NMR and in silico screening

NMR-based screening and virtual, or in silico, screening can be highly complementary and synergistic. NMR-based screening is a rapid and reliable method for validating hits that come from in silico screens. In addition, ligand-binding data derived from NMR-based screens can focus and direct subsequent in silico screening. We will first give a short overview of existing NMR and in silico screening methods, discuss the drawbacks associated with each, and finally present applications that highlight the combination of the two technologies.     

Sensitivity improvement in 19F NMR-based screening experiments: theoretical considerations and experimental applications

NMR-based binding and functional screening performed with FAXS (fluorine chemical shift anisotropy and exchange for screening) and 3-FABS (three fluorine atoms for biochemical screening) represents a potential alternative approach to high-throughput screening for the identification of novel potential drug candidates. The major limitation of this method in its current status is its intrinsic low sensitivity that limits the number of tested compounds. One approach for overcoming this problem is the use of a cryogenically cooled (19)F probe that reduces the thermal noise in the receiver circuitry. Sensitivity improvement in the two screening techniques achieved with the novel cryogenic (19)F probe technology permits an increased throughput, detection of weaker binders and inhibitors (relevant in a fragment-based lead discovery program), detection of slow binders, and reduction in protein and substrate consumption. These aspects are analyzed with theoretical simulations and experimental quantitative performance evaluation. Application of 3-FABS combined with the cryogenic (19)F probe technology to rapid screening at very low enzyme concentrations and the current detection limits reached with this approach are also presented.     

ALARM NMR: a rapid and robust experimental method to detect reactive false positives in biochemical screens

High-throughput screening (HTS) of large compound collections typically results in numerous small molecule hits that must be carefully evaluated to identify valid drug leads. Although several filtering mechanisms and other tools exist that can assist the chemist in this process, it is often the case that costly synthetic resources are expended in pursuing false positives. We report here a rapid and reliable NMR-based method for identifying reactive false positives including those that oxidize or alkylate a protein target. Importantly, the reactive species need not be the parent compound, as both reactive impurities and breakdown products can be detected. The assay is called ALARM NMR (a La assay to detect reactive molecules by nuclear magnetic resonance) and is based on monitoring DTT-dependent (13)C chemical shift changes of the human La antigen in the presence of a test compound or mixture. Extensive validation has been performed to demonstrate the reliability and utility of using ALARM NMR to assess thiol reactivity. This included comparing ALARM NMR to a glutathione-based fluorescence assay, as well as testing a collection of more than 3500 compounds containing HTS hits from 23 drug targets. The data show that current in silico filtering tools fail to identify more than half of the compounds that can act via reactive mechanisms. Significantly, we show how ALARM NMR data has been critical in identifying reactive compounds that would otherwise have been prioritized for lead optimization. In addition, a new filtering tool has been developed on the basis of the ALARM NMR data that can augment current in silico programs for identifying nuisance compounds and improving the process of hit triage.     

非选择性一维氢磷相关技术及其在含磷化学毒剂相关化合物分析中的应用

以异核单量子相关(HSQC)、异核多量子相关(HMQC)核磁共振理论为基础,实现了一维非选择性1H-31P HSQC、1H-31P异核单量子结合多键相关(HSQMBC)脉冲序列,并自主设计了一维非选择性1H-31P HMQC脉冲序列,研究了3种技术在峰形、灵敏度上的差异。通过对某次国际禁化武组织水平考试的水样分析发现,非选择性1H-31P HMQC方法是目前用于筛选含磷化学毒剂相关化合物的最有效方法。     

Design and characterization of libraries of molecular fragments for use in NMR screening against protein targets

We have designed four generations of a low molecular weight fragment library for use in NMR-based screening against protein targets. The library initially contained 723 fragments which were selected manually from the Available Chemicals Directory. A series of in silico filters and property calculations were developed to automate the selection process, allowing a larger database of 1.79 M available compounds to be searched for a further 357 compounds that were added to the library. A kinase binding pharmacophore was then derived to select 174 kinase-focused fragments. Finally, an additional 61 fragments were selected to increase the number of different pharmacophores represented within the library. All of the fragments added to the library passed quality checks to ensure they were suitable for the screening protocol, with appropriate solubility, purity, chemical stability, and unambiguous NMR spectrum. The successive generations of libraries have been characterized through analysis of structural properties (molecular weight, lipophilicity, polar surface area, number of rotatable bonds, and hydrogen-bonding potential) and by analyzing their pharmacophoric complexity. These calculations have been used to compare the fragment libraries with a drug-like reference set of compounds and a set of molecules that bind to protein active sites. In addition, an analysis of the overall results of screening the library against the ATP binding site of two protein targets (HSP90 and CDK2) reveals different patterns of fragment binding, demonstrating that the approach can find selective compounds that discriminate between related binding sites.     

2-Fluoro-ATP as a versatile tool for 19F NMR-based activity screening

19F NMR-based methods have found utility in activity-based screening assays. However, because enzymes catalyze a diverse set of reactions, a large variety of fluorinated substrates would need to be identified to target each one separately. We have developed a more streamlined approach that is applicable to many enzymes that utilize ATP as a substrate. In this method, a fluorine-containing ATP analogue, 2-fluoro-ATP, is used to monitor the reaction. Applications are described for nicotinamide adenine dinucleotide synthetase and 3-phosphoinositide dependent kinase-1. Fragment screening results for the latter indicate that this technique can identify compounds that inhibit as well as activate reactions. The present results, together with previous biochemical studies from other laboratories, have shown that 2-fluoro-ATP can serve as a substrate for nine enzymes that are representative of three of the six enzyme subclasses, namely the transferases, hydrolases, and ligases. This suggests that 2-fluoro-ATP is suitable as a universal tool for screening ATP-requiring enzymes. Importantly, 2-fluoro-ATP has been determined to be a valid substrate for a variety of kinases, including both small molecule and protein kinases, suggesting that it may be useful for investigating the large number of pharmaceutically relevant kinases.     

Virtual high throughput screening in new lead identification

Drug discovery continues to be one of the greatest contemporary challenges and rational application of modelling approaches is the first important step to obtain lead compounds, which can be optimised further. Virtual high throughput screening (VHTS) is one of the efficient approaches to obtain lead structures for a given target. Strategic application of different screening filters like pharmacophore mapping, shape-based, ligand-based, molecular similarity etc., in combination with other drug design protocols provide invaluable insights in lead identification and optimization. Screening of large databases using these computational methods provides potential lead compounds, thus triggering a meaningful interplay between computations and experiments. In this review, we present a critical account on the relevance of molecular modelling approaches in general, lead optimization and virtual screening methods in particular for new lead identification. The importance of developing reliable scoring functions for non-bonded interactions has been highlighted, as it is an extremely important measure for the reliability of scoring function. The lead optimization and new lead design has also been illustrated with examples. The importance of employing a combination of general and target specific screening protocols has also been highlighted.     

Discovery of aminoglycoside mimetics by NMR-based screening of Escherichia coli A-site RNA

A method is described for the NMR-based screening for the discovery of aminoglycoside mimetics that bind to Escherichia coli A-site RNA. Although aminoglycosides are clinically useful, they exhibit high nephrotoxicity and ototoxicity, and their overuse has led to the development of resistance to important microbial pathogens. To identify a new series of aminoglycoside mimetics that could potentially overcome the problems associated with toxicities and resistance development observed with the aminoglycosides, we have prepared large quantities of E. coli 16 S A-site RNA and conducted an NMR-based screening of our compound library in search for small-molecule RNA binders against this RNA target. From these studies, several classes of compounds were identified as initial hits with binding affinities in the range of 70 microM to 3 mM. Lead optimization through synthetic modifications of these initial hits led to the discovery of several small-molecule aminoglycoside mimetics that are structurally very different from the known aminoglycosides. Structural models of the A-site RNA/ligand complexes were prepared and compared to the three-dimensional structures of the RNA/aminoglycoside complexes.     

Competition binding experiments for rapidly ranking lead molecules for their binding affinity to human serum albumin

Many lead molecules that have high affinity for a therapeutic target in vitro exhibit a reduced efficacy in vivo. Drug binding to human serum albumin is a major contributor to this reduction in potency, and many drug discovery programs expand significant resources preparing compounds that have decreased albumin binding. As rational and structure-based approaches have already been demonstrated to design compounds that have reduced affinity for albumin, the ability to rapidly and accurately assess protein binding will be valuable in lead optimization. This review will summarize some of the NMR-based efforts towards developing universal, rapid, accurate, and site-specific assays for estimating protein binding.     

RAMPED-UP NMR: multiplexed NMR-based screening for drug discovery

The crucial step in drug discovery is the identification of a lead compound from a vast chemical library by any number of screening techniques. NMR-based screening has the advantage of directly detecting binding of a compound to the target. The spectra resulting from these screens can also be very complex and difficult to analyze, making this an inefficient process. We present here a method, RAMPED-UP NMR, (Rapid Analysis and Multiplexing of Experimentally Discriminated Uniquely Labeled Proteins using NMR) which generates simple spectra which are easy to interpret and allows several proteins to be screened simultaneously. In this method, the proteins to be screened are uniquely labeled with one amino acid type. There are several benefits derived from this unique labeling strategy: the spectra are greatly simplified, resonances that are most likely to be affected by binding are the only ones observed, and peaks that yield little or no information upon binding are eliminated, allowing the analysis of multiple proteins easily and simultaneously. We demonstrate the ability of three different proteins to be analyzed simultaneously for binding to two different ligands. This method will have significant impact in the use of NMR spectroscopy for both the lead generation and lead optimization phases of drug discovery by its ability to increase screening throughput and the ability to examine selectivity. To the best of our knowledge, this is the first time in any format that multiple proteins can be screened in one tube.     

Simultaneous screening of four epidermal growth factor receptor antagonists from Curcuma longa via cell membrane chromatography online coupled with HPLC–MS

The epidermal growth factor receptors (EGFRs) are significant targets for screening active compounds. In this work, an analytical method was established for rapid screening, separation, and identification of EGFRs antagonists from Curcuma longa. Human embryonic kidney 293 cells with a steadily high expression of EGFRs were used to prepare the cell membrane stationary phase in a cell membrane chromatography model for screening active compounds. Separation and identification of the retention chromatographic peaks was achieved by HPLC–MS. The active sites, docking extents and inhibitory effects of the active compounds were also demonstrated. The screening result found that ar‐turmerone, curcumin, demethoxycurcumin, and bisdemethoxycurcumin from Curcuma longa could be active components in a similar manner to gefitinib. Biological trials showed that all of four compounds can inhibit EGFRs protein secretion and cell growth in a dose‐dependent manner, and downregulate the phosphorylation of EGFRs. This analytical method demonstrated fast and effective characteristics for screening, separation and identification of the active compounds from a complex system and should be useful for drug discovery with natural medicinal herbs.     

Discovery of a potent,selective protein tyrosine phosphatase 1B inhibitor using a linked-fragment strategy

Protein tyrosine phosphatase 1B (PTP1B) is an enzyme that downregulates the insulin receptor. Inhibition of PTP1B is expected to improve insulin action, and the design of small molecule PTP1B inhibitors to treat type II diabetes has received considerable attention. In this work, NMR-based screening identified a nonselective competitive inhibitor of PTP1B. A second site ligand was also identified by NMR-based screening and then linked to the catalytic site ligand by rational design. X-ray data confirmed that the inhibitor bound with the catalytic site in the native, "open" conformation. The final compound displayed excellent potency and good selectivity over many other phosphatases. The modular approach to drug design described in this work should be applicable for the design of potent and selective inhibitors of other therapeutically relevant protein tyrosine phosphatases.     

Simultaneous characterization of a mixture of fluorochemicals using three-dimensional 19F-1H heteronuclear TOCSY filtered/edited NMR experiments

Heteronuclear 19F-1H cross-polarization can be used effectively as a tool for both spectral filtering and editing in the NMR analysis of the increasing number of fluorine-containing compounds encountered in drug discovery. Combined with LC-MS, three-dimensional 19F-1H heteronuclear TOCSY filtered experiments based on this approach have enabled the simultaneous identification of a mixture of closely related dexamethasone derivatives without the need for isolation.     

High throughput screening platform for new inhibitors of protein biosynthesis

The search for new antibiotics is an important task, which is of interest for both basic research and health care practices. It is essential to elucidate the mechanism of antimicrobial action during the screening for antimicrobial activity and at the same time be able to test thousands of compounds. A robotic screening system for potential antibiotics developed at the Department of Chemistry at Moscow State University has been described that enables the immediate identification of those that inhibit protein biosynthesis.     

Virtual screening for compounds that mimic protein-protein interface epitopes

Modulation of protein-protein interactions (PPI) has emerged as a new concept in rational drug design. Here, we present a computational protocol for identifying potential PPI inhibitors. Relevant regions of interfaces (epitopes) are predicted for three-dimensional protein models and serve as queries for virtual compound screening. We present a computational screening protocol that incorporates two different pharmacophore models. One model is based on the mathematical concept of autocorrelation vectors and the other utilizes fuzzy labeled graphs. In a proof-of-concept study, we were able to identify serine protease inhibitors using a predicted trypsin epitope as query. Our virtual screening framework may be suited for rapid identification of PPI inhibitors and suggesting bioactive tool compounds.     

Rapid and simple method for screening of natural antioxidants from Chinese herb Flos Lonicerae Japonicae by DPPH-HPLC-DAD-TOF/MS

A rapid and simple method has been developed for the screening and identification of natural antioxidants of Flos Lonicerae Japonicae (FLJ), derived from the flower buds of Lonicera japonica. The hypothesis is that upon reaction with 1,1-diphenyl-2-picrylhydrazyl (DPPH), the peak areas (PAs) of compounds with potential antioxidant effects in the HPLC chromatograms will be significantly reduced or disappeared, and the identity confirmation could be achieved by HPLC-DAD-TOF/MS hyphenated technique. Using the proposed approach, about 14 compounds in the FLJ extract were found to possess a potential antioxidant activity. They were identified as chlorogenic acid (1), 1-O-caffeoylquinic acid (1-O-CQA, 2), caffeic acid (4), 4-O-CQA (5), rutin (7), isoquercitrin (8), luteolin-7-O-glucoside (9), lonicerin (10), 4,5-O-dicaffeoylquinic acid (4,5-O-diCQA, 11), 3,5-O-diCQA (12), 1,3-O-diCQA (13), 3,4-O-diCQA (14), 1,4-O-diCQA (16), and luteolin (17). In addition, the free radical scavenging capacities of the available identified compounds were also investigated by HPLC assay. The results indicated that the compounds with PAs significantly decreasing were natural antioxidants, whereas those with PAs not changing presented no activities, which accordingly indicated that this newly proposed method could be widely applied for rapid screening and identification of natural antioxidants from complex matrices including Chinese herbal medicines.     

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.     

Utility of NMR in lead optimization: fragment-based approaches

NMR has proven to be a valuable tool for identifying small molecule drug leads that serve as starting points for lead optimization programs. In addition, NMR screening can also be applied during lead optimization in order to improve the pharmacokinetic properties of a compound. In this paper we review the NMR methods that can be used for this purpose. Several examples are then summarized to demonstrate the usefulness of fragment-based approaches in optimizing the physical properties of potential drug candidates.     

Computational validation of the importance of absolute stereochemistry in virtual screening

Consideration of stereochemistry early in the identification and optimization of lead compounds can improve the efficiency and efficacy of the drug discovery process and reduce the time spent on subsequent drug development. These improvements can result by focusing on specific enantiomers that have the desired potential therapeutic effect (eutomers), while removing from consideration enantiomers that may have no, or even undesirable, effects (distomers). A virtual screening campaign that correctly takes stereochemical information into account can, in theory, be utilized to provide information about the relative binding affinities of enantiomers. Thus, the proper enumeration of the relevant stereoisomers in general, and enantiomeric pairs in particular, of chiral compounds is crucial if one is to use virtual screening as an effective drug discovery tool. As is obvious, in cases where no stereochemical information is provided for chiral compounds in a 2D chemical database, then each possible stereoisomer should be generated for construction of the subsequent 3D database to be used for virtual screening. However, acute problems can arise in 3D database construction when relative stereochemistry is encoded in a 2D database for a chiral compound containing multiple stereogenic atoms but absolute stereochemistry is not implied. In this case, we report that generation of enantiomeric pairs is imperative in database development if one is to obtain accurate docking results. A study is described on the impact of the neglect of enantiomeric pairs on virtual screening using the human homolog of murine double minute 2 (MDM2) protein, the product of a proto-oncogene, as the target. Docking in MDM2 with GLIDE 4.0 was performed using the NCI Diversity Set 3D database and, for comparison, a set of enantiomers we created corresponding to mirror image structures of the single enantiomers of chiral compounds present in the NCI Diversity Set. Our results demonstrate that potential lead candidates may be overlooked when databases contain 3D structures representing only a single enantiomer of racemic chiral compounds.