existing ITC data sets. Diverse strategies have also been developed to study enzyme kinetics and enzyme-inhibitor interactions. ITC has also been applied to study small molecule solvent and solute interactions involved in extraction, separation, and purification applications including liquid-liquid separation and extractive distillation. Diverse applications of ITC have been developed from the analysis of protein instability at different temperatures, determination of enzyme kinetics in suspensions of living cells to the adsorption of uremic toxins from aqueous streams.

Isothermal titration calorimetry (ITC): a standard operating procedure (SOP)

Isothermal titration calorimetry (ITC) is currently widely used in many applied areas of research, spanning protein-ligand binding, metal-ligand interactions, DNA/DNA or protein/DNA interactions, partition to membranes, and polymer surfactant interactions, to mention just a few. This is due to the availability of commercial instruments, and thus the production and spread of an accepted and widely followed SOP is felt by most users, in an effort to produce results that are scientifically correct and comparable. Therefore, within the efforts of Working Group 4 of the ARBRE-MOBIEU COST Action (CA15126), this ITC SOP was generated, alongside SOPs for several other biophysical techniques. Here, we discuss the factors that are fundamental for good experimental design and that need to be carefully considered, as well as machine calibration, in particular chemical calibration, linked to another outcome of Working Group 4 on ITC benchmarking, to be also published in this Special Issue.

Estimation of non-constant variance in isothermal titration calorimetry using an ITC measurement model

Isothermal titration calorimetry (ITC) is the gold standard for accurate measurement of thermodynamic parameters in solution reactions. In the data processing of ITC, the non-constant variance of the heat requires special consideration. The variance function approach has been successfully applied in previous studies, but is found to fail under certain conditions in this work. Here, an explicit ITC measurement model consisting of main thermal effects and error components has been proposed to quantitatively evaluate and predict the non-constant variance of the heat data under various conditions. Monte Carlo simulation shows that the ITC measurement model provides higher accuracy and flexibility than variance function in high c-value reactions or with additional error components, for example, originated from the fluctuation of the concentrations or other properties of the solutions. The experimental design of basic error evaluation is optimized accordingly and verified by both Monte Carlo simulation and experiments. An easy-to-run Python source code is provided to illustrate the establishment of the ITC measurement model and the estimation of heat variances. The accurate and reliable non-constant variance of heat is helpful to the application of weighted least squares regression, the proper evaluation or selection of the reaction model.

Analysis of the HIV-1 Genomic RNA Dimerization Initiation Site Binding to Aminoglycoside Antibiotics Using Isothermal Titration Calorimetry

Isothermal titration calorimetry (ITC) provides a sensitive, powerful, and accurate tool to suitably analyze the thermodynamic of RNA binding events. This approach does not require any modification or labeling of the system under analysis and is performed in solution. ITC is a very convenient technique that provides an accurate determination of binding parameters, as well as a complete thermodynamic profile of the molecular interactions. Here we show how this approach can be used to characterize the interactions between the dimerization initiation site (DIS) RNA localized within the HIV-1 viral genome and aminoglycoside antibiotics. Our ITC study showed that the 4,5-disubstituted 2-desoxystreptamine (2-DOS) aminoglycosides can bind the DIS with a nanomolar affinity and a high specificity.

ITC Studies of Ribosome/Antibiotics Interactions

The fight against multiresistant bacteria responsible for nosocomial diseases has recently been classified as an absolute priority by the World Health Organization. For some organisms, priority status has even been assessed as critical, as almost all currently available antibiotics are now inefficient against these "super-bacteria." Ribosome is a major target of several antibiotics, and extensive biochemical and structural studies led to a better understanding of the mechanism of action of drugs targeting translation (Blair et al., Nat Rev Microbiol 13:42-51, 2015; Lin et al., Annu Rev Biochem 87:451-478, 2018; Wilson, Nat Rev Microbiol 12:35-48, 2014; Yonath, Annu Rev Biochem 74:649-79, 2005). However, our knowledge regarding thermodynamic data of compounds targeting the ribosome, which are yet essential for a complete understanding of translation inhibition mechanisms by drugs, is still very poor.In this chapter we describe the use of ITC microcalorimetry to investigate the binding of bacterial ribosome to two antibiotics targeting the peptide tunnel: macrolides and proline-rich antimicrobial peptides (PrAMPs). This strategy yields reliable and artifact-free binding parameters for antibiotics and provides an original view on ribosome/antibiotics interactions.

Critique of methods for estimating heats in isothermal titration calorimetry

Isothermal titration calorimetry data recorded on a MicroCal/Malvern VP-ITC instrument for water-water blanks and for dilution of aqueous solutions of BaCl₂ and Ba(NO₃)₂ are analyzed using Origin software, the freeware NITPIC program, and in-house algorithms, to compare precisions for estimating the heat per injection q. The data cover temperatures 6-47 °C, injection volumes 4-40 μL, and average heats 0-200 μcal. For water-water blanks, where baseline noise limits precision, NITPIC and the in-house algorithm achieve precisions of 0.05 μcal, which is better than Origin by a factor of 4. The precision differences decrease with increasing |q|, becoming insignificant for |q| > 200 μcal. In its default mode, NITPIC underestimates |q| for peaks with incomplete return to baseline, but the shortfall can be largely corrected by overriding the default injection time parameter. The variance estimates from 26 dilution experiments are used to assess the data variance function. The results determine the conditions under which weighted least squares should be used to estimate thermodynamic parameters from ITC data.

Ion Binding to Transport Proteins using Isothermal Titration Calorimetry

Isothermal titration calorimetry (ITC) is an emerging, label-free technology used to measure ligand binding to membrane proteins. This technology utilizes a titration calorimeter to measure the heat exchange upon ligands binding to proteins, the magnitude of which is based on the overall enthalpy of the reaction. In this protocol, the steps we and others use to measure ion binding to ion transport proteins are described.

Can you trust the parametric standard errors in nonlinear least squares? Yes, with provisos

BACKGROUND

Questions about the reliability of parametric standard errors (SEs) from nonlinear least squares (LS) algorithms have led to a general mistrust of these precision estimators that is often unwarranted.

METHODS

The importance of non-Gaussian parameter distributions is illustrated by converting linear models to nonlinear by substituting e^A, ln A, and 1/A for a linear parameter a. Monte Carlo (MC) simulations characterize parameter distributions in more complex cases, including when data have varying uncertainty and should be weighted, but weights are neglected. This situation leads to loss of precision and erroneous parametric SEs, as is illustrated for the Lineweaver-Burk analysis of enzyme kinetics data and the analysis of isothermal titration calorimetry data.

RESULTS

Non-Gaussian parameter distributions are generally asymmetric and biased. However, when the parametric SE is <10% of the magnitude of the parameter, both the bias and the asymmetry can usually be ignored. Sometimes nonlinear estimators can be redefined to give more normal distributions and better convergence properties.

CONCLUSION

Variable data uncertainty, or heteroscedasticity, can sometimes be handled by data transforms but more generally requires weighted LS, which in turn require knowledge of the data variance.

GENERAL SIGNIFICANCE

Parametric SEs are rigorously correct in linear LS under the usual assumptions, and are a trustworthy approximation in nonlinear LS provided they are sufficiently small - a condition favored by the abundant, precise data routinely collected in many modern instrumental methods.