Accounting for triplet and saturation effects in FCS measurements

Fluorescence correlation spectroscopy (FCS) is an increasingly important tool for determining low concentrations and dynamics of molecules in solution. Oftentimes triplet transitions give rise to fast blinking effects, which are accounted for by including an exponential term in the fitting of the autocorrelation function (ACF). In such cases, concomitant saturation effects also modify the amplitude and shape of the remaining parts of the ACF. We review studies of triplet and saturation effects in FCS and present a simple procedure to obtain more accurate results of particle concentrations and diffusional dynamics in experiments where triplet kinetics are evident, or where moderate laser powers approaching saturation levels are used, for example, to acquire sufficient photon numbers when observation times are limited. The procedure involves use of a modified function for curve-fitting the ACF, but there are no additional fitting parameters. Instead, a simple calibration of the total fluorescence count rate as a function of relative laser power is fit to a polynomial, and the non-linear components of this fit, together with the relative laser power used for the FCS measurement, are used to specify the magnitude of additional terms in the fitting function. Monte Carlo simulations and experiments using Alexa dyes and quantum dots, with continuous and pulsed laser excitation, demonstrate the application of the modified fitting procedure with first order correction terms, in the regime where distortions in the ACF due to photobleaching and detector dead time are small compared to those of fluorescence saturation and triplet photophysics.     

Homology modeling of opioid receptor-ligand complexes using experimental constraints

Opioid receptors interact with a variety of ligands, including endogenous peptides, opiates, and thousands of synthetic compounds with different structural scaffolds. In the absence of experimental structures of opioid receptors, theoretical modeling remains an important tool for structure-function analysis. The combination of experimental studies and modeling approaches allows development of realistic models of ligand-receptor complexes helpful for elucidation of the molecular determinants of ligand affinity and selectivity and for understanding mechanisms of functional agonism or antagonism. In this review we provide a brief critical assessment of the status of such theoretical modeling and describe some common problems and their possible solutions. Currently, there are no reliable theoretical methods to generate the models in a completely automatic fashion. Models of higher accuracy can be produced if homology modeling, based on the rhodopsin X-ray template, is supplemented by experimental structural constraints appropriate for the active or inactive receptor conformations, together with receptor-specific and ligand-specific interactions. The experimental constraints can be derived from mutagenesis and cross-linking studies, correlative replacements of ligand and receptor groups, and incorporation of metal binding sites between residues of receptors or receptors and ligands. This review focuses on the analysis of similarity and differences of the refined homology models of mu, delta, and kappa-opioid receptors in active and inactive states, emphasizing the molecular details of interaction of the receptors with some representative peptide and nonpeptide ligands, underlying the multiple modes of binding of small opiates, and the differences in binding modes of agonists and antagonists, and of peptides and alkaloids.     

Quantifying the association and dissociation rates of unlabelled antagonists at the muscarinic M3 receptor

Slow receptor dissociation kinetics has been implicated in the long clinical duration of action of the muscarinic receptor antagonist tiotropium. However, despite the potential benefits of new drugs with slow dissociation kinetics, the rate parameters of new compounds are seldom measured due to technical difficulties and financial implications associated with radiolabeling multiple ligands. Here we describe the development and optimisation of a medium throughput assay which is capable of measuring the kinetic parameters of novel, unlabelled compounds. Radioligand binding studies were performed with membranes derived from CHO cells recombinantly expressing the human M(3) muscarinic receptor.Initial characterisation of the radioligand [(3)H]-NMS yielded on and off rates of 4.1+/-0.2 x 10(8) M(-1) min(-1) and 0.015+/-0.0005 min(-1), respectively. The specific binding of [(3)H]-NMS was measured over time in the presence and absence of several concentrations of unlabelled competitor compounds. These data were analysed using a competition kinetic model to provide on and off rates for the unlabelled competitor. Comparison of the kinetically derived Kd (k(off)/k(on)) with K(i) values generated at equilibrium showed an excellent correlation (r(2)=0.99), providing good validation of the method. The on and off rates were also used in theoretical computer simulations to successfully predict the effect of incubation time on apparent IC(50) values. This study demonstrates that a medium-throughput competition kinetic binding assay can be used to determine accurate on and off rates of unlabelled compounds, providing the opportunity to optimise for kinetic parameters early in the drug discovery process.     

Equilibrium Gel Filtration to Measure Plasma Protein Binding of Very Highly Bound Drugs

For very highly bound drugs (fu < 2%), the determination of the unbound fraction in plasma (fu) and a reliable estimation of protein-binding differences across species, populations, or concentrations is challenging. The difficulty is not mostly assay sensitivity but rather experimental bias. In equilibrium gel filtration (EGF)—opposite to the commonly used methods—the amount bound at a set-free concentration is determined. Therefore, signals and differences are bigger for more highly protein-bound drugs. We describe here a new experimental set-up developed to investigate binding in plasma and compare results with those obtained with standard methods for nine Novartis compounds. The method was then applied for two drugs for which it was challenging to obtain precise data with standard methods: midostaurin and siponimod. Despite the very high binding (fu ≤ 0.1%), precise estimation of up to 10-fold species differences relevant for safety assessments was possible. Evidence for the correctness of the data by comparison with other pharmokinetics parameters is provided. Sensitivity to potential sources of experimental bias is compared with standard methods and advantages and disadvantages of the methods are discussed. In conclusion, EGF allows accurate determination of fu for very highly bound drugs and differentiation even above 99.9% of binding.     

Ligand-receptor interactions in live cells by fluorescence correlation spectroscopy

Receptor binding studies most often require the use of radioactively labeled ligands. In certain cases, the numbers of receptors are few per cell and no specific binding is detected because of a high background. Specific interactions between certain ligands (e.g. peptides, hormones, natural products) and their receptors are, therefore, often overlooked by the conventional binding technique. Fluorescence correlation spectroscopy (FCS) allows detection of the interaction of ligands with receptors in their native environment in live cells in a tiny confocal volume element (0.2 fl) at single-molecule detection sensitivity. This technique permits the identification of receptors which were not possible before to detect by isotope labeling. The beauty of the FCS technique is that there is no need for separating an unbound ligand from a bound one to calculate the receptor bound and free ligand fractions. This review will show FCS as a sensitive and a rapid technique to study ligand-receptor interaction in live cells and will demonstrate that the FCS-analysis of ligand-receptor interactions in live cells fulfils all the criteria of a ligand binding to its receptor i.e. it is able to provide information on the affinity and specificity of a ligand, binding constant, association and dissociation rate constants as well as the number and mobility of receptors carrying a fluorescently labeled ligand. This review is of pharmaceutical significance since it will provide insights on how FCS can be used as a rapid technique for studying ligand-receptor interactions in cell cultures, which is one step forward towards a high throughput drug screening in cell cultures.     

Design and quantitative structure-activity relationship of 3-amidinobenzyl-1H-indole-2-carboxamides as potent,nonchiral, and selective inhibitors of blood coagulation factor Xa

A series of 138 nonchiral 3-amidinobenzyl-1H-indole-2-carboxamides and analogues as inhibitors of the blood coagulation enzyme factor Xa (fXa) were designed, synthesized, and investigated by X-ray structure analysis and 3D quantitative structure-activity relationship (QSAR) studies (CoMFA, CoMSIA) in order to identify important protein-ligand interactions responsible for biological affinity and selectivity. Several compounds from this series are highly potent and selective inhibitors of this important enzyme linking extrinsic and intrinsic coagulation pathways. To rationalize biological affinity and to provide guidelines for further design, all compounds were docked into the factor Xa binding site. Those docking studies were based on X-ray structures of factor Xa in complex with literature-known inhibitors. It was possible to validate those binding modes by four X-ray crystal structures of representative ligands in factor Xa, while one ligand was additionally crystallized in trypsin to rationalize requirements for selective factor Xa inhibition. The 3D-QSAR models based on a superposition rule derived from these docking studies were validated using conventional and cross-validated r(2) values using the leave-one-out method and repeated analyses using two randomly chosen cross-validation groups plus randomization of biological activities. This led to consistent and highly predictive 3D-QSAR models with good correlation coefficients for both CoMFA and CoMSIA, which were found to correspond to experimentally determined factor Xa binding site topology in terms of steric, electrostatic, and hydrophobic complementarity. Subsets selected as smaller training sets using 2D fingerprints and maximum dissimilarity methods resulted in 3D-QSAR models with remarkable correlation coefficients and a high predictive power. The final quantitative SAR information agrees with all experimental data for the binding topology and thus provides reasonable activity predictions for novel factor Xa inhibitors.     

Artificial intelligence in virtual screening: Models versus experiments

A typical drug discovery project involves identifying active compounds with significant binding potential for selected disease-specific targets. Experimental high-throughput screening (HTS) is a traditional approach to drug discovery, but is expensive and time-consuming when dealing with huge chemical libraries with billions of compounds. The search space can be narrowed down with the use of reliable computational screening approaches. In this review, we focus on various machine-learning (ML) and deep-learning (DL)-based scoring functions developed for solving classification and ranking problems in drug discovery. We highlight studies in which ML and DL models were successfully deployed to identify lead compounds for which the experimental validations are available from bioassay studies.     

Dye-labeled benzodiazepines: development of small ligands for receptor binding studies using fluorescence correlation spectroscopy

To investigate benzodiazepine receptor binding studies by fluorescence correlation spectroscopy (FCS), the four fluorophores fluorescein, tetramethylrhodamine, Oregon Green 488, and Alexa 532 were coupled to the benzodiazepine Ro 07-1986/602 (Ro). Binding assays to polyclonal antibodies to benzodiazepines and at the native benzodiazepine receptor on the membrane of rat hippocampal neurons were established to examine the dye-labeled ligands for their benzodiazepine character and their binding behavior. Both the fluorescein and the Oregon Green488 moiety led to a loss of the benzodiazepine receptor binding of the corresponding Ro derivatives. Antibody recognition and interactions to the receptor were observed for the tetramethylrhodamine derivative (K(D) = 96.0 +/- 9.5 nM) but with a high amount of nonspecific binding at the cell membrane of about 50%. In saturation experiments a K(D) value of 97.2 +/- 8.5 nM was found for the Alexa Fluor 532 derivative-antibody interaction. Investigation of the binding of this ligand to the benzodiazepine receptor in FCS cell measurements led to confirmation of high specific binding behavior with a K(D) value of 9.9 +/- 1.9 nM. A nonspecific binding of <10% was observed after coincubation with 1 microM of midazolam. The different properties of the labeled benzodiazepine derivatives and the requirements of the fluorophore in small dye-labeled ligands in FCS binding studies, at the membrane of living cells, are discussed.     

Computational modeling of the sugar-lectin interaction

In the last few years numerous experimental studies have shed light onto the details of the lectin-carbohydrate interaction. X-ray crystallography and NMR spectroscopy have been used to elucidate the structures of lectins, sugars, and their complexes. In addition, an increasing number of experimental methods has been employed to determine the thermodynamic and kinetic parameters of the binding process. Based on this experimental data, computational methods have been developed to model and predict these interactions. A plethora of techniques from Molecular Modeling and Computational Chemistry have been applied to the problem and current models achieve high-quality predictions. These successes are based on both new theoretical approaches and reliable experimental data. The aim of the present article is to outline the most relevant computational and experimental methods applied in the field of lectin-carbohydrate interaction and to give an overview of the current state of the art in the modeling of these interactions with a focus on plant lectins.     

Identification of non-phosphate-containing small molecular weight inhibitors of the tyrosine kinase p56 Lck SH2 domain via in silico screening against the pY + 3 binding site

The protein p56 lymphoid T cell tyrosine kinase (Lck) is predominantly expressed in T lymphocytes where it plays a critical role in T-cell-mediated immune response. Lck participates in phosphotyrosine-dependent protein-protein interactions through its modular binding unit, the Src homology-2 (SH2) domain. Accordingly, virtual screening methods combined with experimental assays were used to identify small molecular weight nonpeptidic compounds that block Lck SH2 domain-dependent interactions. Virtual screening included scoring normalization procedures and postdocking structural clustering that is shown to facilitate the selection of active compounds. By targeting the well-defined hydrophobic binding pocket known to impart specificity on Lck-protein interactions (i.e., pY + 3 site), inhibitors of the Lck SH2 domain were discovered that omit the phosphotyrosine (pY) or related moieties. The 34 out of 196 computationally selected compounds were shown to inhibit Lck SH2 domain association with phosphorylated immunoreceptor tyrosine based activation motifs peptide. Twenty-four of the active compounds were further tested for their ability to modulate biological function. Thirteen of these compounds showed inhibitory activity in mixed lymphocyte culture assay. Fluorescence titration experiments on four of these active compounds further verified their binding to the SH2 domain. Because of their simple chemical structures, these small organic compounds have the potential to act as lead compounds for the development of novel immunosuppressant drugs.     

Do aberrant crypt foci have predictive value for the occurrence of colorectal tumours? Potential of gene expression profiling in tumours.

The effects of different dietary compounds on the formation of aberrant crypt foci (ACF) and colorectal tumours and on the expression of a selection of genes were studied in rats. Azoxymethane-treated male F344 rats were fed either a control diet or a diet containing 10% wheat bran (WB), 0.2% curcumin (CUR), 4% rutin (RUT) or 0.04% benzyl isothiocyanate (BIT) for 8 months. ACF were counted after 7, 15 and 26 weeks. Tumours were scored after 26 weeks and 8 months. We found that the WB and CUR diets inhibited the development of colorectal tumours. In contrast, the RUT and BIT diets rather enhanced (although not statistically significantly) colorectal carcinogenesis. In addition, the various compounds caused different effects on the development of ACF. In most cases the number or size of ACF was not predictive for the ultimate tumour yield. The expression of some tumour-related genes was significantly different in tumours from the control group as compared to tumours from the treated groups. It was concluded that WB and CUR, as opposed to RUT and BIT, protects against colorectal cancer and that ACF are unsuitable as biomarker for colorectal cancer. Effects of the different dietary compounds on metalloproteinase 1 (TIMP-1) expression correlated well with the effects of the dietary compounds on the ultimate tumour yield.     

Anticoagulation factor I, a snaclec (snake C-type lectin) from Agkistrodon acutus venom binds to FIX as well as FX: Ca2+ induced binding data

Anticoagulation factor I (ACF I), a snake C-type lectin (snaclec) from the venom of Agkistrodon acutus binds specifically with activated factor X (FXa) in a Ca2+-dependent manner and prolongs the blood-clotting time in vitro. In this study, the inhibition of the coagulation pathway by ACF I was measured in vivo by activated partial thromboplastin time and prothrombin time assays and the binding of ACF I to factor IX (FIX) was investigated by native PAGE and surface plasmon resonance. The results indicate that ACF I inhibits both intrinsic and extrinsic coagulation pathways, but does not inhibit thrombin activity. ACF I also binds FIX in a Ca2+-dependent manner and their maximal binding occurs at 0.25 mM Ca2+. ACF I has a higher binding-affinity to FIX than to FX. Ca2+ is required to maintain in vivo function of FIX Gla domain for its recognition of ACF I. However, Ca2+ at high concentrations (>0.25 mM) inhibits the binding of ACF I to FIX. Ca2+ functions as a switch for the binding between ACF I and FIX. The results suggest that the binding of ACF I with FIX may play a dominant role in the anticoagulation activity of ACF I in vivo.