Affinity capillary electrophoresis on microchips

The present study shows that the application of the method of affinity capillary electrophoresis (ACE) to investigate interactions between ligands and their substrates can be realized on microchips. With ACE it is possible to characterize non-covalent molecular interactions (complexation and partition equilibria). Binding constants (K(B)) provide a measured value of the affinity of a ligand molecule to a substrate, which is basic information for the understanding of hormones, drugs and their targets, e.g. receptors in the human body. A microchip electrophoresis instrument equipped with a UV-detector and a home-built chip-station with electrochemical detection were used. ACE could be achieved with model solutions of neurotransmitters using sulfated beta-cyclodextrin (sCD) as substrate in a background buffer. This paper describes the advantages of microchip-ACE (MC-ACE) to traditional affinity capillary electrophoresis on a capillary. The results show that MC-ACE has great potential as a tool for fast scanning of interactions and to calculate binding constants of ligands with their substrates.     

Assessment of programs for ligand binding affinity prediction

The prediction of the binding free energy between a ligand and a protein is an important component in the virtual screening and lead optimization of ligands for drug discovery. To determine the quality of current binding free energy estimation programs, we examined FlexX, X-Score, AutoDock, and BLEEP for their performance in binding free energy prediction in various situations including cocrystallized complex structures, cross docking of ligands to their non-cocrystallized receptors, docking of thermally unfolded receptor decoys to their ligands, and complex structures with "randomized" ligand decoys. In no case was there a satisfactory correlation between the experimental and estimated binding free energies over all the datasets tested. Meanwhile, a strong correlation between ligand molecular weight-binding affinity correlation and experimental predicted binding affinity correlation was found. Sometimes the programs also correctly ranked ligands' binding affinities even though native interactions between the ligands and their receptors were essentially lost because of receptor deformation or ligand randomization, and the programs could not decisively discriminate randomized ligand decoys from their native ligands; this suggested that the tested programs miss important components for the accurate capture of specific ligand binding interactions.     

Multiple-injection affinity capillary electrophoresis to estimate binding constants of receptors to ligands

Multiple-injection affinity capillary electrophoresis (MIACE) is used to determine binding constants (K _b) between receptors and ligands using as model systems vancomycin and teicoplanin from Streptomyces orientalis and Actinoplanes teichomyceticus, respectively, and their binding to D-Ala-D-Ala peptides and carbonic anhydrase B (CAB. EC 4.2.1.1) and the binding of the latter to arylsulfonamides. A sample plug containing a non-interacting standard is first injected followed by multiple plugs of sample containing the receptor and then a final injection of sample containing a second standard. Between each injection of sample, a small plug of buffer is injected which contains an increasing concentration of ligand to effect separation between the multiple injections of sample. Electrophoresis is then carried out in an increasing concentration of ligand in the running buffer. Continued electrophoresis results in a shift in the migration time of the receptor in the sample plugs upon binding to their respective ligand. Analysis of the change in the relative migration time ratio (RMTR) or electrophoretic mobility (μ) of the resultant receptor–ligand complex relative to the non-interacting standards, as a function of the concentration of ligand yields a value for K _b. The MIACE technique is a modification in the ACE method that allows for the estimation of binding affinities between biological interactions on a timescale faster than that found for standard ACE. In addition sample volume requirements for the technique are reduced compared to traditional ACE assays. These findings demonstrate the advantage of using MIACE to estimate binding parameters between receptors and ligands.     

Towards a rational spacer design for bivalent inhibition of estrogen receptor

Estrogen receptors are known drug targets that have been linked to several kinds of cancer. The structure of the estrogen receptor ligand binding domain is available and reveals a homodimeric layout. In order to improve the binding affinity of known estrogen receptor inhibitors, bivalent compounds have been developed that consist of two individual ligands linked by flexible tethers serving as spacers. So far, binding affinities of the bivalent compounds do not surpass their monovalent counterparts. In this article, we focus our attention on the molecular spacers that are used to connect the individual ligands to form bivalent compounds, and describe their thermodynamic contribution during the ligand binding process. We use computational methods to predict structural and entropic parameters of different spacer structures. We find that flexible spacers introduce a number of effects that may interfere with ligand binding and possibly can be connected to the low binding affinities that have been reported in binding assays. Based on these findings, we try to provide guidelines for the design of novel molecular spacers.     

Concepts in receptor optimization: targeting the RGD peptide

Synthetic receptors have a wide range of potential applications, but it has been difficult to design low molecular weight receptors that bind ligands with high, "proteinlike" affinities. This study uses novel computational methods to understand why it is hard to design a high-affinity receptor and to explore the limits of affinity, with the bioactive peptide RGD as a model ligand. The M2 modeling method is found to yield excellent agreement with experiment for a known RGD receptor and then is used to analyze a series of receptors generated in silico with a de novo design algorithm. Forces driving binding are found to be systematically opposed by proportionate repulsions due to desolvation and entropy. In particular, strong correlations are found between Coulombic attractions and the electrostatic desolvation penalty and between the mean energy change on binding and the cost in configurational entropy. These correlations help explain why it is hard to achieve high affinity. The change in surface area upon binding is found to correlate poorly with affinity within this series. Measures of receptor efficiency are formulated that summarize how effectively a receptor uses surface area, total energy, and Coulombic energy to achieve affinity. Analysis of the computed efficiencies suggests that a low molecular weight receptor can achieve proteinlike affinity. It is also found that macrocyclization of a receptor can, unexpectedly, increase the entropy cost of binding because the macrocyclic structure further restricts ligand motion.     

EDTA and DTPA modified ligands as sequestering agents for uranyl decorporation

Synthesis of modified EDTA and DTPA ligands and determination of their binding affinities for the uranyl cation are described.Thanks to a screening method, based on a chromophoric complex displacement procedure, chelating properties were studied in aqueous media under various pH conditions for evaluation of their in vivo uranyl-removal efficacy. Each ligand showed a more or less pronounced affinity for uranium. Specific ligands based on EDTA or DTPA analogues containing sulfocatecholamide (CAMS) were found to exhibit a significant affinity towards uranyl ion in acidic, neutral or basic conditions.     

Ligand–Receptor Binding Affinities from Saturation Transfer Difference (STD) NMR Spectroscopy: The Binding Isotherm of STD Initial Growth Rates

The direct evaluation of dissociation constants (K_D) from the variation of saturation transfer difference (STD) NMR spectroscopy values with the receptor–ligand ratio is not feasible due to the complex dependence of STD intensities on the spectral properties of the observed signals. Indirect evaluation, by competition experiments, allows the determination of K_D, as long as a ligand of known affinity is available for the protein under study. Herein, we present a novel protocol based on STD NMR spectroscopy for the direct measurements of receptor–ligand dissociation constants (K_D) from single‐ligand titration experiments. The influence of several experimental factors on STD values has been studied in detail, confirming the marked impact on standard determinations of protein–ligand affinities by STD NMR spectroscopy. These factors, namely, STD saturation time, ligand residence time in the complex, and the intensity of the signal, affect the accumulation of saturation in the free ligand by processes closely related to fast protein–ligand rebinding and longitudinal relaxation of the ligand signals. The proposed method avoids the dependence of the magnitudes of ligand STD signals at a given saturation time on spurious factors by constructing the binding isotherms using the initial growth rates of the STD amplification factors, in a similar way to the use of NOE growing rates to estimate cross relaxation rates for distance evaluations. Herein, it is demonstrated that the effects of these factors are cancelled out by analyzing the protein–ligand association curve using STD values at the limit of zero saturation time, when virtually no ligand rebinding or relaxation takes place. The approach is validated for two well‐studied protein–ligand systems: the binding of the saccharides GlcNAc and GlcNAcβ1,4GlcNAc (chitobiose) to the wheat germ agglutinin (WGA) lectin, and the interaction of the amino acid L ‐tryptophan to bovine serum albumin (BSA). In all cases, the experimental K_D measured under different experimental conditions converged to the thermodynamic values. The proposed protocol allows accurate determinations of protein–ligand dissociation constants, extending the applicability of the STD NMR spectroscopy for affinity measurements, which is of particular relevance for those proteins for which a ligand of known affinity is not available.     

Exploring the subtleties of drug-receptor interactions: the case of matrix metalloproteinases

By solving high-resolution crystal structures of a large number (14 in this case) of adducts of matrix metalloproteinase 12 (MMP12) with strong, nanomolar, inhibitors all derived from a single ligand scaffold, it is shown that the energetics of the ligand-protein interactions can be accounted for directly from the structures to a level of detail that allows us to rationalize for the differential binding affinity between pairs of closely related ligands. In each case, variations in binding affinities can be traced back to slight improvements or worsening of specific interactions with the protein of one or more ligand atoms. Isothermal calorimetry measurements show that the binding of this class of MMP inhibitors is largely enthalpy driven, but a favorable entropic contribution is always present. The binding enthalpy of acetohydroxamic acid (AHA), the prototype zinc-binding group in MMP drug discovery, has been also accurately measured. In principle, this research permits the planning of either improved inhibitors, or inhibitors with improved selectivity for one or another MMP. The present analysis is applicable to any drug target for which structural information on adducts with a series of homologous ligands can be obtained, while structural information obtained from in silico docking is probably not accurate enough for this type of study.     

Estrogen-derived steroidal metal complexes: agents for cellular delivery of metal centers to estrogen receptor-positive cells

Targeted cellular delivery of drugs to specific tissues is an important goal in biomedical chemistry. Achieving this requires harnessing and applying molecular-level recognition events prevalent in (or specific to) the desired tissue type. Tissues rich in estrogen receptors (ERs), which include many types of breast cancer, accumulate molecules that have high binding affinities for these receptors. Therefore, molecules that (i) bind to the ER, (ii) have favorable cellular transport properties, and (iii) contain a second functionality (such as a center that may be used for diagnostic imaging or medical therapy) are exciting synthetic targets in the field of drug delivery. To this end, we have prepared a range of metallo-estrogens based on 17alpha-ethynylestradiol and examined their binding to the ER both as isolated receptor and in whole cell assays (ER positive MCF-7 cells). Estrogens functionalized with metal binding units are prepared by palladium-catalyzed cross-coupling reactions and a wide range of metal centers introduced readily. All the compounds prepared and tested exhibit effective binding to the estrogen receptor and are delivered across the cell membrane into MCF-7 cells. In the whole cell assays, despite their monocationic nature, the palladium and platinum complexes prepared exhibit similar (and even enhanced) receptor binding affinities compared to their corresponding neutral free ligands. It is unprecedented for a higher ER binding affinity to be observed for a cationic complex than for its metal-free ligand.     

Modeling multiple species of nicotine and deschloroepibatidine interacting with alpha4beta2 nicotinic acetylcholine receptor: from microscopic binding to phenomenological binding affinity

A variety of molecular modeling, molecular docking, and first-principles electronic structure calculations were performed to study how the alpha4beta2 nicotinic acetylcholine receptor (nAChR) binds with different species of two typical agonists, (S)-(-)-nicotine and (R)-(-)-deschloroepibatidine, each of which is distinguished by different free bases and protonation states. On the basis of these results, predictions were made regarding the corresponding microscopic binding free energies. Hydrogen-bonding and cation-pi interactions between the receptor and the respective ligands were found to be the dominant factors differentiating the binding strengths of different microscopic binding species. The calculated results and analyses demonstrate that, for each agonist, all the species are interchangeable and can quickly achieve a thermodynamic equilibrium in solution and at the nAChR binding site. This allows quantitation of the equilibrium concentration distributions of the free ligand species and the corresponding microscopic ligand-receptor binding species, their pH dependence, and their contributions to the phenomenological binding affinity. The predicted equilibrium concentration distributions, pK(a) values, absolute phenomenological binding affinities, and their pH dependence are all in good agreement with available experimental data, suggesting that the computational strategy from the microscopic binding species and affinities to the phenomenological binding affinity is reliable for studying alpha4beta2 nAChR-ligand binding. This should provide valuable information for future rational design of drugs targeting nAChRs. The general strategy of the "from-microscopic-to-phenomenological" approach for studying interactions of alpha4beta2 nAChRs with (S)-(-)-nicotine and (R)-(-)-deschloroepibatidine may also be useful in studying other types of ligand-protein interactions involving multiple molecular species of a ligand and in associated rational drug design.     

Mechanistic Insight into Nanomolar Binding of Multivalent Neoglycopeptides to Wheat Germ Agglutinin

Multivalent carbohydrate–protein interactions are frequently involved in essential biological recognition processes. Accordingly, multivalency is often also exploited for the design of high‐affinity lectin ligands aimed at the inhibition of such processes. In a previous study (D. Schwefel et al., J. Am. Chem. Soc. 2010 , 132, 8704–8719) we identified a tetravalent cyclopeptide‐based ligand with nanomolar affinity to the model lectin wheat germ agglutinin (WGA). To unravel the structural features of this ligand required for high‐affinity binding to WGA, we synthesized a series of cyclic and linear neoglycopeptides that differ in their conformational freedom as well as the number of GlcNAc residues. Combined evidence from isothermal titration calorimetry (ITC), enzyme‐linked lectin assays (ELLA), and dynamic light scattering (DLS) revealed different binding modes of tetra‐ and divalent ligands and that conformational preorganization of the ligands by cyclization is not a prerequisite for achieving high binding affinities. The high affinities of the tetravalent ligands rather stem from their ability to form crosslinks between several WGA molecules. The results illustrate that binding affinities and mechanisms are strongly dependent on the used multivalent system which offers opportunities to tune and control binding processes.     

New approach to molecular docking and its application to virtual screening of chemical databases

This paper describes the validation of a molecular docking method and its application to virtual database screening. The code flexibly docks ligand molecules into rigid receptor structures using a tabu search methodology driven by an empirically derived function for estimating the binding affinity of a protein-ligand complex. The docking method has been tested on 70 ligand-receptor complexes for which the experimental binding affinity and binding geometry are known. The lowest energy geometry produced by the docking protocol is within 2.0 A root mean square of the experimental binding mode for 79% of the complexes. The method has been applied to the problem of virtual database screening to identify known ligands for thrombin, factor Xa, and the estrogen receptor. A database of 10,000 randomly chosen "druglike" molecules has been docked into the three receptor structures. In each case known receptor ligands were included in the study. The results showed good separation between the predicted binding affinities of the known ligand set and the database subset.     

Lessons learned from participating in D3R 2016 Grand Challenge 2: compounds targeting the farnesoid X receptor

D3R 2016 Grand Challenge 2 focused on predictions of binding modes and affinities for 102 compounds against the farnesoid X receptor (FXR). In this challenge, two distinct methods, a docking-based method and a template-based method, were employed by our team for the binding mode prediction. For the new template-based method, 3D ligand similarities were calculated for each query compound against the ligands in the co-crystal structures of FXR available in Protein Data Bank. The binding mode was predicted based on the co-crystal protein structure containing the ligand with the best ligand similarity score against the query compound. For the FXR dataset, the template-based method achieved a better performance than the docking-based method on the binding mode prediction. For the binding affinity prediction, an in-house knowledge-based scoring function ITScore2 and MM/PBSA approach were employed. Good performance was achieved for MM/PBSA, whereas the performance of ITScore2 was sensitive to ligand composition, e.g. the percentage of carbon atoms in the compounds. The sensitivity to ligand composition could be a clue for the further improvement of our knowledge-based scoring function.     

Electrospray ionization of nucleic acid aptamer/small molecule complexes for screening aptamer selectivity

Molecular recognition of small molecule ligands by the nucleic acid aptamers for tobramycin, ATP, and FMN has been examined using electrospray ionization mass spectrometry (ESI-MS). Mass spectrometric data for binding stoichiometry and relative binding affinity correlated well with solution data for tobramycin aptamer complexes, in which aptamer/ligand interactions are mediated by hydrogen bonds. For the ATP and FMN aptamers, where ligand interactions involve both hydrogen bonding and significant pi-stacking, the relative binding affinities determined by MS did not fully correlate with results obtained from solution experiments. Some high-affinity aptamer/ligand complexes appeared to be destabilized in the gas phase by internal Coulombic repulsion. In CAD experiments, complexes with a greater number of intermolecular hydrogen bonds exhibited greater gas-phase stability even in cases when solution binding affinities were equivalent. These results indicate that in at least some cases, mass spectrometric data on aptamer/ligand binding affinities should be used in conjunction with complementary techniques to fully assess aptamer molecular recognition properties.     

Protein‐specific force field derived from the fragment molecular orbital method can improve protein–ligand binding interactions

Accurate computational estimate of the protein–ligand binding affinity is of central importance in rational drug design. To improve accuracy of the molecular mechanics (MM) force field (FF) for protein–ligand simulations, we use a protein‐specific FF derived by the fragment molecular orbital (FMO) method and by the restrained electrostatic potential (RESP) method. Applying this FMO‐RESP method to two proteins, dodecin, and lysozyme, we found that protein‐specific partial charges tend to differ more significantly from the standard AMBER charges for isolated charged atoms. We did not see the dependence of partial charges on the secondary structure. Computing the binding affinities of dodecin with five ligands by MM PBSA protocol with the FMO‐RESP charge set as well as with the standard AMBER charges, we found that the former gives better correlation with experimental affinities than the latter. While, for lysozyme with five ligands, both charge sets gave similar and relatively accurate estimates of binding affinities. © 2013 Wiley Periodicals, Inc.     

A general technique to rank protein-ligand binding affinities and determine allosteric versus direct binding site competition in compound mixtures

To realize the full potential of combinatorial chemistry-based drug discovery, generic and efficient tools must be developed that apply the strengths of diversity-oriented chemical synthesis to the identification and optimization of lead compounds for disease-associated protein targets. We report an affinity selection-mass spectrometry (AS-MS) method for protein-ligand affinity ranking and the classification of ligands by binding site. The method incorporates the following steps: (1) an affinity selection stage, where protein-binding compounds are selected from pools of ligands in the presence of varying concentrations of a competitor ligand, (2) a first chromatography stage to separate unbound ligands from protein-ligand complexes, and (3) a second chromatography stage to dissociate the ligands from the complexes for identification and quantification by MS. The ability of the competitor ligand to displace a target-bound library member, as measured by MS, reveals the binding site classification and affinity ranking of the mixture components. The technique requires no radiolabel incorporation or direct biochemical assay, no modification or immobilization of the compounds or target protein, and all reaction components, including any buffers or cofactors required for protein stability, are free in solution. We demonstrate the method for several compounds of wide structural variety against representatives of the most important protein classes in contemporary drug discovery, including novel ATP-competitive and allosteric inhibitors of the Akt-1 (PKB) and Zap-70 kinases, and previously undisclosed antagonists of the M(2) muscarinic acetylcholine receptor, a G-protein coupled receptor (GPCR). The theoretical basis of the technique is analyzed mathematically, allowing quantitative estimation of binding affinities and, in the case of allosteric interaction, absolute determination of binding cooperativity. The method is readily applicable to high-throughput screening hit triage, combinatorial library-based affinity optimization, and developing structure-activity relationships among multiple ligands to a given receptor.     

Solution and structural investigations of ligand preorganization in trivalent lanthanide complexes of bicyclic malonamides

This report describes an investigation into the coordination chemistry of trivalent lanthanides in solution and the solid state with acyclic and preorganized bicyclic malonamide ligands. Two experimental investigations were performed: solution binding affinities were determined through single-phase spectrophotometric titrations and the extent of conformational change upon binding was investigated with single-crystal X-ray crystallography. Both experimental methods compare the bicyclic malonamide (BMA), which is designed to be preorganized for binding trivalent lanthanides, to an analogous acyclic malonamide. Results from the spectrophotometric titrations indicate that BMA exhibits a 10-100x increase in binding affinity to Ln(III) over acyclic malonamide. In addition, BMA forms compounds with high ligand-metal ratios, even when competing with water and nitrate ligands for binding sites. The crystal structures exhibit no significant differences in the nature of the binding between Ln(III) and the BMA or acyclic malonamide. These results support the conclusion that rational ligand design can lead to compounds that enhance the binding affinities within a ligand class.     

Biological properties of opioid peptides replacing Tyr at position 1 by 2,6-dimethyl-Tyr.

To understand the effect of the replacement of Tyr residue at position 1 in opioid peptides by 2,6-dimethyl-Tyr (Dmt) on the biological property, chiral (D or L) Dmt1 analogs of Leu-enkephalin (Enk) and Tyr-D-Arg-Phe-beta Ala-NH2 (YRFB) were synthesized and their enzymatic stabilities, in vitro bioactivities and receptor binding affinities compared with those of parent peptides. [L-Dmt1]Enk (1) exhibited 4-fold higher stability against aminopeptidase-M and possessed dramatically increased activities in guinea pig ilium (GPI) (187-fold) and mouse vas deferens (MVD) (131-fold) assays, and in rat brain receptor binding assays (356-fold at mu receptor and 46-fold at delta receptor) as compared to Enk. [L-Dmt1]YRFB (3) also exhibited increased activities in GPI (46-fold) and MVD (177-fold) assays, and in the binding assays (69-fold at mu receptro and 341-fold at delta receptor) as compared to the parent peptide. [D-Dmt1]Enk (2) and [D-Dmt1]YRFB (4) exhibited activities with diminished or lesser potency than the parent peptide in all assays. These results indicate that there is a tendency for mu affinity to be enhanced more than delta affinity with introduction of L-Dmt into delta ligand peptide (Enk), and for delta affinity to be enhanced more than mu affinity in case of mu ligand peptide (YRFB), resulting in reduced receptor selectivities at the receptors.     

Large scale free energy calculations for blind predictions of protein–ligand binding: the D3R Grand Challenge 2015

We describe binding free energy calculations in the D3R Grand Challenge 2015 for blind prediction of the binding affinities of 180 ligands to Hsp90. The present D3R challenge was built around experimental datasets involving Heat shock protein (Hsp) 90, an ATP-dependent molecular chaperone which is an important anticancer drug target. The Hsp90 ATP binding site is known to be a challenging target for accurate calculations of ligand binding affinities because of the ligand-dependent conformational changes in the binding site, the presence of ordered waters and the broad chemical diversity of ligands that can bind at this site. Our primary focus here is to distinguish binders from nonbinders. Large scale absolute binding free energy calculations that cover over 3000 protein–ligand complexes were performed using the BEDAM method starting from docked structures generated by Glide docking. Although the ligand dataset in this study resembles an intermediate to late stage lead optimization project while the BEDAM method is mainly developed for early stage virtual screening of hit molecules, the BEDAM binding free energy scoring has resulted in a moderate enrichment of ligand screening against this challenging drug target. Results show that, using a statistical mechanics based free energy method like BEDAM starting from docked poses offers better enrichment than classical docking scoring functions and rescoring methods like Prime MM-GBSA for the Hsp90 data set in this blind challenge. Importantly, among the three methods tested here, only the mean value of the BEDAM binding free energy scores is able to separate the large group of binders from the small group of nonbinders with a gap of 2.4 kcal/mol. None of the three methods that we have tested provided accurate ranking of the affinities of the 147 active compounds. We discuss the possible sources of errors in the binding free energy calculations. The study suggests that BEDAM can be used strategically to discriminate binders from nonbinders in virtual screening and to more accurately predict the ligand binding modes prior to the more computationally expensive FEP calculations of binding affinity.     

Estimating protein-ligand binding affinity using high-throughput screening by NMR

Many of today's drug discovery programs use high-throughput screening methods that rely on quick evaluations of protein activity to rank potential chemical leads. By monitoring biologically relevant protein-ligand interactions, NMR can provide a means to validate these discovery leads and to optimize the drug discovery process. NMR-based screens typically use a change in chemical shift or line width to detect a protein-ligand interaction. However, the relatively low throughput of current NMR screens and their high demand on sample requirements generally makes it impractical to collect complete binding curves to measure the affinity for each compound in a large and diverse chemical library. As a result, NMR ligand screens are typically limited to identifying candidates that bind to a protein and do not give any estimate of the binding affinity. To address this issue, a methodology has been developed to rank binding affinities for ligands based on NMR screens that use 1D (1)H NMR line-broadening experiments. This method was demonstrated by using it to estimate the dissociation equilibrium constants for twelve ligands with the protein human serum albumin (HSA). The results were found to give good agreement with previous affinities that have been reported for these same ligands with HSA.