Determination of protein-ligand binding affinity by NMR: observations from serum albumin model systems

The usefulness of bovine serum albumin (BSA) as a model protein for testing NMR methods for the study of protein-ligand interactions is discussed. Isothermal titration calorimetry established the binding affinity and stoichiometry of the specific binding site for L-tryptophan, D-tryptophan, naproxen, ibuprofen, salicylic acid and warfarin. The binding affinities of the same ligands determined by NMR methods are universally weaker (larger KD). This is because the NMR methods are susceptible to interference from additional non-specific binding. The L-tryptophan-BSA and naproxen-BSA systems were the best behaved model systems.     

Rapid estimation of relative protein-ligand binding affinities using a high-throughput version of MM-PBSA

By employing a modified protocol of the Molecular Mechanics with Poisson-Boltzmann Surface Area (MM-PBSA) methodology we substantially decrease the required computation time for calculating relative estimates of protein-ligand binding affinities. The modified method uses a generalized Born implicit solvation model during molecular dynamics to enhance conformational sampling as well as a very efficient Poisson-Boltzmann solver and a computational design based on a distributed-computing paradigm. This construction allows for reduction of the computational cost of the calculations by roughly 2 orders of magnitude compared to the traditional formulation of MM-PBSA. With this high-throughput version of MM-PBSA we show that one can produce efficient physics-based estimates of relative binding free energies with reasonable correlation to experimental data and a total computation time that is sufficiently low such that an industrially relevant throughput can be realized given currently accessible computing resources. We demonstrate this approach by performing a comparison of different MM-PBSA implementations on a set of 18 ligands for the protein target urokinase.     

Integration of NMR and high-throughput screening

NMR-based screening has become a powerful method for the identification and analysis of low-molecular weight organic compounds that bind to protein targets and can be utilized in drug discovery programs. In particular, heteronuclear NMR-based screening can yield information about both the affinity and binding location of potential lead compounds. In addition, heteronuclear NMR-based screening has wide applications in complementing and facilitating conventional high-throughout screening programs. This article will describe several strategies for the integration of NMR-based screening and high-throughput screening. The marriage of these two techniques promises to be of tremendous benefit in the triage of hits that come from HTS, and can aid the medicinal chemist in the identification of quality leads that have high potential for further optimization.     

Multi-selective one dimensional proton NMR experiments for rapid screening and binding affinity measurements

High-throughput ligand-based proton NMR screening performed in the presence of a spy molecule and a control molecule is a valuable tool for identifying drug leads. A limitation of the technique is represented by the severe overlap encountered in the screening of large chemical mixtures. An approach for overcoming this overlap problem is the use of multi-selective R(1) filtered and COSY or TOCSY experiments. Application of this methodology to compounds binding to the Sudlow site I of human serum albumin is presented. The screening is performed by simply monitoring the intensity of two signals. The precise measurement of the relative intensity of the two resonances permits determination of the binding constant of the NMR-hit. For a simple competition binding mechanism, the rapidly-derived NMR binding constants are in good agreement with the values derived from full-titration ITC and fluorescence spectroscopy measurements.     

Information theory-based scoring function for the structure-based prediction of protein-ligand binding affinity

The development and validation of a new knowledge based scoring function (SIScoreJE) to predict binding energy between proteins and ligands is presented. SIScoreJE efficiently predicts the binding energy between a small molecule and its protein receptor. Protein-ligand atomic contact information was derived from a Non-Redundant Data set (NRD) of over 3000 X-ray crystal structures of protein-ligand complexes. This information was classified for individual "atom contact pairs" (ACP) which is used to calculate the atomic contact preferences. In addition to the two schemes generated in this study we have assessed a number of other common atom-type classification schemes. The preferences were calculated using an information theoretic relationship of joint entropy. Among 18 different atom-type classification schemes "ScoreJE Atom Type set2" (SATs2) was found to be the most suitable for our approach. To test the sensitivity of the method to the inclusion of solvent, Single-body Solvation Potentials (SSP) were also derived from the atomic contacts between the protein atom types and water molecules modeled using AQUARIUS2. Validation was carried out using an evaluation data set of 100 protein-ligand complexes with known binding energies to test the ability of the scoring functions to reproduce known binding affinities. In summary, it was found that a combined SSP/ScoreJE (SIScoreJE) performed significantly better than ScoreJE alone, and SIScoreJE and ScoreJE performed better than GOLD::GoldScore, GOLD::ChemScore, and XScore.     

A high-throughput phage display screening method using a combination of real-time PCR and affinity chromatography

Phage display is one of the best methods to identify drug targets, although technical problems including imprecision in quantifying phage and false-positive results are common. To address these difficulties, we propose two methods to more rapidly identify drug-binding phage particles. First, quantification of phage using SYBR Green Real-time PCR significantly improved accuracy and reproducibility. Second, affinity-column chromatography for selection of drug-binding phage particles concentrated particles more than a 96-well plate, making a phage amplification step, which can bias phage distribution, unnecessary. The methods proposed here should be suitable for high-throughput phage-display screenings and ultimately lead to more rapid identification of drug targets.     

Virtual screening using protein-ligand docking: avoiding artificial enrichment

This study addresses a number of topical issues around the use of protein-ligand docking in virtual screening. We show that, for the validation of such methods, it is key to use focused libraries (containing compounds with one-dimensional properties, similar to the actives), rather than "random" or "drug-like" libraries to test the actives against. We also show that, to obtain good enrichments, the docking program needs to produce reliable binding modes. We demonstrate how pharmacophores can be used to guide the dockings and improve enrichments, and we compare the performance of three consensus-ranking protocols against ranking based on individual scoring functions. Finally, we show that protein-ligand docking can be an effective aid in the screening for weak, fragment-like binders, which has rapidly become a popular strategy for hit identification. All results presented are based on carefully constructed virtual screening experiments against four targets, using the protein-ligand docking program GOLD.     

CSAR scoring challenge reveals the need for new concepts in estimating protein-ligand binding affinity

The dG prediction accuracy by the Lead Finder docking software on the CSAR test set was characterized by R(2)=0.62 and rmsd=1.93 kcal/mol, and the method of preparation of the full-atom structures of the test set did not significantly affect the resulting accuracy of predictions. The primary factors determining the correlation between the predicted and experimental values were the van der Waals interactions and solvation effects. Those two factors alone accounted for R(2)=0.50. The other factors that affected the accuracy of predictions, listed in the order of decreasing importance, were the change of ligand's internal energy upon binding with protein, the electrostatic interactions, and the hydrogen bonds. It appears that those latter factors contributed to the independence of the prediction results from the method of full-atom structure preparation. Then, we turned our attention to the other factors that could potentially improve the scoring function in order to raise the accuracy of the dG prediction. It turned out that the ligand-centric factors, including Mw, cLogP, PSA, etc. or protein-centric factors, such as the functional class of protein, did not improve the prediction accuracy. Following that, we explored if the weak molecular interactions such as X-H...Ar, X-H...Hal, CO...Hal, C-H...X, stacking and π-cationic interactions (where X is N or O), that are generally of interest to the medicinal chemists despite their lack of proper molecular mechanical parametrization, could improve dG prediction. Our analysis revealed that out of these new interactions only CO...Hal is statistically significant for dG predictions using Lead FInder scoring function. Accounting for the CO...Hal interaction resulted in the reduction of the rmsd from 2.19 to 0.69 kcal/mol for the corresponding structures. The other weak interaction factors were not statistically significant and therefore irrelevant to the accuracy of dG prediction. On the basis of our findings from our participation in the CSAR scoring challenge we conclude that a significant increase of accuracy predictions necessitates breakthrough scoring approaches. We anticipate that the explicit accounting for water molecules, protein flexibility, and a more thermodynamically accurate method of dG calculation rather than single point energy calculation may lead to such breakthroughs.     

Characterization of protein-ligand interactions by high-resolution solid-state NMR spectroscopy

A novel approach for detection of ligand binding to a protein in solid samples is described. Hydrated precipitates of the anti-apoptotic protein Bcl-xL show well-resolved (13)C-(13)C 2D solid-state NMR spectra that allow site-specific assignment of resonances for many residues in uniformly (13)C-enriched samples. Binding of a small peptide or drug-like organic molecule leads to changes in the chemical shift of resonances from multiple residues in the protein that can be monitored to characterize binding. Differential chemical shifts can be used to distinguish between direct protein-ligand contacts and small conformational changes of the protein induced by ligand binding. The agreement with prior solution-state NMR results indicates that the binding pocket in solid and liquid samples is similar for this protein. Advantages of different labeling schemes involving selective (13)C enrichment of methyl groups of Ala, Val, Leu, and Ile (Cdelta1) for characterizing protein-ligand interactions are also discussed. It is demonstrated that high-resolution solid-state NMR spectroscopy on uniformly or extensively (13)C-enriched samples has the potential to screen proteins of moderate size ( approximately 20 kDa) for ligand binding as hydrated solids. The results presented here suggest the possibility of using solid-state NMR to study ligand binding in proteins not amenable to solution NMR.     

A practical high-throughput screening system for enantioselectivity by using FTIR spectroscopy

For the first time FTIR spectroscopy has been applied to the measurement of enantiomeric purity. The underlying concept is based on the use of pseudo-enantiomers that are (13)C-labeled at appropriate positions. Upon applying Lambert-Beer's law in the determination of the concentrations of both enantiomers, the ee values are accessible, accuracy to within +/-5 % of the true values being possible. The application of a commercially available high-throughput FTIR system results in a slightly decreased accuracy (+/-7% for the ee values), but this allows a throughput of up to 10000 samples per day. The method is of interest in the area of combinatorial symmetric catalysis and directed evolution of enantioselective enzymes.     

Biophysical limits of protein-ligand binding

In classic work, Kuntz et al. (Proc. Nat. Acad. Sci. USA1999, 96, 9997-10002) introduced the concept of ligand efficiency. Though that study focused primarily on drug-like molecules, it also showed that metal binding led to the greatest ligand efficiencies. Here, the physical limits of binding are examined across the wide variety of small molecules in the Binding MOAD database. The complexes with the greatest ligand efficiencies share the trait of being small, charged ligands bound in highly charged, well buried binding sites. The limit of ligand efficiency is -1.75 kcal/mol·atom for the protein-ligand complexes within Binding MOAD, and 95% of the set have efficiencies below a "soft limit" of -0.83 kcal/mol·atom. On the basis of buried molecular surface area, the hard limit of ligand efficiency is -117 cal/mol·?(2), which is in surprising agreement with the limit of macromolecule-protein binding. Close examination of the most efficient systems reveals their incredibly high efficiency is dictated by tight contacts between the charged groups of the ligand and the pocket. In fact, a misfit of 0.24 ? in the average contacts inherently decreases the maximum possible efficiency by at least 0.1 kcal/mol·atom.     

Predicting protein-ligand binding affinities using novel geometrical descriptors and machine-learning methods

Inspired by the concept of knowledge-based scoring functions, a new quantitative structure-activity relationship (QSAR) approach is introduced for scoring protein-ligand interactions. This approach considers that the strength of ligand binding is correlated with the nature of specific ligand/binding site atom pairs in a distance-dependent manner. In this technique, atom pair occurrence and distance-dependent atom pair features are used to generate an interaction score. Scoring and pattern recognition results obtained using Kernel PLS (partial least squares) modeling and a genetic algorithm-based feature selection method are discussed.     

An integrated bioanalytical platform for supporting high-throughput serum protein binding screening

Quantification of small molecules using liquid chromatography/tandem mass spectrometry (LC/MS/MS) on a triple quadrupole mass spectrometer has become a common practice in bioanalytical support of in vitro adsorption, distribution, metabolism and excretion (ADME) screening. The bioanalysis process involves primarily three indispensable steps: MS/MS optimization for a large number of new chemical compounds undergoing various screening assays in early drug discovery, high-throughput sample analysis with LC/MS/MS for those chemically diverse compounds using the optimized MS/MS conditions, and post-acquisition data review and reporting. To improve overall efficiency of ADME bioanalysis, an integrated system was proposed featuring an automated and unattended MS/MS optimization, a staggered parallel LC/MS/MS for high-throughput sample analysis, and a sophisticated software tool for LC/MS/MS raw data review as well as biological data calculation and reporting. The integrated platform has been used in bioanalytical support of a serum protein binding screening assay with high speed, high capacity, and good robustness. In this new platform, a unique sample dilution scheme was also introduced. With this dilution design, the total number of analytical samples was reduced; therefore, the total operation time was reduced and the overall throughput was further improved. The performance of the protein binding screening assay was monitored with two controls representing high and low binding properties and an acceptable inter-assay consistency was achieved. This platform has been successfully used for the determination of serum protein binding in multiple species for more than 4000 compounds.     

Fluorine-NMR competition binding experiments for high-throughput screening of large compound mixtures

High-throughput ligand-based NMR screening with competition binding experiments is extended to (19)F detection. Fluorine is a favorable nucleus for these experiments because of the significant contribution of the Chemical Shift Anisotropy (CSA) to the (19)F transverse relaxation of the ligand signal when bound to a macromolecular target. A low to moderate affinity ligand containing a fluorine atom is used as a reference molecule for the detection and characterization of new ligands. Titration NMR experiments with the selected reference compound are performed for finding the optimal set-up conditions for HTS and for deriving the binding constants of the identified NMR hits. Rapid HTS of large chemical mixtures and plant or fungi extracts against the receptor of interest is possible due to the high sensitivity of the (19)F nucleus and the absence of overlap with the signals of the mixtures to be screened. Finally, a novel approach for HTS using a reference molecule in combination with a control molecule is presented.     

Rapid screening of binding constants by calibrated competitive 1H NMR spectroscopy

A calibrated competitive NMR method has been developed that is appropriate for the rapid screening of binding constants. This method involves the initial characterisation of a receptor-substrate binding event for which the (1)H NMR spectrum of a given receptor (calibrant) is modified by the substrate of interest at a range of concentrations. For all subsequent "unknown" receptors, K(a) values are then determined by using a competition assay (in the presence of the calibrant receptor) by measuring a single standard (1)H NMR spectrum. This enables a rapid assessment of the recognition properties of a library of potential receptors. Only the calibrant receptor needs to be NMR active, while the library of putative receptors, as well as the substrate, can be NMR silent. This method assumes the formation of complexes of 1:1 stoichiometry. To demonstrate this methodology, the binding of a number of crown ether type compounds with K+ ions has been studied. Comparison of the binding strengths obtained by using this approach with those in the literature shows excellent agreement. A range of new compounds that have recently been synthesised within our group has also been screened in order to illustrate how this approach can rapidly assess binding ability. This method has significance for chemists working in the fields of combinatorial receptor/substrate design and supramolecular chemistry as a means of rapid optimisation of binding strength.     

Spontaneous membrane-translocating peptides by orthogonal high-throughput screening

Combinatorial peptide chemistry and orthogonal high-throughput screening were used to select peptides that spontaneously translocate across synthetic lipid bilayer membranes without permeabilization. A conserved sequence motif was identified that contains several cationic residues in conserved positions in an otherwise hydrophobic sequence. This 9-residue motif rapidly translocates across synthetic multibilayer vesicles and into cells while carrying a large polar dye as a "cargo" moiety. The extraordinary ability of this family of peptides to spontaneously translocate across bilayers without an energy source of any kind is distinctly different from the behavior of the well-known, highly cationic cell-penetrating peptides, such as the HIV tat peptide, which do not translocate across synthetic bilayers, and enter cells mostly by active endocytosis. Peptides that translocate spontaneously across membranes have the potential to transform the field of drug design by enabling the delivery of otherwise membrane-impermeant polar drugs into cells and tissues. Here we describe the chemical tools needed to rapidly identify spontaneous membrane translocating peptides.     

Unraveling complex small-molecule binding mechanisms by using simple NMR spectroscopy

Heteronuclear NMR spectroscopy provides a unique way to obtain site-specific information about protein-ligand interactions. Usually, such studies rely on the availability of isotopically labeled proteins, thereby allowing both editing of the spectra and ligand signals to be filtered out. Herein, we report that the use of the methyl SOFAST correlation experiment enables the determination of site-specific equilibrium binding constants by using unlabeled proteins. By using the binding of L- and D-tryptophan to serum albumin as a test case, we determined very accurate dissociation constants for both the high- and low-affinity sites present at the protein surface. The values of site-specific dissociation constants were closer to those obtained by isothermal titration calorimetry than those obtained from ligand-observed methods, such as saturation transfer difference. The possibility of measuring ligand binding to serum albumin at physiological concentrations with unlabeled proteins may open up new perspectives in the field of drug discovery.