NMR-based quality control approach for the identification of false positives and false negatives in high throughput screening

Innovative Strategy toward Mutant CFTR Rescue in Cystic Fibrosis: Design and Synthesis of Thiadiazole Inhibitors of the E3 Ligase RNF5

In cystic fibrosis (CF), deletion of phenylalanine 508 (F508del) in the CF transmembrane conductance regulator (CFTR) is associated to misfolding and defective gating of the mutant channel. One of the most promising CF drug targets is the ubiquitin ligase RNF5, which promotes F508del-CFTR degradation. Recently, the first ever reported inhibitor of RNF5 was discovered, i.e., the 1,2,4-thiadiazol-5-ylidene inh-2. Here, we designed and synthesized a series of new analogues to explore the structure-activity relationships (SAR) of this class of compounds. SAR efforts ultimately led to compound 16, which showed a greater F508del-CFTR corrector activity than inh-2, good tolerability, and no toxic side effects. Analogue 16 increased the basal level of autophagy similar to what has been described with RNF5 silencing. Furthermore, co-treatment with 16 significantly improved the F508del-CFTR rescue induced by the triple combination elexacaftor/tezacaftor/ivacaftor in CFBE41o^- cells. These findings validate the 1,2,4-thiadiazolylidene scaffold for the discovery of novel RNF5 inhibitors and provide evidence to pursue this unprecedented strategy for the treatment of CF.

Design, Synthesis, In Vitro and In Vivo Characterization of CDC42 GTPase Interaction Inhibitors for the Treatment of Cancer

CDC42 GTPases (RHOJ, CDC42, and RHOQ) are overexpressed in multiple tumor types and activate pathways critical for tumor growth, angiogenesis, and metastasis. Recently, we reported the discovery of a novel lead compound, ARN22089, which blocks the interaction of CDC42 GTPases with specific downstream effectors. ARN22089 blocks tumor growth in BRAF mutant mouse melanoma models and patient-derived xenografts (PDXs) in vivo. ARN22089 also inhibits tumor angiogenesis in three-dimensional vascularized microtumor models in vitro. Notably, ARN22089 belongs to a novel class of trisubstituted pyrimidines. Based on these results, we describe an extensive structure-activity relationship of ∼30 compounds centered on ARN22089. We discovered and optimized two novel inhibitors (27, ARN25062, and 28, ARN24928), which are optimal back-up/follow-up leads with favorable drug-like properties and in vivo efficacy in PDX tumors. These findings further demonstrate the potential of this class of CDC42/RHOJ inhibitors for cancer treatment, with lead candidates ready for advanced preclinical studies.

Green chemistry and first-principles theory enhance catalysis: synthesis and 6-fold catalytic activity increase of sub-5 nm Pd and Pt@Pd nanocubes

Synthesizing metal nanoparticles with fine control of size, shape and surface properties is of high interest for applications such as catalysis, nanoplasmonics, and fuel cells. In this contribution, we demonstrate that the citrate-coated surfaces of palladium (Pd) and platinum (Pt)@Pd nanocubes with a lateral length <5 nm and low polydispersity in shape achieve superior catalytic properties. The synthesis achieves great control of the nanoparticle's physico-chemical properties by using only biogenic reagents and bromide ions in water while being fast, easy to perform and scalable. The role of the seed morphology is pivotal as Pt single crystal seeds are necessary to achieve low polydispersity in shape and prevent nanorods formation. In addition, electrochemical measurements demonstrate the abundancy of Pd{100} surface facets at a macroscopic level, in line with information inferred from TEM analysis. Quantum density functional theory calculations indicate that the kinetic origin of cubic Pd nanoshapes is facet-selective Pd reduction/deposition on Pd(111). Moreover, we underline both from an experimental and theoretical point of view that bromide alone does not induce nanocube formation without the synergy with formic acid. The superior performance of these highly controlled nanoparticles to perform the catalytic reduction of 4-nitrophenol was proved: polymer-free and surfactant-free Pd nanocubes outperform state-of-the-art materials by a factor >6 and a commercial Pd/C catalyst by more than one order of magnitude.

Efficient Screening of Target-Specific Selected Compounds in Mixtures by 19F NMR Binding Assay with Predicted 19F NMR Chemical Shifts

Ligand-based 19 F NMR screening is a highly effective and well-established hit-finding approach. The high sensitivity to protein binding makes it particularly suitable for fragment screening. Different criteria can be considered for generating fluorinated fragment libraries. One common strategy is to assemble a large, diverse, well-designed and characterized fragment library which is screened in mixtures, generated based on experimental 19 F NMR chemical shifts. Here, we introduce a complementary knowledge-based 19 F NMR screening approach, named 19 Focused screening, enabling the efficient screening of putative active molecules selected by computational hit finding methodologies, in mixtures assembled and on-the-fly deconvoluted based on predicted 19 F NMR chemical shifts. In this study, we developed a novel approach, named LEFshift , for 19 F NMR chemical shift prediction using rooted topological fluorine torsion fingerprints in combination with a random forest machine learning method. A demonstration of this approach to a real test case is reported.

Advances in the quality control of fenugreek seeds using chromatographic, spectroscopic and DNA-based techniques: A comprehensive review

INTRODUCTION

Fenugreek has been used in traditional remedies since ancient times. It has a long history of use against medical ailments as an antidiabetic, anticarcinogenic, hypocholesterolemic, antioxidant, antibacterial, hypoglycemic, gastric stimulant, and anti-anorexia agent. The major active constituents include alkaloids, fibres, saponins, proteins, and amino acids.

OBJECTIVES

To provide a comprehensive overview of the application of chromatographic and spectroscopic methods, in addition to DNA-profiling methods to assess the quality of fenugreek. Also, to highlight the recent application of chemometrics combined with quality control methods during the last two decades.

METHODOLOGY

A literature search conducted from January 2000 up to December 2020 using various scientific databases (e.g., Scopus, Medline, PubMed, EBSCO, JSTOR, ScienceDirect, Google Scholar, Web of Science and Egyptian Knowledge Bank, Academic Journals, and Springer Link); general web searches were also undertaken using Google applying some related search terms. Studies involving the application of quality control analyses were classified into three categories according to the conducted analysis method including chromatographic [high-performance liquid chromatography (HPLC), high-performance thin-layer chromatography (HPTLC), and gas chromatography (GC)], spectroscopic [ultraviolet (UV), infrared (IR), and nuclear magnetic resonance (NMR)], and DNA-based markers.

RESULTS

This review shed the light on relevant studies covering the past two decades, presenting the application of spectroscopic and chromatographic methods and DNA profiling in the quality control of fenugreek.

CONCLUSION

The reviewed chromatographic and spectroscopic methods combined with chemometrics provide a powerful tool that could be applied widely for the quality control of fenugreek.

NMR quality control of fragment libraries for screening

Fragment-based screening has evolved as a remarkable approach within the drug discovery process both in the industry and academia. Fragment screening has become a more structure-based approach to inhibitor development, but also towards development of pathway-specific clinical probes. However, it is often witnessed that the availability, immediate and long-term, of a high quality fragment-screening library is still beyond the reach of most academic laboratories. Within iNEXT (Infrastructure for NMR, EM and X-rays for Translational research), a EU-funded Horizon 2020 program, a collection of 782 fragments were assembled utilizing the concept of "poised fragments" with the aim to facilitate downstream synthesis of ligands with high affinity by fragment ligation. Herein, we describe the analytical procedure to assess the quality of this purchased and assembled fragment library by NMR spectroscopy. This quality assessment requires buffer solubility screening, comparison with LC/MS quality control and is supported by state-of-the-art software for high throughput data acquisition and on-the-fly data analysis. Results from the analysis of the library are presented as a prototype of fragment progression through the quality control process.

Fluorine NMR functional screening: from purified enzymes to human intact living cells

The substrate- or cofactor-based fluorine NMR screening, also known as n-FABS (n fluorine atoms for biochemical screening), represents a powerful method for performing a direct functional assay in the search of inhibitors or enhancers of an enzymatic reaction. Although it suffers from the intrinsic low sensitivity compared to other biophysical techniques usually applied in functional assays, it has some distinctive features that makes it appealing for tackling complex chemical and biological systems. Its strengths are represented by the easy set-up, robustness, flexibility, lack of signal interference and rich information content resulting in the identification of bona fide inhibitors and reliable determination of their inhibitory strength. The versatility of the n-FABS allows its application to either purified enzymes, cell lysates or intact living cells. The principles, along with theoretical, technical and practical aspects, of the methodology are discussed. Furthermore, several applications of the technique to pharmaceutical projects are presented.

An Efficient Feature Extraction Technique Based on Local Coding PSSM and Multifeatures Fusion for Predicting Protein-Protein Interactions

Background

Increasing evidence has indicated that protein-protein interactions (PPIs) play important roles in various aspects of the structural and functional organization of a cell. Thus, continuing to uncover potential PPIs is an important topic in the biomedical domain. Although various feature extraction methods with machine learning approaches have enhanced the prediction of PPIs. There remains room for improvement by developing novel and effective feature extraction methods and classifier approaches to identify PPIs.

Method

In this study, we proposed a sequence-based feature extraction method called LCPSSMMF, which combined local coding position-specific scoring matrix (PSSM) with multifeatures fusion. First, we used a novel local coding method based on PSSM to build a new PSSM (CPSSM); the advantage of this method is that it incorporated global and local feature extraction, which can account for the interactions between residues in both continuous and discontinuous regions of amino acid sequences. Second, we adopted 2 different feature extraction methods (Local Average Group [LAG] and Bigram Probability [BP]) to capture multiple key feature information by employing the evolutionary information embedded in the CPSSM matrix. Finally, feature vectors were acquired by using multifeatures fusion method.

Result

To evaluate the performance of the proposed feature extraction approach, we employed support vector machine (SVM) as a prediction classifier and applied this method to yeast and human PPI datasets. The prediction accuracies of LCPSSMMF were 93.43% and 90.41% on the yeast and human datasets, respectively. Moreover, we also compared the proposed method with the previous sequence-based approaches on the yeast datasets by using the same SVM classifier. The experimental results indicated that the performance of LCPSSMMF significantly exceeded that of several other state-of-the-art methods. It is proven that the LCPSSMMF approach can capture more local and global discriminatory information than almost all previous methods and can function remarkably well in identifying PPIs. To facilitate extensive research in future proteomics studies, we developed a LCPSSMMFSVM server, which is freely available for academic use at http://219.219.62.123:8888/LCPSSMMFSVM.

Exposing Small-Molecule Nanoentities by a Nuclear Magnetic Resonance Relaxation Assay

Small molecules can self-assemble in aqueous solution into a wide range of nanoentity types and sizes (dimers, n-mers, micelles, colloids, etc.), each having their own unique properties. This has important consequences in the context of drug discovery including issues related to nonspecific binding, off-target effects, and false positives and negatives. Here, we demonstrate the use of the spin-spin relaxation Carr-Purcell-Meiboom-Gill NMR experiment, which is sensitive to molecular tumbling rates and can expose larger aggregate species that have slower rotational correlations. The strategy easily distinguishes lone-tumbling molecules versus nanoentities of various sizes. The technique is highly sensitive to chemical exchange between single-molecule and aggregate states and can therefore be used as a reporter when direct measurement of aggregates is not possible by NMR. Interestingly, we found differences in solution behavior for compounds within structurally related series, demonstrating structure-nanoentity relationships. This practical experiment is a valuable tool to support drug discovery efforts.

Systematic mapping of protein-metabolite interactions in central metabolism of Escherichia coli

Metabolite binding to proteins regulates nearly all cellular processes, but our knowledge of these interactions originates primarily from empirical in vitro studies. Here, we report the first systematic study of interactions between water-soluble proteins and polar metabolites in an entire biological subnetwork. To test the depth of our current knowledge, we chose to investigate the well-characterized Escherichia coli central metabolism. Using ligand-detected NMR, we assayed 29 enzymes towards binding events with 55 intracellular metabolites. Focusing on high-confidence interactions at a false-positive rate of 5%, we detected 98 interactions, among which purine nucleotides accounted for one-third, while 50% of all metabolites did not interact with any enzyme. In contrast, only five enzymes did not exhibit any metabolite binding and some interacted with up to 11 metabolites. About 40% of the interacting metabolites were predicted to be allosteric effectors based on low chemical similarity to their target's reactants. For five of the eight tested interactions, in vitro assays confirmed novel regulatory functions, including ATP and GTP inhibition of the first pentose phosphate pathway enzyme. With 76 new candidate regulatory interactions that have not been reported previously, we essentially doubled the number of known interactions, indicating that the presently available information about protein-metabolite interactions may only be the tip of the iceberg.

Sequence-based Prediction of Protein-Protein Interactions Using Gray Wolf Optimizer-Based Relevance Vector Machine

Protein-protein interactions (PPIs) are essential to a number of biological processes. The PPIs generated by biological experiment are both time-consuming and expensive. Therefore, many computational methods have been proposed to identify PPIs. However, most of these methods are limited as they are difficult to compute and rely on a large number of homologous proteins. Accordingly, it is urgent to develop effective computational methods to detect PPIs using only protein sequence information. The kernel parameter of relevance vector machine (RVM) is set by experience, which may not obtain the optimal solution, affecting the prediction performance of RVM. In this work, we presented a novel computational approach called GWORVM-BIG, which used Bi-gram (BIG) to represent protein sequences on a position-specific scoring matrix (PSSM) and GWORVM classifier to perform classification for predicting PPIs. More specifically, the proposed GWORVM model can obtain the optimum solution of kernel parameters using gray wolf optimizer approach, which has the advantages of less control parameters, strong global optimization ability, and ease of implementation compared with other optimization algorithms. The experimental results on yeast and human data sets demonstrated the good accuracy and efficiency of the proposed GWORVM-BIG method. The results showed that the proposed GWORVM classifier can significantly improve the prediction performance compared with the RVM model using other optimizer algorithms including grid search (GS), genetic algorithm (GA), and particle swarm optimization (PSO). In addition, the proposed method is also compared with other existing algorithms, and the experimental results further indicated that the proposed GWORVM-BIG model yields excellent prediction performance. For facilitating extensive studies for future proteomics research, the GWORVMBIG server is freely available for academic use at http://219.219.62.123:8888/GWORVMBIG.

Ligand-Efficient Inhibitors of Trichomonas vaginalis Adenosine/Guanosine Preferring Nucleoside Ribohydrolase

Trichomoniasis is caused by the parasitic protozoan Trichomonas vaginalis and is the most prevalent, nonviral sexually transmitted disease. The parasite has shown increasing resistance to the current 5-nitroimidazole therapies indicating the need for new therapies with different mechanisms. T. vaginalis is an obligate parasite that scavenges nucleosides from host cells and then uses salvage pathway enzymes to obtain the nucleobases. The adenosine/guanosine preferring nucleoside ribohydrolase was screened against a 2000-compound diversity fragment library using a ¹H NMR-based activity assay. Three classes of inhibitors with more than five representatives were identified: bis-aryl phenols, amino bicyclic pyrimidines, and aryl acetamides. Among the active fragments were 10 compounds with ligand efficiency values greater than 0.5, including five with IC₅₀ values <10 μM. Jump-dilution and detergent counter screens validated reversible, target-specific activity. The data reveals an emerging SAR that is guiding our medicinal chemistry efforts aimed at discovering compounds with nanomolar potency.

Resonant waveguide grating based assays for colloidal aggregate detection and promiscuity characterization in natural products

Small molecules, including natural compounds, in aqueous buffer that self-associate into colloidal aggregates is the main cause of false results in the early stage of drug discovery. Here we reported resonant waveguide grating (RWG) based assays to identify natural compound aggregation and characterize its influence on membrane receptors in living cells. We first applied a cell-free aggregation assay to determine compound critical aggregation concentration (CAC) values. Then we characterized the aggregators' influence on membrane receptors using three types of dynamic mass redistribution (DMR) assays. Results showed that colloidal aggregates may cause false activity in DMR desensitization assays; some of the false activities can be implied by the large response in DMR agonism assays and can further be identified by DMR antagonism assays. Furthermore, the aggregation mechanism was confirmed by addition of 0.025% tween-80, with cell signals attenuated and potency decreased. Finally, these observations were used for aggregate examination and promiscuity investigation of a traditional herbal medicine, Rhodiola rosea, which ultimately led to the revealing of the true target and reduced the risk of a bioactivity tracking process at the very first stage. This study highlights that the RWG based assays can be used as practical tools to distinguish between real and false hits to provide reliable results in the early stage of drug discovery.

Resonant waveguide grating based assays to eliminate colloidal aggregate induced false activity involving natural products.

Current NMR Techniques for Structure-Based Drug Discovery

A variety of nuclear magnetic resonance (NMR) applications have been developed for structure-based drug discovery (SBDD). NMR provides many advantages over other methods, such as the ability to directly observe chemical compounds and target biomolecules, and to be used for ligand-based and protein-based approaches. NMR can also provide important information about the interactions in a protein-ligand complex, such as structure, dynamics, and affinity, even when the interaction is too weak to be detected by ELISA or fluorescence resonance energy transfer (FRET)-based high-throughput screening (HTS) or to be crystalized. In this study, we reviewed current NMR techniques. We focused on recent progress in NMR measurement and sample preparation techniques that have expanded the potential of NMR-based SBDD, such as fluorine NMR (¹⁹F-NMR) screening, structure modeling of weak complexes, and site-specific isotope labeling of challenging targets.

NMR Methods for Identification of False Positives in Biochemical Screens

Over the past few decades, NMR spectroscopy has become an established tool in drug discovery. This communication will highlight the potential of NMR spectroscopy as a method for identification of problematic compounds and as a valuable aid toward revealing some mechanisms of promiscuous behavior. NMR methods for detecting false positives will be analyzed on the basis of their performance, strengths, limitations, and potential pitfalls. Additionally, this communication aims to provide an insight into the limitations of NMR-based methodologies applied to ligand screening in the context of false-positive hits.

Evaluation of ligand-based NMR screening methods to characterize small molecule binding to HIV-1 glycoprotein-41

Small molecule inhibitors of glycoprotein-41 (gp41) are able to prevent HIV infection by binding to a hydrophobic pocket (HP) contained within the gp41 ectodomain, and preventing progression of fusion. There is little structural information on gp41-ligand complexes, owing to hydrophobicity of the ligands, occlusion of the HP in folded gp41 ectodomain, and failure to form crystals of complexes. Here we used an engineered gp41 ectodomain protein containing an exposed HP and a small molecule designed to bind with weak affinity to the HP. We evaluated NMR methods, including WaterLOGSY, Saturation Transfer Difference spectroscopy (STD-NMR) and 1H relaxation rate difference spectroscopy with and without target irradiation (DIRECTION) for their ability to probe complex formation and structure. WaterLOGSY was the most sensitive technique for monitoring formation of the complex. STD-NMR and DIRECTION experiments gave similar pharmacophore mapping profiles, although the low dynamic range of the DIRECTION experiment limited its discrimination and sensitivity. A unique binding pose was identified from the STD data and provided clues for future optimization. Advantages and disadvantages of the techniques are discussed. This is the first example of the use of STD for structural analysis of a gp41-small molecule complex.

Process of Fragment-Based Lead Discovery-A Perspective from NMR

Fragment-based lead discovery (FBLD) has proven fruitful during the past two decades for a variety of targets, even challenging protein–protein interaction (PPI) systems. Nuclear magnetic resonance (NMR) spectroscopy plays a vital role, from initial fragment-based screening to lead generation, because of its power to probe the intrinsically weak interactions between targets and low-molecular-weight fragments. Here, we review the NMR FBLD process from initial library construction to lead generation. We describe technical aspects regarding fragment library design, ligand- and protein-observed screening, and protein–ligand structure model generation. For weak binders, the initial hit-to-lead evolution can be guided by structural information retrieved from NMR spectroscopy, including chemical shift perturbation, transferred pseudocontact shifts, and paramagnetic relaxation enhancement. This perspective examines structure-guided optimization from weak fragment screening hits to potent leads for challenging PPI targets.

Twenty years on: the impact of fragments on drug discovery

After 20 years of sometimes quiet growth, fragment-based drug discovery (FBDD) has become mainstream. More than 30 drug candidates derived from fragments have entered the clinic, with two approved and several more in advanced trials. FBDD has been widely applied in both academia and industry, as evidenced by the large number of papers from universities, non-profit research institutions, biotechnology companies and pharmaceutical companies. Moreover, FBDD draws on a diverse range of disciplines, from biochemistry and biophysics to computational and medicinal chemistry. As the promise of FBDD strategies becomes increasingly realized, now is an opportune time to draw lessons and point the way to the future. This Review briefly discusses how to design fragment libraries, how to select screening techniques and how to make the most of information gleaned from them. It also shows how concepts from FBDD have permeated and enhanced drug discovery efforts.

Advances in NMR Methods To Map Allosteric Sites: From Models to Translation

The last five years have witnessed major developments in the understanding of the allosteric phenomenon, broadly defined as coupling between remote molecular sites. Such advances have been driven not only by new theoretical models and pharmacological applications of allostery, but also by progress in the experimental approaches designed to map allosteric sites and transitions. Among these techniques, NMR spectroscopy has played a major role given its unique near-atomic resolution and sensitivity to the dynamics that underlie allosteric couplings. Here, we highlight recent progress in the NMR methods tailored to investigate allostery with the goal of offering an overview of which NMR approaches are best suited for which allosterically relevant questions. The picture of the allosteric "NMR toolbox" is provided starting from one of the simplest models of allostery (i.e., the four-state thermodynamic cycle) and continuing to more complex multistate mechanisms. We also review how such an "NMR toolbox" has assisted the elucidation of the allosteric molecular basis for disease-related mutations and the discovery of novel leads for allosteric drugs. From this overview, it is clear that NMR plays a central role not only in experimentally validating transformative theories of allostery, but also in tapping the full translational potential of allosteric systems.

Suppression of problematic compound oligomerization by cosolubilization of nondetergent sulfobetaines

Numerous small organic compounds exist in equilibrium among monomers, soluble oligomers, and insoluble aggregates in aqueous solution. Compound aggregation is a major reason for false positives in drug screening, and even soluble oligomers can interfere with structural and biochemical analyses. However, an efficient way to manage the equilibrium of aggregation-prone compounds, especially those involved with soluble oligomers, has not been established. In this study, solution NMR spectroscopy was used as a suitable technique to detect compound oligomers in equilibrium, and it was demonstrated that cosolubilization of nondetergent sulfobetaines (NDSBs) can largely suppress compound oligomerization and aggregation by shifting the equilibrium toward the monomers. The rotational correlation time was obtained from the ratio of the selective and nonselective longitudinal NMR relaxation times, which directly and quantitatively reflected the apparent sizes of the compounds in the equilibrium. The rotational correlation time of the aggregation-prone compound SKF86002 (1 mM) was substantially reduced from 0.31 to 0.23 ns by cosolubilization of 100 mM NDSB195. NDSB cosolubilization allowed us to perform successful structural and biochemical experiments with substantially fewer artifacts, which represents a strategy to directly resolve the problematic oligomerization and aggregation of compounds.

NMR screening in fragment-based drug design: a practical guide

Fragment-based drug design (FBDD) comprises both fragment-based screening (FBS) to find hits and elaboration of these hits to lead compounds. Typical fragment hits have lower molecular weight (<300-350 Da) and lower initial potency but higher ligand efficiency when compared to those from high-throughput screening. NMR spectroscopy has been widely used for FBDD since it identifies and localizes the binding site of weakly interacting hits on the target protein. Here we describe ligand-based NMR methods for hit identification from fragment libraries and for functional cross-validation of primary hits.

Fragment-based hit discovery and structure-based optimization of aminotriazoloquinazolines as novel Hsp90 inhibitors

In the last decade the heat shock protein 90 (Hsp90) has emerged as a major therapeutic target and many efforts have been dedicated to the discovery of Hsp90 inhibitors as new potent anticancer agents. Here we report the identification of a novel class of Hsp90 inhibitors by means of a biophysical FAXS-NMR based screening of a library of fragments. The use of X-ray structure information combined with modeling studies enabled the fragment evolution of the initial triazoloquinazoline hit to a class of compounds with nanomolar potency and drug-like properties suited for further lead optimization.

NMR and molecular recognition. The application of ligand-based NMR methods to monitor molecular interactions

NMR allows the monitoring of molecular recognition processes in solution. Nowadays, a plethora of NMR methods are available to deduce the key features of the interaction from both the ligand or the receptor points of view.

Design and generation of highly diverse fluorinated fragment libraries and their efficient screening with improved (19) F NMR methodology

Fragment screening performed with (19) F NMR spectroscopy is becoming increasingly popular in drug discovery projects. With this approach, libraries of fluorinated fragments are first screened using the direct-mode format of the assay. The choice of fluorinated motifs present in the library is fundamental in order to ensure a large coverage of chemical space and local environment of fluorine (LEF). Mono- and poly-fluorinated fragments to be included in the libraries for screening are selected from both in-house and commercial collections, and those that are ad hoc designed and synthesized. Additional fluorinated motifs to be included in the libraries derive from the fragmentation of compounds in development and launched on the market, and compounds contained in other databases (such as Integrity, PDB and ChEMBL). Complex mixtures of highly diverse fluorine motifs can be rapidly screened and deconvoluted in the same NMR tube with a novel on the fly combined procedure for the identification of the active molecule(s). Issues and problems encountered in the design, generation and screening of diverse fragment libraries of fluorinated compounds with (19) F NMR spectroscopy are analyzed and technical solutions are provided to overcome them. The versatile screening methodology described here can be efficiently applied in laboratories with limited NMR setup and could potentially lead to the increasing role of (19) F NMR in the hit identification and lead optimization phases of drug discovery projects.

Development of fragment-based n-FABS NMR screening applied to the membrane enzyme FAAH

Despite the recognized importance of membrane proteins as pharmaceutical targets, the reliable identification of fragment hits that are able to bind these proteins is still a major challenge. Among different ¹⁹F NMR spectroscopic methods, n-fluorine atoms for biochemical screening (n-FABS) is a highly sensitive technique that has been used efficiently for fragment screening, but its application for membrane enzymes has not been reported yet. Herein, we present the first successful application of n-FABS to the discovery of novel fragment hits, targeting the membrane-bound enzyme fatty acid amide hydrolase (FAAH), using a library of fluorinated fragments generated based on the different local environment of fluorine concept. The use of the recombinant fusion protein MBP-FAAH and the design of compound 11 as a suitable novel fluorinated substrate analogue allowed n-FABS screening to be efficiently performed using a very small amount of enzyme. Notably, we have identified 19 novel fragment hits that inhibit FAAH with a median effective concentration (IC₅₀) in the low mM-μM range. To the best of our knowledge, these results represent the first application of a ¹⁹F NMR fragment-based functional assay to a membrane protein.

Metal impurities cause false positives in high-throughput screening campaigns

Organic impurities in compound libraries are known to often cause false-positive signals in screening campaigns for new leads, but organic impurities do not fully account for all false-positive results. We discovered inorganic impurities in our screening library that can also cause positive signals for a variety of targets and/or readout systems, including biochemical and biosensor assays. We investigated in depth the example of zinc for a specific project and in retrospect in various HTS screens at Roche and propose a straightforward counter screen using the chelator TPEN to rule out inhibition caused by zinc.

The generation of purinome-targeted libraries as a means to diversify ATP-mimetic chemical classes for lead finding

The generation of novel chemotypes in support of our oncology research projects expanded in recent years from a canonical design of kinase-targeted compound libraries to a broader interpretation of purinome-targeted libraries (PTL) addressing the specificity of cancer relevant targets such as kinases and ATPases. Successful screening of structurally diverse ATP-binding targets requires compound libraries covering multiple design elements, which may include phosphate surrogate moieties in ATPase inhibitors or far reaching lipophilic residues stabilizing inactive kinase conformations. Here, we exemplify the design and preparation of drug-like combinatorial libraries and report significantly enhanced screening performance on purinomic targets. We compared overall hit rates of PTL with a simultaneously tested unbiased collection of 200,000 compounds and found consistent superiority of the targeted libraries in all cases. We also analyzed the performance of the largest targeted libraries in comparison with each other and often found striking differences in how a specific target responds to various chemotypes and to whole collections.

Case Studies of Minimizing Nonspecific Inhibitors in HTS Campaigns That Use Assay-Ready Plates

Identifying chemical lead matter by high-throughput screening (HTS) has been a common practice in early stage drug discovery. Evolution of small-molecule library composition to include more drug-like molecules with desirable physical chemical properties combined with improving assay technologies has vastly enhanced the capability of HTS. However, HTS campaigns can still be plagued by false positives arising from nonspecific inhibitors. The generation of assay-ready plates has permitted an incremental advancement to the speed and efficiency of HTS but has the potential to enhance the occurrence of nonspecific inhibitors. A subtle change in the order of reagent addition to the assay-ready plates can greatly alleviate false-positive inhibition. Our case studies with six different kinase and protease targets reveal that this type of inhibition affects targets regardless of enzyme class and is unpredictable based on protein construct or inhibitor chemical scaffold. These case studies support a model where a diversity set of compounds should be tested first for hit rates as a function of order of addition, carrier protein, and relevant mechanistic studies prior to launch of the HTS campaign.

NMR-based screening of membrane protein ligands

Membrane proteins pose problems for the application of NMR-based ligand-screening methods because of the need to maintain the proteins in a membrane mimetic environment such as detergent micelles: they add to the molecular weight of the protein, increase the viscosity of the solution, interact with ligands non-specifically, overlap with protein signals, modulate protein dynamics and conformational exchange and compromise sensitivity by adding highly intense background signals. In this article, we discuss the special considerations arising from these problems when conducting NMR-based ligand-binding studies with membrane proteins. While the use of (13)C and (15)N isotopes is becoming increasingly feasible, (19)F and (1)H NMR-based approaches are currently the most widely explored. By using suitable NMR parameter selection schemes independent of or exploiting the presence of detergent, (1)H-based approaches require least effort in sample preparation because of the high sensitivity and natural abundance of (1)H in both, ligand and protein. On the other hand, the (19)F nucleus provides an ideal NMR probe because of its similarly high sensitivity to that of (1)H and the lack of natural (19)F background in biologic systems. Despite its potential, the use of NMR spectroscopy is highly underdeveloped in the area of drug discovery for membrane proteins.

Application of NMR and molecular docking in structure-based drug discovery

Drug discovery is a complex and costly endeavor, where few drugs that reach the clinical testing phase make it to market. High-throughput screening (HTS) is the primary method used by the pharmaceutical industry to identify initial lead compounds. Unfortunately, HTS has a high failure rate and is not particularly efficient at identifying viable drug leads. These shortcomings have encouraged the development of alternative methods to drive the drug discovery process. Specifically, nuclear magnetic resonance (NMR) spectroscopy and molecular docking are routinely being employed as important components of drug discovery research. Molecular docking provides an extremely rapid way to evaluate likely binders from a large chemical library with minimal cost. NMR ligand-affinity screens can directly detect a protein-ligand interaction, can measure a corresponding dissociation constant, and can reliably identify the ligand binding site and generate a co-structure. Furthermore, NMR ligand affinity screens and molecular docking are perfectly complementary techniques, where the combination of the two has the potential to improve the efficiency and success rate of drug discovery. This review will highlight the use of NMR ligand affinity screens and molecular docking in drug discovery and describe recent examples where the two techniques were combined to identify new and effective therapeutic drugs.

Perspectives on NMR in drug discovery: a technique comes of age

In the past decade, the potential of harnessing the ability of nuclear magnetic resonance (NMR) spectroscopy to monitor intermolecular interactions as a tool for drug discovery has been increasingly appreciated in academia and industry. In this Perspective, we highlight some of the major applications of NMR in drug discovery, focusing on hit and lead generation, and provide a critical analysis of its current and potential utility.

Perspectives of biomolecular NMR in drug discovery: the blessing and curse of versatility

The versatility of NMR and its broad applicability to several stages in the drug discovery process is well known and generally considered one of the major strengths of NMR (Pellecchia et al., Nature Rev Drug Discov 1:211-219, 2002; Stockman and Dalvit, Prog Nucl Magn Reson Spectrosc 41:187-231, 2002; Lepre et al., Comb Chem High throughput screen 5:583-590, 2002; Wyss et al., Curr Opin Drug Discov Devel 5:630-647, 2002; Jahnke and Widmer, Cell Mol Life Sci 61:580-599, 2004; Huth et al., Methods Enzymol 394:549-571, 2005b; Klages et al., Mol Biosyst 2:318-332, 2006; Takeuchi and Wagner, Curr Opin Struct Biol 16:109-117, 2006; Zartler and Shapiro, Curr Pharm Des 12:3963-3972, 2006). Indeed, NMR is the only biophysical technique which can detect and quantify molecular interactions, and at the same time provide detailed structural information with atomic level resolution. NMR should therefore be ideally suited and widely requested as a tool for drug discovery research, and numerous examples of drug discovery projects which have substantially benefited from NMR contributions or were even driven by NMR have been described in the literature. However, not all pharmaceutical companies have rigorously implemented NMR as integral tool of their research processes. Some companies invest with limited resources, and others do not use biomolecular NMR at all. This discrepancy in assessing the value of a technology is striking, and calls for clarification--under which circumstances can NMR provide added value to the drug discovery process? What kind of contributions can NMR make, and how is it implemented and integrated for maximum impact? This perspectives article suggests key areas of impact for NMR, and a model of integrating NMR with other technologies to realize synergies and maximize their value for drug discovery.