Survey of the year 2005: literature on applications of isothermal titration calorimetry

Exploration of interaction between angiotensin I-converting enzyme (ACE) and the inhibitory peptide from Wakame (Undaria pinnatifida)

The interaction between angiotensin I-converting enzyme (ACE) and the inhibitory peptide KNFL from Wakame was explored using isothermal titration calorimetry, multiple spectroscopic techniques and molecular dynamics simulations, and an inhibition model was established based on free energy binding theory. The experiments revealed that the binding of KNFL to ACE was a spontaneous exothermic process driven by enthalpy and entropy and occurred via multiple binding sites to form stable complexes. The complexes may be formed through multiple steps of inducing fit and conformational selection. The peptide KNFL had a fluorescence quenching effect on ACE and its addition not only affected the microenvironment around the ACE Trp and Tyr residues, but also increased the diameter and altered the conformation of ACE. This study should prove useful for improving our understanding of the mechanism of ACE inhibitory peptides.

Thermodynamics of semi-specific ligand recognition: the binding of dipeptides to the E.coli dipeptide binding protein DppA

This investigation of the temperature dependence of DppA interactions with a subset of three dipeptides (AA. AF and FA) by isothermal titration calorimetry has revealed the negative heat capacity (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta {C}_{p}^{o}$$\end{document}ΔCpo) that is a characteristic of hydrophobic interactions. The observation of enthalpy–entropy compensation is interpreted in terms of the increased structuring of water molecules trapped in a hydrophobic environment, the enthalpic energy gain from which is automatically countered by the entropy decrease associated with consequent loss of water structure flexibility. Specificity for dipeptides stems from appropriate spacing of designated DppA aspartate and arginine residues for electrostatic interaction with the terminal amino and carboxyl groups of a dipeptide, after which the binding pocket closes to become completely isolated from the aqueous environment. Any differences in chemical reactivity of the dipeptide sidechains are thereby modulated by their occurrence in a hydrophobic environment where changes in the structural state of entrapped water molecules give rise to the phenomenon of enthalpy–entropy compensation. The consequent minimization of differences in the value of ΔG⁰ for all DppA–dipeptide interactions thus provides thermodynamic insight into the biological role of DppA as a transporter of all dipeptides across the periplasmic membrane.

Continuous Injection Isothermal Titration Calorimetry for In Situ Evaluation of Thermodynamic Binding Properties of Ligand-Receptor Binding Models

We utilize a continuous injection approach (CIA) rather than the traditional incremental injection approach (IIA) to deliver ligand (or receptor) to the calorimeter cell to evaluate thermodynamic binding parameters for three common ligand-receptor binding models-single independent, competitive, and two independent binding sites-using isothermal titration calorimetry (ITC). A general mathematical expression for the binding isotherm for any binding stoichiometry under continuous delivery of ligand (or receptor) resulting in an analytical solution for the thermodynamic binding parameters is presented. The advantages of CIA include reduction in experimental time, estimation of thermodynamic binding parameter values, and automation of the experiment since thermodynamic parameters are estimated in situ. We demonstrate the inherent advantages of CIA over IIA for the three binding models. For the single independent site model, we utilized the binding of Ba²⁺ ions to ethylenediaminetetraacetic acid (EDTA), while competitive binding was captured by titration of Ca²⁺ ions into a buffered solution of Ba²⁺ and EDTA. We experimentally simulated a two independent binding site system by injecting Ca²⁺ into a solution of EDTA and 1,3-diaminopropane-N,N,N',N'-tetraacetic acid (DPTA). The results demonstrate estimation of thermodynamic parameters with greater confidence and simultaneous reduction in the experimental time of 83% and titrating reagent of 50%, as compared to IIA.

Discovery of a potent small molecule inhibiting Huntington's disease (HD) pathogenesis via targeting CAG repeats RNA and Poly Q protein

CAG repeats RNA causes various fatal neurodegenerative diseases exemplified by Huntington's disease (HD) and several spinocerebellar ataxias (SCAs). Although there are differences in the pathogenic mechanisms, these diseases share the common cause, i.e., expansion of CAG repeats. The shared cause of these diseases raises the possibility for the exploiting the common target as a potential therapeutic approach. Oligonucleotide-based therapeutics are designed earlier with the help of the base pairing rule but are not very promiscuous, considering the nonspecific stimulation of the immune system and the poor cellular delivery. Therefore, small molecules-based therapeutics are preferred for targeting the repeats expansion disorders. Here, we have used the chemical similarity search approach to discern the small molecules that selectively target toxic CAG RNA. The lead compounds showed the specificity towards AA mismatch in biophysical studies including CD, ITC, and NMR spectroscopy and thus aided to forestall the polyQ mediated pathogenicity. Furthermore, the lead compounds also explicitly alleviate the polyQ mediated toxicity in HD cell models and patient-derived cells. These findings suggest that the lead compound could act as a chemical probe for AA mismatch containing RNA as well as plays a neuroprotective role in fatal neurodegenerative diseases like HD and SCAs.

A Highly Compensated Interferometer for Biochemical Analysis

Here we report an improved interferometric sensing approach that facilitates high sensitivity nanovolume refractive index (RI) measurements and molecular interaction assays without a temperature controller. The compensated backscattering interferometer (CBSI) is based on a helium-neon (He-Ne) laser, a microfluidic chip, and a CCD array. The CBSI enables simultaneous differential RI measurements within nanoliter volumes, at a compensation level of ca. 5 × 10^-8 RIU in the presence of large thermal perturbations (8 °C). This level of d n/d T compensation is enabled by elongating the laser beam along the central axis of the microfluidic channel and measuring the difference in positional shift of interference patterns from two adjacent regions of the channel. By separating two solutions by an air gap or oil droplet, CBSI can discriminate the difference in RI for the sample and reference at a detection limit of 7 × 10^-7 RIU in the absence of electronic filtering. At this level of ΔRI sensitivity, it is possible to perform label-free, free-solution biochemical assays at the 10s of nM level without the typical high-resolution temperature control needed in conventional interferometers. Here we illustrate the effective use of CBSI by quantifying the binding affinities for mannose-concanavalin A and Ca²⁺-recoverin interactions.

Data Mining and Machine Learning Models for Predicting Drug Likeness and Their Disease or Organ Category

Data mining approaches can uncover underlying patterns in chemical and pharmacological property space decisive for drug discovery and development. Two of the most common approaches are visualization and machine learning methods. Visualization methods use dimensionality reduction techniques in order to reduce multi-dimension data into 2D or 3D representations with a minimal loss of information. Machine learning attempts to find correlations between specific activities or classifications for a set of compounds and their features by means of recurring mathematical models. Both models take advantage of the different and deep relationships that can exist between features of compounds, and helpfully provide classification of compounds based on such features or in case of visualization methods uncover underlying patterns in the feature space. Drug-likeness has been studied from several viewpoints, but here we provide the first implementation in chemoinformatics of the t-Distributed Stochastic Neighbor Embedding (t-SNE) method for the visualization and the representation of chemical space, and the use of different machine learning methods separately and together to form a new ensemble learning method called AL Boost. The models obtained from AL Boost synergistically combine decision tree, random forests (RF), support vector machine (SVM), artificial neural network (ANN), k nearest neighbors (kNN), and logistic regression models. In this work, we show that together they form a predictive model that not only improves the predictive force but also decreases bias. This resulted in a corrected classification rate of over 0.81, as well as higher sensitivity and specificity rates for the models. In addition, separation and good models were also achieved for disease categories such as antineoplastic compounds and nervous system diseases, among others. Such models can be used to guide decision on the feature landscape of compounds and their likeness to either drugs or other characteristics, such as specific or multiple disease-category(ies) or organ(s) of action of a molecule.

Antihypertensive Effects, Molecular Docking Study, and Isothermal Titration Calorimetry Assay of Angiotensin I-Converting Enzyme Inhibitory Peptides from Chlorella vulgaris

The aim of this work is to explore angiotensin I-converting enzyme (ACE) inhibitory peptides from Chlorella vulgaris (C. vulgaris) and discover the inhibitory mechanism of the peptides. After C. vulgaris proteins were gastrointestinal digested in silico, several ACE inhibitory peptides with C-terminal tryptophan were screened. Among them, two novel noncompetitive ACE inhibitors, Thr-Thr-Trp (TTW) and Val-His-Trp (VHW), exhibited the highest inhibitory activity indicated by IC₅₀ values 0.61 ± 0.12 and 0.91 ± 0.31 μM, respectively. Both the peptides were demonstrated stable against gastrointestinal digestion and ACE hydrolysis. The peptides were administrated to spontaneously hypertensive rats (SHRs) in the dose 5 mg/kg body weight, and VHW could decrease 50 mmHg systolic blood pressure of SHRs (p < 0.05). Molecular docking displayed that both TTW and VHW formed six hydrogen bonds with active site pockets of ACE. Besides, isothermal titration calorimetry assay discovered that VHW could form more stable complex with ACE than TTW. Therefore, VHW was an excellent ACE inhibitor.

Physiologically relevant binding affinity quantification of monoclonal antibody PF-00547659 to mucosal addressin cell adhesion molecule for in vitro in vivo correlation

Background and Purpose

A monoclonal antibody (PF‐00547659) against mucosal addressin cell adhesion molecule (MAdCAM), expressed as both soluble (sMAdCAM) and trans‐membrane (mMAdCAM) target forms, showed over 30‐fold difference in antibody‐target K_D between in vitro (Biacore) and clinically derived (K_D,in‐vivo) values. Back‐scattering interferometry (BSI) was applied to acquire physiologically relevant K_D values which were used to establish in vitro and in vivo correlation (IVIVC).

Experimental Approach

BSI was applied to obtain K_D values between PF‐00547659 and recombinant human MAdCAM in buffer or CHO cells and endogenous MAdCAM in human serum or colon tissue. CHO cells and tissue were minimally processed to yield homogenate containing membrane vesicles and soluble proteins. A series of binding affinities in serum with various dilution factors was used to estimate both K_D,in‐vivo and target concentrations; MAdCAM concentrations were also measured using LC–MS/MS.

Key Results

BSI measurements revealed low K_D values (higher affinity) for sMAdCAM in buffer and serum, yet a 20‐fold higher K_D value (lower affinity) for mMAdCAM in CHO, mMAdCAM and sMAdCAM in tissue. BSI predicted K_D,in‐vivo in serum was similar to clinically derived K_D,in‐vivo, and the BSI‐estimated serum sMAdCAM concentration also matched the measured concentration by LC–MS/MS.

Conclusions and Implications

Our results successfully demonstrated that BSI measurements of physiologically relevant K_D values can be used to establish IVIVC, for PF‐00547659 to MAdCAM despite the lack of correlation when using Biacore measured K_D and accurately estimates endogenous target concentrations. The application of BSI would greatly enhance successful basic pharmacological research and drug development.

Applications of isothermal titration calorimetry - the research and technical developments from 2011 to 2015

Isothermal titration calorimetry is a widely used biophysical technique for studying the formation or dissociation of molecular complexes. Over the last 5 years, much work has been published on the interpretation of isothermal titration calorimetry (ITC) data for single binding and multiple binding sites. As over 80% of ITC papers are on macromolecules of biological origin, this interpretation is challenging. Some researchers have attempted to link the thermodynamics constants to events at the molecular level. This review highlights work carried out using binding sites characterized using x-ray crystallography techniques that allow speculation about individual bond formation and the displacement of individual water molecules during ligand binding and link these events to the thermodynamic constants for binding. The review also considers research conducted with synthetic binding partners where specific binding events like anion-π and π-π interactions were studied. The revival of assays that enable both thermodynamic and kinetic information to be collected from ITC data is highlighted. Lastly, published criticism of ITC research from a physical chemistry perspective is appraised and practical advice provided for researchers unfamiliar with thermodynamics and its interpretation. Copyright © 2016 John Wiley & Sons, Ltd.

Current Experimental Methods for Characterizing Protein-Protein Interactions

Protein molecules often interact with other partner protein molecules in order to execute their vital functions in living organisms. Characterization of protein-protein interactions thus plays a central role in understanding the molecular mechanism of relevant protein molecules, elucidating the cellular processes and pathways relevant to health or disease for drug discovery, and charting large-scale interaction networks in systems biology research. A whole spectrum of methods, based on biophysical, biochemical, or genetic principles, have been developed to detect the time, space, and functional relevance of protein-protein interactions at various degrees of affinity and specificity. This article presents an overview of these experimental methods, outlining the principles, strengths and limitations, and recent developments of each type of method.

Current Experimental Methods for Characterizing Protein-Protein Interactions

Protein molecules often interact with other partner protein molecules in order to execute their vital functions in living organisms. Characterization of protein-protein interactions thus plays a central role in understanding the molecular mechanism of relevant protein molecules, elucidating the cellular processes and pathways relevant to health or disease for drug discovery, and charting large-scale interaction networks in systems biology research. A whole spectrum of methods, based on biophysical, biochemical, or genetic principles, have been developed to detect the time, space, and functional relevance of protein-protein interactions at various degrees of affinity and specificity. This article presents an overview of these experimental methods, outlining the principles, strengths and limitations, and recent developments of each type of method.

Origin and prediction of free-solution interaction studies performed label-free

Interaction/reaction assays have led to significant scientific discoveries in the biochemical, medical, and chemical disciplines. Several fundamental driving forces form the basis of intermolecular and intramolecular interactions in chemical and biochemical systems (London dispersion, hydrogen bonding, hydrophobic, and electrostatic), and in the past three decades the sophistication and power of techniques to interrogate these processes has developed at an unprecedented rate. In particular, label-free methods have flourished, such as NMR, mass spectrometry (MS), surface plasmon resonance (SPR), biolayer interferometry (BLI), and backscattering interferometry (BSI), which can facilitate assays without altering the participating components. The shortcoming of most refractive index (RI)-based label-free methods such as BLI and SPR is the requirement to tether one of the interaction entities to a sensor surface. This is not the case for BSI. Here, our hypothesis is that the signal origin for free-solution, label-free determinations can be attributed to conformation and hydration-induced changes in the solution RI. We propose a model for the free-solution response function (FreeSRF) and show that, when quality bound and unbound structural data are available, FreeSRF correlates well with the experiment (R(2)> 0.99, Spearman rank correlation coefficients >0.9) and the model is predictive within ∼15% of the experimental binding signal. It is also demonstrated that a simple mass-weighted dη/dC response function is the incorrect equation to determine that the change in RI is produced by binding or folding event in free solution.

Characterizing aptamer small molecule interactions with backscattering interferometry

Aptamers are segments of single-strand DNA or RNA used in a wide array of applications, including sensors, therapeutics, and cellular process regulators. Aptamers can bind many target species, including proteins, peptides, and small molecules (SM) with high affinity and specificity. They are advantageous because they can be identified in vitro by SELEX, produced rapidly and relatively economically using oligonucleotide synthesis. The use of aptamers as SM probes has experienced a recent rebirth, and because of their unique properties they represent an attractive alternative to antibodies. Current assay methodology for characterizing small molecule-aptamer binding is limited by either mass sensitivity, as in biolayer interferometry (BLI) and surface plasmon resonance (SPR), or the need for using a fluorophore, as in thermophoresis. Here we report that backscattering interferometry (BSI), a label-free and free-solution sensing technique, can be used to effectively characterize SM-aptamer interactions, providing Kd values on microliter sample quantities and at low nanomolar sensitivity. To demonstrate this capability we measured the aptamer affinity for three previously reported small molecules; bisphenol A, tenofovir, and epirubicin showing BSI provided values consistent with those published previously. We then quantified the Kd values for aptamers to ampicillin, tetracycline and norepinephrine. All measurements produced R(2) values >0.95 and an excellent signal to noise ratio at target concentrations that enable true Kd values to be obtained. No immobilization or labeling chemistry was needed, expediting the assay which is also insensitive to the large relative mass difference between the interacting molecules.

Self-assembled β-lactoglobulin-oleic acid and β-lactoglobulin-linoleic acid complexes with antitumor activities

β-Lactoglobulin (β-LG) can bind to fatty acids such as oleic acid (OA) and linoleic acid (LA). Another whey protein, α-lactalbumin (α-LA), can also bind to OA to give the complex α-LA-OA, which has antitumor properties. Based on reports that the activity of α-LA-OA is highly dependent on OA, as well as the acquisition of similar complexes using other proteins, such as lysozyme and lactoferrin, we speculated whether β-LG could also kill tumor cells after binding to other fatty acids. Therefore, we prepared complexes of β-LG with OA (β-LG-OA) and LA (β-LG-LA) in the current study and evaluated them in terms of antitumor activity and thermostability using the methylene blue method and differential scanning calorimetry, respectively. The structural features of these complexes were also evaluated using fluorescence spectroscopy and circular dichroism. The binding dynamics of OA and LA to β-LG were studied using isothermal titration calorimetry. Cell viability results revealed that β-LG-LA and β-LG-OA exhibited similar antitumor activities. Interestingly, the binding of β-LG to LA led to an increase in its thermostability, whereas its binding to OA had very little effect. The environments of the tryptophan residues in the β-LG-OA and β-LG-LA complexes were very different, with the residues being blue- and red-shifted, respectively. Furthermore, the hydrophobic regions in β-LG were buried after binding of OA, which was slightly changed in β-LG-LA. Circular dichroism results showed that β-LG-OA enhanced the tertiary structure, which was partially lost in β-LG-LA. There were more binding sites for OA than for LA on β-LG, although the binding constants of the 2 fatty acids were similar, with both acids interacting with the protein though van der Waals and hydrogen bonding interactions. This study could help provide a deeper understanding of the structural basis for formation of antitumor protein-fatty acid complexes.

Label-free free-solution nanoaperture optical tweezers for single molecule protein studies

Recent advances in nanoaperture optical tweezers have enabled studies of single nanoparticles like proteins in label-free, free-solution environments.

Thermodynamic and kinetic properties of interpolymer complexes assessed by isothermal titration calorimetry and surface plasmon resonance

Interpolymer complexes (IPCs) formed between complimentary polymers in solution have shown a wide range of applications from drug delivery to biosensors. This work describes the combined use of isothermal titration calorimetry and surface plasmon resonance to investigate the thermodynamic and kinetic processes during hydrogen-bonded interpolymer complexation. Varied polymers that are commonly used in layer-by-layer coatings and pharmaceutical preparations were selected to span a range of chemical functionalities including some known IPCs previously characterized by other techniques, and other polymer combinations with unknown outcomes. This work is the first to comprehensively detail the thermodynamic and kinetic data of hydrogen bonded IPCs, aiding understanding and detailed characterization of the complexes. The applicability of the two techniques in determining thermodynamic, gravimetric and kinetic properties of IPCs is considered.

A label-free untethered approach to single-molecule protein binding kinetics

Single molecule approaches provide rich real-time dynamics of molecular interactions that are not accessible to ensemble measurements. Previous single molecule studies have relied on labeling and tethering, which alters the natural state of the protein. Here we use the double-nanohole (DNH) optical tweezer approach to measure protein binding kinetics at the single molecule level in a label-free, free-solution (untethered) way. The binding kinetics of human serum albumin (HSA) to tolbutamide and to phenytoin are in quantitative agreement with previous measurements, and our single-molecule approach reveals a biexponential behavior characteristic of a multistep process. The DNH optical tweezer is an inexpensive platform for studying the real-time binding kinetics of protein-small molecule interactions in a label-free, free-solution environment, which will be of interest to future studies including drug discovery.

The SARS coronavirus nucleocapsid protein--forms and functions

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Coronavirus N proteins share the same modular organization.

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Structures of SARS-CoV N protein provide insight into nucleocapsid formation.

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N protein binds to nucleic acid at multiple sites in a coupled-allostery manner.

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A RNP packaging model highlighting the importance of disorder and modularity is proposed.

The nucleocapsid phosphoprotein of the severe acute respiratory syndrome coronavirus (SARS-CoV N protein) packages the viral genome into a helical ribonucleocapsid (RNP) and plays a fundamental role during viral self-assembly. It is a protein with multifarious activities. In this article we will review our current understanding of the N protein structure and its interaction with nucleic acid. Highlights of the progresses include uncovering the modular organization, determining the structures of the structural domains, realizing the roles of protein disorder in protein–protein and protein–nucleic acid interactions, and visualizing the ribonucleoprotein (RNP) structure inside the virions. It was also demonstrated that N-protein binds to nucleic acid at multiple sites with a coupled-allostery manner. We propose a SARS-CoV RNP model that conforms to existing data and bears resemblance to the existing RNP structures of RNA viruses. The model highlights the critical role of modular organization and intrinsic disorder of the N protein in the formation and functions of the dynamic RNP capsid in RNA viruses. This paper forms part of a symposium in Antiviral Research on “From SARS to MERS: 10 years of research on highly pathogenic human coronaviruses.”

Drugs, non-drugs, and disease category specificity: organ effects by ligand pharmacology

Important understanding can be gained from using molecular biology-based and chemistry-based techniques together. Bayesian classifiers have thus been developed in the present work using several statistically significant molecular properties of compiled datasets of drugs and non-drugs, including their disease category or organ. The results show they provide a useful classification and simplicity of several different ligand efficiencies and molecular properties. Early recall of drugs among non-drugs using the classifiers as a ranking tool is also provided. As the chemical space of compounds is addressed together with their anatomical characterization, chemical libraries can be improved to select for specific organ or disease. Eventually, by including even finer detail, the method may help in designing libraries with specific pharmacological or toxicological target chemical space. Alternatively, a lack of statistically significant differences in property density distributions may help in further describing compounds with possibility of activity on several organs or disease groups, and given their very similar or considerably overlapping chemical space, therefore wanted or unwanted side-effects. The overlaps between densities for several properties of organs or disease categories were calculated by integrating the area under the curves where they intersect. The naïve Bayesian classifiers are readily built, fast to score, and easily interpretable.

Modeling complex equilibria in isothermal titration calorimetry experiments: thermodynamic parameters estimation for a three-binding-site model

Isothermal titration calorimetry (ITC) is a powerful technique that can be used to estimate a complete set of thermodynamic parameters (e.g., K(eq) (or ΔG), ΔH, ΔS, and n) for a ligand-binding interaction described by a thermodynamic model. Thermodynamic models are constructed by combining equilibrium constant, mass balance, and charge balance equations for the system under study. Commercial ITC instruments are supplied with software that includes a number of simple interaction models, for example, one binding site, two binding sites, sequential sites, and n-independent binding sites. More complex models, for example, three or more binding sites, one site with multiple binding mechanisms, linked equilibria, or equilibria involving macromolecular conformational selection through ligand binding, need to be developed on a case-by-case basis by the ITC user. In this paper we provide an algorithm (and a link to our MATLAB program) for the nonlinear regression analysis of a multiple-binding-site model with up to four overlapping binding equilibria. Error analysis demonstrates that fitting ITC data for multiple parameters (e.g., up to nine parameters in the three-binding-site model) yields thermodynamic parameters with acceptable accuracy.

Determining DNA supercoiling enthalpy by isothermal titration calorimetry

DNA supercoiling plays a critical role in certain essential DNA transactions, such as DNA replication, recombination, and transcription. For this reason, exploring energetics of DNA supercoiling is fundamentally important for understanding its biological functions. In this paper, using a unique property of DNA intercalators, such as ethidium bromide and daunorubicin, which bind to supercoiled, nicked, and relaxed DNA templates with different DNA-binding enthalpies, we determined DNA supercoiling enthalpy of plasmid pXXZ6, a 4.5 kb plasmid to be about 11.5 kcal/mol per linking number change. This determination allowed us to partition the DNA supercoiling free energy into enthalpic and entropic contributions where the unfavorable DNA supercoiling free energy exclusively originated from the large positive supercoiling enthalpy and was compensated by a large, favorable entropy term (TΔS).

DrugLogit: logistic discrimination between drugs and nondrugs including disease-specificity by assigning probabilities based on molecular properties

The increasing knowledge of both structure and activity of compounds provides a good basis for enhancing the pharmacological characterization of chemical libraries. In addition, pharmacology can be seen as incorporating both advances from molecular biology as well as chemical sciences, with innovative insight provided from studying target-ligand data from a ligand molecular point of view. Predictions and profiling of libraries of drug candidates have previously focused mainly on certain cases of oral bioavailability. Inclusion of other administration routes and disease-specificity would improve the precision of drug profiling. In this work, recent data are extended, and a probability-based approach is introduced for quantitative and gradual classification of compounds into categories of drugs/nondrugs, as well as for disease- or organ-specificity. Using experimental data of over 1067 compounds and multivariate logistic regressions, the classification shows good performance in training and independent test cases. The regressions have high statistical significance in terms of the robustness of coefficients and 95% confidence intervals provided by a 1000-fold bootstrapping resampling. Besides their good predictive power, the classification functions remain chemically interpretable, containing only one to five variables in total, and the physicochemical terms involved can be easily calculated. The present approach is useful for an improved description and filtering of compound libraries. It can also be applied sequentially or in combinations of filters, as well as adapted to particular use cases. The scores and equations may be able to suggest possible routes for compound or library modification. The data is made available for reuse by others, and the equations are freely accessible at http://hermes.chem.ut.ee/~alfx/druglogit.html.

Applications of isothermal titration calorimetry in pure and applied research--survey of the literature from 2010

Isothermal titration calorimetry (ITC) is a biophysical technique for measuring the formation and dissociation of molecular complexes and has become an invaluable tool in many branches of science from cell biology to food chemistry. By measuring the heat absorbed or released during bond formation, ITC provides accurate, rapid, and label-free measurement of the thermodynamics of molecular interactions. In this review, we survey the recent literature reporting the use of ITC and have highlighted a number of interesting studies that provide a flavour of the diverse systems to which ITC can be applied. These include measurements of protein-protein and protein-membrane interactions required for macromolecular assembly, analysis of enzyme kinetics, experimental validation of molecular dynamics simulations, and even in manufacturing applications such as food science. Some highlights include studies of the biological complex formed by Staphylococcus aureus enterotoxin C3 and the murine T-cell receptor, the mechanism of membrane association of the Parkinson's disease-associated protein α-synuclein, and the role of non-specific tannin-protein interactions in the quality of different beverages. Recent developments in automation are overcoming limitations on throughput imposed by previous manual procedures and promise to greatly extend usefulness of ITC in the future. We also attempt to impart some practical advice for getting the most out of ITC data for those researchers less familiar with the method.

DNA-protein interactions: methods for detection and analysis

DNA-binding proteins control various cellular processes such as recombination, replication and transcription. This review is aimed to summarize some of the most commonly used techniques to determine DNA-protein interactions. In vitro techniques such as footprinting assays, electrophoretic mobility shift assay, southwestern blotting, yeast one-hybrid assay, phage display and proximity ligation assay have been discussed. The highly versatile in vivo techniques such as chromatin immunoprecipitation and its variants, DNA adenine methyl transferase identification as well as 3C and chip-loop assay have also been summarized. In addition, some in silico tools have been reviewed to provide computational basis for determining DNA-protein interactions. Biophysical techniques like fluorescence resonance energy transfer (FRET) techniques, FRET-FLIM, circular dichroism, atomic force microscopy, nuclear magnetic resonance, surface plasmon resonance, etc. have also been highlighted.

Energetics of ligand binding to G-quadruplexes

G-quadruplex ligands are potential anticancer agents as telomerase inhibitors and potential transcriptional regulators of oncogenes. The search for best-in-class drugs is addressed to identify small molecules able to promote and stabilize G-quadruplex structures. What features should the G-quadruplex ligands possess? They should have selective antiproliferative effects on cancer cells and induce telomerase inhibition or oncogene suppression. One of the main challenges in their design and synthesis is to make the ligands selective for G-quadruplex DNA. These features should be amplified by careful analyses of physico-chemical aspects of G-quadruplex-drug interactions. In particular, the study of the energetics of G-quadruplex-drug interactions can enhance drug design by providing thermodynamic parameters that give quantitative information on the biomolecular interactions important for binding. The main methodologies used to gain information on energetics of binding are based on spectroscopic or calorimetric principles. Spectroscopic techniques such as fluorescence and circular dichroism are rapid and cheap methods, but are not sufficient to characterize completely the thermodynamics of interaction. Calorimetric techniques such as isothermal titration calorimetry offer a direct measure of binding enthalpy, in addition to the stoichiometry and affinity constants. With the complete thermodynamic signature of drug-target interaction, dissecting the enthalpic and entropic components of binding is possible, which can be a useful aid to decision-making during drug optimization.

Isothermal titration calorimetry for measuring macromolecule-ligand affinity

Isothermal titration calorimetry (ITC) is a useful tool for understanding the complete thermodynamic picture of a binding reaction. In biological sciences, macromolecular interactions are essential in understanding the machinery of the cell. Experimental conditions, such as buffer and temperature, can be tailored to the particular binding system being studied. However, careful planning is needed since certain ligand and macromolecule concentration ranges are necessary to obtain useful data. Concentrations of the macromolecule and ligand need to be accurately determined for reliable results. Care also needs to be taken when preparing the samples as impurities can significantly affect the experiment. When ITC experiments, along with controls, are performed properly, useful binding information, such as the stoichiometry, affinity and enthalpy, are obtained. By running additional experiments under different buffer or temperature conditions, more detailed information can be obtained about the system. A protocol for the basic setup of an ITC experiment is given.

The thermodynamic and binding properties of the transferrins as studied by isothermal titration calorimetry

BACKGROUND

In mammals, serum-transferrins transport iron from the neutral environment of the blood to the cytoplasm by receptor-mediated endocytosis. Extensive in-vitro studies have focused on the thermodynamics and kinetics of Fe(3+) binding to a number of transferrins. However, little attention has been given to the thermodynamic characterization of the interaction of transferrin with its receptor.

SCOPE OF REVIEW

Iron-loaded transferrin (Tf) binds with high affinity to the specific transferrin receptor (TfR) on the cell surface. The Tf-TfR complex is then internalized via receptor mediated endocytosis into an endosome where iron is released. Here, we provide an overview of recent studies that have used ITC to quantify the interaction of various metal ions with transferrin and highlight our current understanding of the thermodynamics of the transferrin-transferrin receptor system at physiological pH.

GENERAL SIGNIFICANCE

The interaction of the iron-loaded transferrin with the transferrin receptor is a key cellular process that occurs during the normal course of iron metabolism. Understanding the thermodynamics of this interaction is important for iron homeostasis since the physiological requirement of iron must be appropriately maintained to avoid iron-related diseases.

MAJOR CONCLUSIONS

The thermodynamic data revealed stoichiometric binding of all tested metal ions to transferrin with very high affinities ranging between 10(17) and 10(22)M(-1). Iron-loaded transferrin (monoferric or diferric) is shown to bind avidly (K~10(7)-10(8)M(-1)) to the receptor at neutral pH with a stoichiometry of one Tf molecule per TfR monomer. Significantly, both the N- and the C-lobe contribute to the binding interaction which is shown to be both enthalpically and entropically driven. This article is part of a Special Issue entitled Transferrins: Molecular mechanisms of iron transport and disorders.

Collecting variable-concentration isothermal titration calorimetry datasets in order to determine binding mechanisms

Isothermal titration calorimetry (ITC) is commonly used to determine the thermodynamic parameters associated with the binding of a ligand to a host macromolecule. ITC has some advantages over common spectroscopic approaches for studying host/ligand interactions. For example, the heat released or absorbed when the two components interact is directly measured and does not require any exogenous reporters. Thus the binding enthalpy and the association constant (Ka) are directly obtained from ITC data, and can be used to compute the entropic contribution. Moreover, the shape of the isotherm is dependent on the c-value and the mechanistic model involved. The c-value is defined as c = n[P]tKa, where [P]t is the protein concentration, and n is the number of ligand binding sites within the host. In many cases, multiple binding sites for a given ligand are non-equivalent and ITC allows the characterization of the thermodynamic binding parameters for each individual binding site. This however requires that the correct binding model be used. This choice can be problematic if different models can fit the same experimental data. We have previously shown that this problem can be circumvented by performing experiments at several c-values. The multiple isotherms obtained at different c-values are fit simultaneously to separate models. The correct model is next identified based on the goodness of fit across the entire variable-c dataset. This process is applied here to the aminoglycoside resistance-causing enzyme aminoglycoside N-6'-acetyltransferase-Ii (AAC(6')-Ii). Although our methodology is applicable to any system, the necessity of this strategy is better demonstrated with a macromolecule-ligand system showing allostery or cooperativity, and when different binding models provide essentially identical fits to the same data. To our knowledge, there are no such systems commercially available. AAC(6')-Ii, is a homo-dimer containing two active sites, showing cooperativity between the two subunits. However ITC data obtained at a single c-value can be fit equally well to at least two different models a two-sets-of-sites independent model and a two-site sequential (cooperative) model. Through varying the c-value as explained above, it was established that the correct binding model for AAC(6')-Ii is a two-site sequential binding model. Herein, we describe the steps that must be taken when performing ITC experiments in order to obtain datasets suitable for variable-c analyses.

The synucleins are a family of redox-active copper binding proteins

Thermodynamic studies in conjunction with EPR confirm that α-synuclein, β-synuclein, and γ-synuclein bind copper(II) in a high affinity 1:1 stoichiometry. γ-Synuclein demonstrates the highest affinity, in the picomolar range, while α-synuclein and β-synuclein both bind copper(II) with nanomolar affinity. The copper center on all three proteins demonstrates reversible or partly reversible redox cycling. Various mutations show that the primary coordinating ligand for copper(II) is located within the N-terminal regions between residues 2-9. There is also a contribution from the C-terminus in conjunction with the histidine at position 50 in α-synuclein and position 65 in β-synuclein, although these regions appear to have little effect on overall coordination stability. These histidines and the C-terminus, however, appear to be critical to the redox engine of the proteins.

Experiment and prediction: a productive symbiosis in studies on the thermodynamics of DNA oligomers

Recently, we reported the kinetics of hybridization of cDNA dodecamers (Carrillo-Nava, E., Mejía-Radillo, Y., and Hinz, H.-J. Biochemistry 2008, 47, 13153-13157). In this study, we provide the thermodynamic reaction parameters of those dodecamers as well as a comparison with parameters for 24-mers designed from two identical dodecamers in tandem arrangement. The thermodynamic properties were determined by isothermal titration calorimetry (ITC), differential scanning microcalorimetry (DSC), and UV melting studies. On the basis of the results from our kinetic studies, fitting algorithms of DSC and UV melting profiles employed the two-state assumption for the duplex to a single strand dissociation reaction. The formation of both 12-mer and 24-mer duplexes is strongly enthalpy driven at all temperatures. At identical temperatures, the hybridization enthalpy of the 24-mer is within error limits twice that of the 12-mer. Duplex formation is always associated with a significant negative heat capacity change, ΔC(p), which, on a mass basis, is comparable to that observed for protein folding. Only a small part of the favorable reaction enthalpy appears as a standard Gibbs free energy change due to large compensating negative entropy changes linked to duplex formation. On the basis of the results of the present studies, it appears to be absolutely essential for a proper analysis of thermodynamic parameters of oligonucleotide hybridization reactions to combine low temperature ITC measurements of binding enthalpies with DSC and UV melting studies to obtain an accurate assessment of standard Gibbs energy changes or, equivalently, hybridization constants over a broad temperature range. The experimental thermodynamic parameters were compared with theoretical estimates based on nearest-neighbor approximations employing temperature-independent enthalpies. Good agreement between experimental and predicted ΔG° values is observed at ambient temperatures (20-30 °C), as long as helix formation is associated with small molar heat capacity changes. If the experimental ΔC(p) values determined by ITC are taken into account, significant deviations occur.

Interaction of weakly bound antibiotics neomycin and lincomycin with bovine and human serum albumin: biophysical approach

The thermodynamics of interaction of neomycin and lincomycin with bovine serum albumin (BSA) and human serum albumin (HSA) has been studied using isothermal titration calorimetry (ITC), in combination with UV-visible, steady state and time resolved fluorescence spectroscopic measurements. Neomycin is observed to bind weakly to BSA and HSA whereas lincomycin did not show any evidence for binding with the native state of these proteins, rather it interacts in the presence of surfactants. The ITC results suggest 1 : 1 binding stoichiometry for neomycin in the studied temperature range. The values of the van't Hoff enthalpy do not agree with the calorimetric enthalpy in the case of neomycin, suggesting conformational changes in the protein upon ligand binding, as well as with the rise in the temperature. Experiments at different ionic strengths, and in the presence of tetrabutyl ammonium bromide and surfactants suggest the predominant involvement of electrostatic interactions in the complexation process of neomycin with BSA and HSA, and non-specific interaction behaviour of lincomycin with these proteins.

A thermodynamic approach to the affinity optimization of drug candidates

High throughput screening and other techniques commonly used to identify lead candidates for drug development usually yield compounds with binding affinities to their intended targets in the mid-micromolar range. The affinity of these molecules needs to be improved by several orders of magnitude before they become viable drug candidates. Traditionally, this task has been accomplished by establishing structure activity relationships to guide chemical modifications and improve the binding affinity of the compounds. As the binding affinity is a function of two quantities, the binding enthalpy and the binding entropy, it is evident that a more efficient optimization would be accomplished if both quantities were considered and improved simultaneously. Here, an optimization algorithm based upon enthalpic and entropic information generated by Isothermal Titration Calorimetry is presented.

Biological calorimetry and the thermodynamics of the origination and evolution of life

Calorimetric measurements on biological systems from small molecules to whole organisms lead to a new conception of the nature of live matter that has profound consequences for our understanding of biology. The data show that the differences in Gibbs energy (ΔG) and enthalpy (ΔH) are near zero or negative and the difference in entropy (ΔS) is near zero between a random mixture of molecules and live matter of the same composition. A constant input of energy is required to maintain ion gradients, ATP production, and the other functions of living matter, but because cells are organized in a spontaneous process, no energy input is required to maintain the structure or organization of cells. Thus, the origin of life and evolution of complex life forms occurs by thermodynamically spontaneous processes, carbon-based life should be common throughout the universe, and because there is no energy cost, evolution can occur relatively rapidly.

Isothermal titration calorimetry of RNA

Isothermal titration calorimetry (ITC) is a fast and robust method to study the physical basis of molecular interactions. A single well-designed experiment can provide complete thermodynamic characterization of a binding reaction, including K(a), DeltaG, DeltaH, DeltaS and reaction stoichiometry (n). Repeating the experiment at different temperatures allows determination of the heat capacity change (DeltaC(P)) of the interaction. Modern calorimeters are sensitive enough to probe even weak biological interactions making ITC a very popular method among biochemists. Although ITC has been applied to protein studies for many years, it is becoming widely applicable in RNA biochemistry as well, especially in studies which involve RNA folding and RNA interactions with small molecules, proteins and with other RNAs. This review focuses on best practices for planning, designing and executing effective ITC experiments when one or more of the reactants is an RNA.

A survey of the year 2007 literature on applications of isothermal titration calorimetry

Elucidation of the energetic principles of binding affinity and specificity is a central task in many branches of current sciences: biology, medicine, pharmacology, chemistry, material sciences, etc. In biomedical research, integral approaches combining structural information with in-solution biophysical data have proved to be a powerful way toward understanding the physical basis of vital cellular phenomena. Isothermal titration calorimetry (ITC) is a valuable experimental tool facilitating quantification of the thermodynamic parameters that characterize recognition processes involving biomacromolecules. The method provides access to all relevant thermodynamic information by performing a few experiments. In particular, ITC experiments allow to by-pass tedious and (rarely precise) procedures aimed at determining the changes in enthalpy and entropy upon binding by van't Hoff analysis. Notwithstanding limitations, ITC has now the reputation of being the "gold standard" and ITC data are widely used to validate theoretical predictions of thermodynamic parameters, as well as to benchmark the results of novel binding assays. In this paper, we discuss several publications from 2007 reporting ITC results. The focus is on applications in biologically oriented fields. We do not intend a comprehensive coverage of all newly accumulated information. Rather, we emphasize work which has captured our attention with originality and far-reaching analysis, or else has provided ideas for expanding the potential of the method.

Binding of calcium ions to Ras promotes Ras guanine nucleotide exchange under emulated physiological conditions

Both Ras protein and calcium play significant roles in various cellular processes via complex signaling transduction networks. However, it is not well understood whether and how Ca(2+) can directly regulate Ras function. Here we demonstrate by isothermal titration calorimetry that Ca(2+) directly binds to the H-Ras.GDP.Mg(2+) complex with moderate affinity at the first binding site followed by two weak binding events. The results from limited proteinase degradation show that Ca(2+) protects the fragments of H-Ras from being further degraded by trypsin and by proteinase K. HPLC studies together with fluorescence spectroscopic measurements indicate that binding of Ca(2+) to the H-Ras.GDP.Mg(2+) complex remarkably promotes guanine nucleotide exchange on H-Ras under emulated physiological Ca(2+) concentration conditions. Addition of high concentrations of either of two macromolecular crowding agents, Ficoll 70 and dextran 70, dramatically enhances H-Ras guanine nucleotide exchange extent in the presence of Ca(2+) at emulated physiological concentrations, and the nucleotide exchange extent increases significantly with the concentrations of crowding agents. Together, these results indicate that binding of calcium ions to H-Ras remarkably promotes H-Ras guanine nucleotide exchange under emulated physiological conditions. We thus propose that Ca(2+) may activate Ras signaling pathway by interaction with Ras, providing clues to understand the role of calcium in regulating Ras function in physiological environments.

Substrate binding to cytochromes P450

P450s have attracted tremendous attention owing to not only their involvement in the metabolism of drug molecules and endogenous substrates but also the unusual nature of the reaction they catalyze, namely, the oxidation of unactivated C-H bonds. The binding of substrates to P450s, which is usually viewed as the first step in the catalytic cycle, has been studied extensively via a variety of biochemical and biophysical approaches. These studies were directed towards answering different questions related to P450s, including mechanism of oxidation, substrate properties, unusual substrate oxidation kinetics, function, and active-site features. Some of the substrate binding studies extending over a period of more than 40 years of dedicated work have been summarized in this review and categorized by the techniques employed in the binding studies.

Applications of isothermal titration calorimetry in protein science

During the past decade, isothermal titration calorimetry (ITC) has developed from a specialist method for understanding molecular interactions and other biological processes within cells to a more robust, widely used method. Nowadays, ITC is used to investigate all types of protein interactions, including protein-protein interactions, protein-DNA/RNA interactions, protein-small molecule interactions and enzyme kinetics; it provides a direct route to the complete thermodynamic characterization of protein interactions. This review concentrates on the new applications of ITC in protein folding and misfolding, its traditional application in protein interactions, and an overview of what can be achieved in the field of protein science using this method and what developments are likely to occur in the near future. Also, this review discusses some new developments of ITC method in protein science, such as the reverse titration of ITC and the displacement method of ITC.

Calorimetric and spectroscopic studies of Hoechst 33258: self-association and binding to non-cognate DNA

Sequence and structure-specific molecular recognition of DNA by small molecules is an important goal in biophysical chemistry and drug discovery. Many candidate ligands possess flat aromatic surfaces and other molecular features that allow them to self-associate. In addition, non-specific binding to the target is a complicating feature of these interactions. Therefore, multiple equilibria are present and need to be accounted for in data analysis in order to obtain meaningful thermodynamic parameters. In order to address these issues we have systematically examined the bis-benzimidazole dye Hoechst 33258 (H33258) in terms of self-aggregation and binding to DNA oligonucleotides lacking any cognate minor groove A.T sites. This model system has been interrogated using isothermal titration calorimetry (ITC), circular dichroism (CD), fluorescence spectroscopy and pulsed gradient spin echo NMR. Three distinct binding events and ligand self-aggregation have been identified and, where possible, quantified. H33258 self-aggregation involves a step-wise aggregation mechanism, driven by stacking interactions. The DNA binding process includes two specific binding modes and non-specific DNA-templated H33258 stacking. We have written novel ITC data-fitting software (IC-ITC; freely available to the biophysics community), which simultaneously fits ligand aggregation and ligand-DNA binding. Here, this numerical analysis, which uses simulated annealing of complex calorimetric data representing multiple coupled equilibria, is described.

A microfabricated nanocalorimeter: design, characterization, and chemical calibration

A microfabricated titration calorimeter having nanowatt sensitivity is presented. The device is achieved by modifying a commercial, suspended-membrane, thin-film thermopile infrared sensor. Chemical reactions are studied by placing a 50.0 nL droplet of one reagent directly on the sensor and injecting nanoliter droplets of a second reagent through a micropipette by means of a pressure-driven droplet injector with 1% reliability in volume delivery. External thermal noise is minimized by a two-layer thermal shielding system. Evaporation is prevented by positioning the micropipette through a tiny hole in a cover glass, sealed by a drop of oil. The device is calibrated using two acid-base reactions: H2SO4 + HEPES buffer, and NaOH + HCl. The measured power sensitivity is 2.90(4) V/W, giving a detection limit of 22 nW. The 1/e time constant for a single injection is 1.1 s. The day-to-day power sensitivity is reproducible to approximately 2%. A computational model of the sensor reproduces the power sensitivity within 10% and the time constant within 20%. For a 50 nL sample and 0.8-1.5 nL titrant injection volumes, the heat uncertainty of 44 nJ corresponds to a 3sigma detection limit of 132 nJ, or the binding energy associated with 2.9 pM of IgG-protein A complex.