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.     

Application of affinity selection-mass spectrometry assays to purification and affinity-based screening of the chemokine receptor CXCR4

Affinity selection-mass spectrometry (AS-MS) is a sensitive technology for identifying small molecules that bind to target proteins, and assays enabled by AS-MS can be used to delineate relative binding affinities of ligands for proteins. 'Indirect' AS-MS assays employ size-exclusion techniques to separate target-ligand complexes from unbound ligands, and target-associated ligands are then specifically detected by liquid chromatography mass spectrometry. We report how indirect AS-MS binding assays with known reference control compounds were used as guideposts for development of an optimized purification method for CXCR4, a G-protein coupled chemokine receptor, for which we sought novel antagonists. The CXCR4 purification method that was developed was amenable to scale-up and enabled the screening of purified recombinant human CXCR4 against a large combinatorial library of small molecules by high throughput indirect AS-MS. The screen resulted in the discovery of new ligands that competed off binding of reference compounds to CXCR4 in AS-MS binding assays and that antagonized SDF1α-triggered responses and CXCR4-mediated HIV1 viral uptake in cell-based assays. This report provides a methodological paradigm whereby indirect AS-MS-based ligand binding assays may be used to guide optimal integral membrane protein purification methods that enable downstream affinity selection-based applications such as high throughput AS-MS screens.     

Direct screening of a dynamic combinatorial library using mass spectrometry

A dynamic combinatorial library (DCL) screening approach is described that permits direct identification of the effective (from ineffective) combination of building blocks in the equilibrating DCL. The approach uses Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) together with sustained off-resonance irradiation collision activated dissociation (SORI-CAD) to detect noncovalent protein-DCL ligand complexes under native conditions. It was shown that in a single, rapid experiment one could concurrently identify all the ligands of interest from the DCL against a background of inactive DCL ligands while still in the presence of the target protein. This result has demonstrated that mass spectrometry may provide a fast preliminary screening approach to identify DCL candidates for later verification with more traditional but time-consuming analysis. The MS/MS enables DCL mixtures to be effectively deconvoluted without the need for either chromatography, synthesis of DCL sub-libraries, conversion of the DCL to a static library, or disruption of the protein-ligand complexes before analysis--all typically necessary for the current screening method for DCLs.     

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.     

Determining affinity-selected ligands and estimating binding affinities by online size exclusion chromatography/liquid chromatography-mass spectrometry

Size exclusion chromatography (SEC) isolation of affinity-selected ligands combined with reverse phase liquid chromatography-mass spectrometry (LC-MS) is an effective means for identifying members of mixtures which form tightly bound noncovalent complexes with target proteins. A potential liability of the approach is that the SEC isolation is carried out under nonequilibrium conditions favoring protein/ligand complex dissociation. At long SEC isolation times and/or for complexes with fast off-rates the extent of dissociation can jeopardize the ability to detect the affinity-selected components. Additionally, equilibrium binding affinities cannot be exactly determined from the measured distribution of isolated ligands. We present here an online SEC/LC-MS system for determining affinity-selected members of active mixtures which reduces this liability. A kinetic model of the SEC isolation process is developed to determine the practical limits for the application of the method and to extrapolate equilibrium binding affinities from the nonequilibrium data. The utility of online SEC/LC-MS for identifying affinity-selected ligands and for estimating binding affinities is demonstrated for a small molecule mixture of compounds with known binding affinities and for a simple combinatorial mixture.     

Top-down ESI-ECD-FT-ICR mass spectrometry localizes noncovalent protein-ligand binding sites

Mass spectrometry (MS) with electrospray ionization (ESI) has the capability to measure and detect noncovalent protein-ligand and protein-protein complexes. However, information on the sites of ligand binding is not easily obtained by the ESI-MS methodology. Electron capture dissociation (ECD) favors cleavage of covalent backbone bonds of protein molecules. We show that this characteristic of ECD translates to noncovalent protein-ligand complexes, as covalent backbone bonds of protein complexes are dissociated, but the noncovalent ligand interaction is retained. For the complex formed from 140-residue, 14.5 kDa alpha-synuclein protein, and one molecule of polycationic spermine (202 Da), ECD generates product ions that retain the protein-spermine noncovalent interaction. Spermine binding is localized to residues 106-138; the ECD data are consistent with previous solution NMR studies. Our studies suggest that ECD mass spectrometry can be used to determine directly the sites of ligand binding to protein targets.     

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.     

Drug screening of pharmaceutical discovery compounds by micro-size exclusion chromatography/mass spectrometry.

Micro-size exclusion chromatography coupled with capillary liquid chromatography (capLC) and mass spectrometry (MS) provides a rapid and simple approach to the preliminary screening of active ligands toward a specific target macromolecule. In this study, the effectiveness of this technique is demonstrated by a number of small molecule ligands with known binding affinities towards the protein target. All ligands were incubated together with a target protein under native conditions. Separation was then achieved by microcentrifugation where the high molecular weight (MW) compounds were selectively passed through the size-exclusion material. The retained low MW compounds were then recovered and analyzed by capLC/MS. The absence of the ligand indicated strong affinity towards the target, while ligand detection indicated inactivity. This assay demonstrated the drugs that were acting as strong inhibitors of Co-PDF from those showing to be comparatively inactive. The relative binding rank order of the drugs towards Co-PDF was also determined. The results were validated by a corresponding set of control experiments in which the target molecules were excluded from the process. In principle, high-throughput micro-size exclusion chromatography, coupled with capLC/MS, offers a powerful technique as a preliminary screen in determining both the strong binding affinity and the relative affinity rank ordering of ligands towards a specific target macromolecule, and is complementary with other analytical drug screening techniques.     

Rapid protein-ligand costructures using chemical shift perturbations

Structure-based drug discovery requires the iterative determination of protein-ligand costructures in order to improve the binding affinity and selectivity of potential drug candidates. In general, X-ray and NMR structure determination methods are time consuming and are typically the limiting factor in the drug discovery process. The application of molecular docking simulations to filter and evaluate drug candidates has become a common method to improve the throughput and efficiency of structure-based drug design. Unfortunately, molecular docking methods suffer from common problems that include ambiguous ligand conformers or failure to predict the correct docked structure. A rapid approach to determine accurate protein-ligand costructures is described based on NMR chemical shift perturbation (CSP) data routinely obtained using 2D 1H-15N HSQC spectra in high-throughput ligand affinity screens. The CSP data is used to both guide and filter AutoDock calculations using our AutoDockFilter program. This method is demonstrated for 19 distinct protein-ligand complexes where the docked conformers exhibited an average rmsd of 1.17 +/- 0.74 A relative to the original X-ray structures for the protein-ligand complexes.     

Multiple ligand detection and affinity measurement by ultrafiltration and mass spectrometry analysis applied to fragment mixture screening

Binding affinity of a small molecule drug candidate to a therapeutically relevant biomolecular target is regarded the first determinant of the candidate's efficacy. Although the ultrafiltration-LC/MS (UF-LC/MS) assay enables efficient ligand discovery for a specific target from a mixed pool of compounds, most previous analysis allowed for relative affinity ranking of different ligands. Moreover, the reliability of affinity measurement for multiple ligands with UF-LC/MS has hardly been strictly evaluated. In this study, we examined the accuracy of K_d determination through UF-LC/MS by comparison with classical ITC measurement. A single-point K_d calculation method was found to be suitable for affinity measurement of multiple ligands bound to the same target when binding competition is minimized. A second workflow based on analysis of the unbound fraction of compounds was then developed, which simplified sample preparation as well as warranted reliable ligand discovery. The new workflow implemented in a fragment mixture screen afforded rapid and sensitive detection of low-affinity ligands selectively bound to the RNA polymerase NS5B of hepatitis C virus. More importantly, ligand identification and affinity measurement for mixture-based fragment screens by UF-LC/MS were in good accordance with single ligand evaluation by conventional SPR analysis. This new approach is expected to become a valuable addition to the arsenal of high-throughput screening techniques for fragment-based drug discovery.     

Binding constant determination of high-affinity protein-ligand complexes by electrospray ionization mass spectrometry and ligand competition

We describe an approach for the determination of binding constants for protein-ligand complexes with electrospray ionization mass spectrometry, based on the observation of unbound ligands competing for binding to a protein target. For the first time, dissociation constants lower than picomolar could be determined with good accuracy by electrospray ionization mass spectrometry. The presented methodology relies only on the determination of signal intensity ratios for free ligands in the low mass region. Therefore, all the advantages of measuring low masses with mass spectrometry, such as high resolution are preserved. By using a reference ligand with known binding affinity, the affinity of a second ligand can be determined. Since no noncovalently bound species are observed, assumptions about response factors are not necessary. The method is validated with ligands binding to avidin and applied to ligands binding to p38 mitogen-activated protein kinase.     

Identification of ligand binding sites on proteins using a multi-scale approach

Identification of a ligand binding site on a protein is pivotal to drug discovery. To date, no reliable and computationally feasible general approach to this problem has been published. Here we present an automated efficient method for determining binding sites on proteins for potential ligands without any a priori knowledge. Our method is based upon the multiscale concept where we deal with a hierarchy of models generated using a k-means clustering algorithm for the potential ligand. This is done in a simple approach whereby a potential ligand is represented by a growing number of feature points. At each increasing level of detail, a pruning of potential binding site is performed. A nonbonding energy function is used to score the interactions between molecules at each step. The technique was successfully employed to seven protein-ligand complexes. In the current paper we show that the algorithm considerably reduces the computational effort required to solve this problem. This approach offers real opportunities for exploiting the large number of structures that will evolve from structural genomics.     

亲和色谱中配基的筛选与应用

亲和配基的选择与筛选是发展新的亲和色谱填料或构建一个新的亲和色谱体系所必须解决的首要问题。该文结合作者所在实验室的工作,对配基的选择、筛选与应用方面的一些进展进行了简要评述。作者所在实验室针对特定蛋白质和多肽的多肽亲和配基的筛选,开展了反义肽简并性的研究,发展了基于反义肽的组合化学筛选新方法。与常规的组合合成法相比,该方法简单、快捷、有效,极大地减小了合成和筛选的工作量,降低了筛选后亲和组分结构鉴定的难度。所建立的筛选策略已应用于流感病毒、严重急性呼吸道综合征(SARS)病毒亲和抑制剂的筛选和用于人β-干扰素测定的石英晶体微天平（QCM）生物传感器的构建,均取得了有意义的结果。     

Amplification of bifunctional ligands for calmodulin from a dynamic combinatorial library

A well known strategy to prepare high affinity ligands for a biological receptor is to link together low affinity ligands. DCC (dynamic combinatorial chemistry) was used to select bifunctional protein ligands with high affinity relative to the corresponding monofunctional ligands. Thiol to disulfide linkage generated a small dynamic library of bifunctional ligands in the presence of calmodulin, a protein with two independently mobile domains. The binding constant of the bifunctional ligand (disulfide) most amplified by the presence of calmodulin is nearly two orders of magnitude higher than that of the corresponding monofunctional ligand (thiol).     

Two-dimensional turbulent flow chromatography coupled on-line to liquid chromatography–mass spectrometry for solution-based ligand screening against multiple proteins

We present herein a novel bioseparation/chemical analysis strategy for protein–ligand screening and affinity ranking in compound mixtures, designed to increase screening rates and improve sensitivity and ruggedness in performance. The strategy is carried out by combining on-line two-dimensional turbulent flow chromatography (2D-TFC) with liquid chromatography–mass spectrometry (LC–MS), and accomplished through the following steps: (1) a reversed-phase TFC stage to separate the protein/ligand complex from the unbound free molecules, (2) an on-line dissociation process to release the bound ligands from the complexes, and (3) a second mixed-mode cation-exchange/reversed-phase TFC stage to trap the bound ligands and to remove the proteins and salts, followed by LC–MS analysis for identification and determination of the binding affinities. The technique can implement an ultra-fast isolation of protein/ligand complex with the retention time of a complex peak in about 5 s, and on-line prepare the “clean” sample to be directly compatible with the LC–MS analysis. The improvement in performance of this 2D-TFC/LC–MS approach over the conventional approach has been demonstrated by determining affinity-selected ligands of the target proteins acetylcholinesterase and butyrylcholinesterase from a small library with known binding affinities and a steroidal alkaloid library composed of structurally similar compounds. Our results show that 2D-TFC/LC–MS is a generic and efficient tool for high-throughput screening of ligands with low-to-high binding affinities, and structure-activity relationship evaluation.     

Statistical potential for modeling and ranking of protein-ligand interactions

Applications in structural biology and medicinal chemistry require protein-ligand scoring functions for two distinct tasks: (i) ranking different poses of a small molecule in a protein binding site and (ii) ranking different small molecules by their complementarity to a protein site. Using probability theory, we developed two atomic distance-dependent statistical scoring functions: PoseScore was optimized for recognizing native binding geometries of ligands from other poses and RankScore was optimized for distinguishing ligands from nonbinding molecules. Both scores are based on a set of 8,885 crystallographic structures of protein-ligand complexes but differ in the values of three key parameters. Factors influencing the accuracy of scoring were investigated, including the maximal atomic distance and non-native ligand geometries used for scoring, as well as the use of protein models instead of crystallographic structures for training and testing the scoring function. For the test set of 19 targets, RankScore improved the ligand enrichment (logAUC) and early enrichment (EF(1)) scores computed by DOCK 3.6 for 13 and 14 targets, respectively. In addition, RankScore performed better at rescoring than each of seven other scoring functions tested. Accepting both the crystal structure and decoy geometries with all-atom root-mean-square errors of up to 2 ? from the crystal structure as correct binding poses, PoseScore gave the best score to a correct binding pose among 100 decoys for 88% of all cases in a benchmark set containing 100 protein-ligand complexes. PoseScore accuracy is comparable to that of DrugScore(CSD) and ITScore/SE and superior to 12 other tested scoring functions. Therefore, RankScore can facilitate ligand discovery, by ranking complexes of the target with different small molecules; PoseScore can be used for protein-ligand complex structure prediction, by ranking different conformations of a given protein-ligand pair. The statistical potentials are available through the Integrative Modeling Platform (IMP) software package (http://salilab.org/imp) and the LigScore Web server (http://salilab.org/ligscore/).     

Ligand design by a combinatorial approach based on modeling and experiment: application to HLA-DR4

Combinatorial synthesis and large scale screening methods are being used increasingly in drug discovery, particularly for finding novel lead compounds. Although these "random" methods sample larger areas of chemical space than traditional synthetic approaches, only a relatively small percentage of all possible compounds are practically accessible. It is therefore helpful to select regions of chemical space that have greater likelihood of yielding useful leads. When three-dimensional structural data are available for the target molecule this can be achieved by applying structure-based computational design methods to focus the combinatorial library. This is advantageous over the standard usage of computational methods to design a small number of specific novel ligands, because here computation is employed as part of the combinatorial design process and so is required only to determine a propensity for binding of certain chemical moieties in regions of the target molecule. This paper describes the application of the Multiple Copy Simultaneous Search (MCSS) method, an active site mapping and de novo structure-based design tool, to design a focused combinatorial library for the class II MHC protein HLA-DR4. Methods for the synthesizing and screening the computationally designed library are presented; evidence is provided to show that binding was achieved. Although the structure of the protein-ligand complex could not be determined, experimental results including cross-exclusion of a known HLA-DR4 peptide ligand (HA) by a compound from the library. Computational model building suggest that at least one of the ligands designed and identified by the methods described binds in a mode similar to that of native peptides.     

Relative contributions of desolvation, inter- and intramolecular interactions to binding affinity in protein kinase systems

In several previous studies, we performed sensitivity analysis to gauge the relative importance of different atomic partial charges in determining protein-ligand binding. In this work, we gain further insights by decomposing these results into three contributions: desolvation, intramolecular interactions, and intermolecular interactions, again based on a Poisson continuum electrostatics model. Three protein kinase-inhibitor systems have been analyzed: CDK2-deschloroflavopiridol, PKA-PKI, and LCK-PP2. Although our results point out the importance of specific intermolecular interactions to the binding affinity, they also reveal the remarkable contributions from the solvent-mediated intramolecular interactions in some cases. Thus, it is necessary to look beyond analyzing protein-ligand interactions to understand protein-ligand recognition or to gain insights into designing ligands and proteins. In analyzing the contributions of the three components to the overall binding free energy, the PKA-PKI system with a much larger ligand was found to behave differently from the other two systems with smaller ligands. In the former case, the intermolecular interactions are very favorable, and together with the favorable solvent-mediated intramolecular interactions, they overcome the large desolvation penalties to give a favorable electrostatics contribution to the overall binding affinity. On the other hand, the other two systems with smaller ligands only present modest intermolecular interactions and they are not or are only barely sufficient to overcome the desolvation penalty even with the aid of the favorable intramolecular contributions. As a result, the binding affinity of these two systems do not or only barely benefit from electrostatics contributions.