Library design for NMR-based screening

Unsupervised Analysis of Small Molecule Mixtures by Wavelet-Based Super-Resolved NMR

Resolving small molecule mixtures by nuclear magnetic resonance (NMR) spectroscopy has been of great interest for a long time for its precision, reproducibility, and efficiency. However, spectral analyses for such mixtures are often highly challenging due to overlapping resonance lines and limited chemical shift windows. The existing experimental and theoretical methods to produce shift NMR spectra in dealing with the problem have limited applicability owing to sensitivity issues, inconsistency, and/or the requirement of prior knowledge. Recently, we resolved the problem by decoupling multiplet structures in NMR spectra by the wavelet packet transform (WPT) technique. In this work, we developed a scheme for deploying the method in generating highly resolved WPT NMR spectra and predicting the composition of the corresponding molecular mixtures from their 1H NMR spectra in an automated fashion. The four-step spectral analysis scheme consists of calculating the WPT spectrum, peak matching with a WPT shift NMR library, followed by two optimization steps in producing the predicted molecular composition of a mixture. The robustness of the method was tested on an augmented dataset of 1000 molecular mixtures, each containing 3 to 7 molecules. The method successfully predicted the constituent molecules with a median true positive rate of 1.0 against the varying compositions, while a median false positive rate of 0.04 was obtained. The approach can be scaled easily for much larger datasets.

DMSO Solubility Assessment for Fragment-Based Screening

In this paper, we report comprehensive experimental and chemoinformatics analyses of the solubility of small organic molecules ("fragments") in dimethyl sulfoxide (DMSO) in the context of their ability to be tested in screening experiments. Here, DMSO solubility of 939 fragments has been measured experimentally using an NMR technique. A Support Vector Classification model was built on the obtained data using the ISIDA fragment descriptors. The analysis revealed 34 outliers: experimental issues were retrospectively identified for 28 of them. The updated model performs well in 5-fold cross-validation (balanced accuracy = 0.78). The datasets are available on the Zenodo platform (DOI:10.5281/zenodo.4767511) and the model is available on the website of the Laboratory of Chemoinformatics.

Rapid Quantification of Protein-Ligand Binding via 19F NMR Lineshape Analysis

Fluorine incorporation is ideally suited to many NMR techniques, and incorporation of fluorine into proteins and fragment libraries for drug discovery has become increasingly common. Here, we use one-dimensional 19F NMR lineshape analysis to quantify the kinetics and equilibrium thermodynamics for the binding of a fluorine-labeled Src homology 3 (SH3) protein domain to four proline-rich peptides. SH3 domains are one of the largest and most well-characterized families of protein recognition domains and have a multitude of functions in eukaryotic cell signaling. First, we showe that fluorine incorporation into SH3 causes only minor structural changes to both the free and bound states using amide proton temperature coefficients. We then compare the results from lineshape analysis of one-dimensional 19F spectra to those from two-dimensional 1H-15N heteronuclear single quantum coherence spectra. Their agreement demonstrates that one-dimensional 19F lineshape analysis is a robust, low-cost, and fast alternative to traditional heteronuclear single quantum coherence-based experiments. The data show that binding is diffusion limited and indicate that the transition state is highly similar to the free state. We also measured binding as a function of temperature. At equilibrium, binding is enthalpically driven and arises from a highly positive activation enthalpy for association with small entropic contributions. Our results agree with those from studies using different techniques, providing additional evidence for the utility of 19F NMR lineshape analysis, and we anticipate that this analysis will be an effective tool for rapidly characterizing the energetics of protein interactions.

Design of a Fragment-Screening Library

Herein we describe a method for the design, purchase, and assembly of a fragment-screening library from a list of commercially available compounds. The computational tools used in assessment of compound properties as well as the workflow for compound selection are provided for reference as implemented in commercially available software that is free and accessible to most academic users. The workflow can be modified as necessary to generate a fit-for-purpose fragment library with the desired compound property profiles. An analytical process for assessing the quality, identity, and suitability of a purchased fragment for inclusion in a screening collection is described. Results from our in-house library are presented as an example of compound progression through this quality control process.

DnaG Primase-A Target for the Development of Novel Antibacterial Agents

The bacterial primase-an essential component in the replisome-is a promising but underexploited target for novel antibiotic drugs. Bacterial primases have a markedly different structure than the human primase. Inhibition of primase activity is expected to selectively halt bacterial DNA replication. Evidence is growing that halting DNA replication has a bacteriocidal effect. Therefore, inhibitors of DNA primase could provide antibiotic agents. Compounds that inhibit bacterial DnaG primase have been developed using different approaches. In this paper, we provide an overview of the current literature on DNA primases as novel drug targets and the methods used to find their inhibitors. Although few inhibitors have been identified, there are still challenges to develop inhibitors that can efficiently halt DNA replication and may be applied in a clinical setting.

Identification of DNA primase inhibitors via a combined fragment-based and virtual screening

The structural differences between bacterial and human primases render the former an excellent target for drug design. Here we describe a technique for selecting small molecule inhibitors of the activity of T7 DNA primase, an ideal model for bacterial primases due to their common structural and functional features. Using NMR screening, fragment molecules that bind T7 primase were identified and then exploited in virtual filtration to select larger molecules from the ZINC database. The molecules were docked to the primase active site using the available primase crystal structure and ranked based on their predicted binding energies to identify the best candidates for functional and structural investigations. Biochemical assays revealed that some of the molecules inhibit T7 primase-dependent DNA replication. The binding mechanism was delineated via NMR spectroscopy. Our approach, which combines fragment based and virtual screening, is rapid and cost effective and can be applied to other targets.

Analysis of ligand-protein exchange by Clustering of Ligand Diffusion Coefficient Pairs (CoLD-CoP)

NMR spectroscopy is a powerful tool in describing protein structures and protein activity for pharmaceutical and biochemical development. This study describes a method to determine weak binding ligands in biological systems by using hierarchic diffusion coefficient clustering of multidimensional data obtained with a 400 MHz Bruker NMR. Comparison of DOSY spectrums of ligands of the chemical library in the presence and absence of target proteins show translational diffusion rates for small molecules upon interaction with macromolecules. For weak binders such as compounds found in fragment libraries, changes in diffusion rates upon macromolecular binding are on the order of the precision of DOSY diffusion measurements, and identifying such subtle shifts in diffusion requires careful statistical analysis. The "CoLD-CoP" (Clustering of Ligand Diffusion Coefficient Pairs) method presented here uses SAHN clustering to identify protein-binders in a chemical library or even a not fully characterized metabolite mixture. We will show how DOSY NMR and the "CoLD-CoP" method complement each other in identifying the most suitable candidates for lysozyme and wheat germ acid phosphatase.

Fragment-based drug discovery using the SHAPES method

The SHAPES method is one of several fragment-based drug discovery methods developed in the last decade. Molecules containing drug-like fragments are screened using NMR methods to find weakly binding (0.1 μM to multi-mM) hits that are then transformed into potent, viable leads. This review analyzes ten years of SHAPES screens, in which potent leads were found for 70 - 80% of the targets screened, and discusses lessons learned about how best to apply fragment-based lead discovery in the pharmaceutical environment. Detailed examples of lead discovery and optimization for the kinases REDK and MK2 are given. Finally, future directions are considered and a strategy is proposed for increasing efficiency by coupling fragment-based screening with receptor-assisted inhibitor design (NMR-RAID).

e-Drug3D: 3D structure collections dedicated to drug repurposing and fragment-based drug design

MOTIVATION

In the drug discovery field, new uses for old drugs, selective optimization of side activities and fragment-based drug design (FBDD) have proved to be successful alternatives to high-throughput screening. e-Drug3D is a database of 3D chemical structures of drugs that provides several collections of ready-to-screen SD files of drugs and commercial drug fragments. They are natural inputs in studies dedicated to drug repurposing and FBDD.

AVAILABILITY

e-Drug3D collections are freely available at http://chemoinfo.ipmc.cnrs.fr/e-drug3d.html either for download or for direct in silico web-based screenings.

Design of a multi-purpose fragment screening library using molecular complexity and orthogonal diversity metrics

Fragment Based Drug Discovery (FBDD) continues to advance as an efficient and alternative screening paradigm for the identification and optimization of novel chemical matter. To enable FBDD across a wide range of pharmaceutical targets, a fragment screening library is required to be chemically diverse and synthetically expandable to enable critical decision making for chemical follow-up and assessing new target druggability. In this manuscript, the Pfizer fragment library design strategy which utilized multiple and orthogonal metrics to incorporate structure, pharmacophore and pharmacological space diversity is described. Appropriate measures of molecular complexity were also employed to maximize the probability of detection of fragment hits using a variety of biophysical and biochemical screening methods. In addition, structural integrity, purity, solubility, fragment and analog availability as well as cost were important considerations in the selection process. Preliminary analysis of primary screening results for 13 targets using NMR Saturation Transfer Difference (STD) indicates the identification of uM-mM hits and the uniqueness of hits at weak binding affinities for these targets.

Design of screening collections for successful fragment-based lead discovery

A successful fragment-based lead discovery (FBLD) campaign largely depends on the content of the fragment collection being screened. To design a successful fragment collection, several factors must be considered, including collection size, property filters, hit follow-up considerations, and screening methods. In this chapter, we will discuss each factor and how it was applied to the design and assembly of one or more fragment collections in a major pharmaceutical company setting. We will also present examples and statistics of screening results from such collections and how subsequent collections can be improved. Lastly, we will provide a summary comparison of selected fragment collections from literature.

QSAR-based solubility model for drug-like compounds

Solubility plays a very important role in the selection of compounds for drug screening. In this context, a QSAR model was developed for predicting water solubility of drug-like compounds. First, a set of relevant parameters for establishing a drug-like chemical space was defined. The comparison of chemical structures from the FDAMDD and PHYSPROP databases allowed the selection of properties that were more efficient in discriminating drug-like compounds from other chemicals. These filters were later on applied to the PHYSPROP database and 1174 chemicals fulfilling these criteria and with experimental solubility information available at 25°C were retained. Several QSAR solubility models were developed from this set of compounds, and the best one was selected based on the accuracy of correct classifications obtained for randomly chosen training and validation subsets. Further validation of the model was performed with a set of 102 drugs for which experimental solubility data have been recently reported. A good agreement between the predictions and the experimental values confirmed the reliability of the QSAR model.

Integration of fragment screening and library design

With more than 10 years of practical experience and theoretical analysis, fragment-based drug discovery (FBDD) has entered the mainstream of the pharmaceutical and biotech industries. An array of biophysical techniques has been used to detect the weak interaction between a fragment and the target. Each technique presents its own requirements regarding the fragment collection and the target; therefore, in order to optimize the potential of FBDD, the nature of the target should be a driving factor for simultaneous development of both the library and the screening technology. A roadmap is now available to guide fragment-to-lead evolution when structural information is available. The next challenge is to apply FBDD to targets for which high-resolution structural information is not available.

NMR screening applied to the fragment-based generation of inhibitors of creatine kinase exploiting a new interaction proximate to the ATP binding site

Using an in-house fragment NMR library, we identified a set of ligands that bind rabbit muscular creatine kinase, an enzyme involved in key ATP-dependent processes. The ligands docked to the crystal structures of creatine kinase indicated that a phenylfuroic acid could enter into a pocket adjacent to the nucleotide binding site. This fragment served as an anchor to develop in silico a series of potential inhibitors which could partly access the nucleotide binding site. The short synthesis of only four derivatives provided entirely novel hit compounds that reversibly inhibit creatine kinase at micromolar concentrations with a mixed ATP-competitive/noncompetitive mechanism in agreement with the structural model of the inhibited enzyme. These initial biologically active compounds are novel and modular and exploit a new interaction proximate to the ATP binding site.

Fragment-based drug design: how big is too big?

Much has been discussed about the proper physicochemical properties (e.g., molecular weight, hydrophobicity, etc.) that should be considered when utilizing fragment leads in drug design. However, little has been reported as to what emphasis, if any, should be placed on the potency of the resulting fragment leads. In this report, a retrospective analysis of 18 highly optimized inhibitors is described in which the compounds were systematically deconstructed until the minimal binding elements could be identified. An analysis of the potency changes that were observed as the leads were reduced in size indicate that a nearly linear relationship exists between molecular weight and binding affinity over the entire range of sizes and potencies represented in the dataset. On the basis of these observations, prediction maps can be constructed that enable critical and quantitative assessments of the process of lead identification and optimization. These data place well-defined limits on the ideal size and potency of fragment leads that are being considered for use in fragment-based drug design.

Target structure-based discovery of small molecules that block human p53 and CREB binding protein association

Lysine acetylation of human tumor suppressor p53 in response to cellular stress signals is required for its function as a transcription factor that regulates cell cycle arrest, senescence, or apoptosis. Here, we report small molecules that block lysine 382-acetylated p53 association with the bromodomain of the coactivator CBP, an interaction essential for p53-induced transcription of the cell cycle inhibitor p21 in response to DNA damage. These chemicals were discovered in target structure-guided nuclear magnetic resonance spectroscopy screening of a focused chemical library constructed based on the structural knowledge of CBP bromodomain/p53-AcK382 binding. Structural characterization shows that these chemicals inhibit CBP/p53 association by binding to the acetyl-lysine binding site of the bromodomain. Cell-based functional assays demonstrate that the lead chemicals can modulate p53 stability and function in response to DNA damage.

Discovery of Ligands by a Combination of Computational and NMR-Based Screening: RNA as an Example Target

NMR for screening of knowledge-based focused libraries of compounds provides an efficient, cost-effective method to develop promising drug leads that target functionally important RNA structures. A knowledge-based focused library may be constructed from virtual (i.e., computational) screening of commercial or proprietary databases of available compounds for binding to the three-dimensional structure of a selected RNA target. Alternatively, the library may be constructed from compounds with properties deemed desirable, e.g., molecular moiety commonly found in drugs or known to bind RNA. The library ideally should be composed of small water-soluble, nonpeptide, nonnucleotide organic compounds. Various simple, robust NMR experiments are described that enable experimental screening of such a library for binding to a selected RNA structure. Some of the NMR experiments enable rapid mapping of the interaction site on the RNA to verify that the targeted structure is hit rather than the double helical region or a commonly occurring tetraloop. Other experiments enable elucidation of the ligand's binding moiety. Of course, any compounds thus identified should represent promising scaffolds suitable for easy chemical modification to enhance their pharmaceutical properties for subsequent drug development.

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.

Technological Advances in High-Throughput Screening

High-throughput screening (HTS) is the process of testing a large number of diverse chemical structures against disease targets to identify 'hits'. Compared to traditional drug screening methods, HTS is characterized by its simplicity, rapidness, low cost, and high efficiency, taking the ligand-target interactions as the principle, as well as leading to a higher information harvest. As a multidisciplinary field, HTS involves an automated operation-platform, highly sensitive testing system, specific screening model (in vitro), an abundant components library, and a data acquisition and processing system. Various technologies, especially the novel technologies such as fluorescence, nuclear-magnetic resonance, affinity chromatography, surface plasmon resonance, and DNA microarray, are now available, and the screening of more than 100,000 samples per day is already possible. Fluorescence-based assays include the scintillation proximity assay, time-resolved energy transfer, fluorescence anisotropy, fluorescence correlation spectroscopy, and fluorescence fluctuation spectroscopy. Fluorescence-based techniques are likely to be among the most important detection approaches used for HTS due to their high sensitivity and amenability to automation, giving the industry-wide drive to simplify, miniaturize, and speed up assays. The application of NMR technology to HTS is another recent trend in drug research. One advantage afforded by NMR technology is that it can provide direct information on the affinity of the screening compounds and the binding location of protein. The structure-activity relationship acquired from NMR analysis can sharpen the library design, which will be very important in furnishing HTS with well-defined drug candidates. Affinity chromatography used for library screening will provide the information on the fundamental processes of drug action, such as absorption, distribution, excretion, and receptor activation; also the eluting curve can give directly the possibility of candidate drug. SPR can measure the quantity of a complex formed between two molecules in real-time without the need for fluorescent or radioisotopic labels. SPR is capable of characterizing unmodified biopharmaceuticals, studying the interaction of drug candidates with macromolecular targets, and identifying binding partners during ligand fishing experiments. DNA microarrays can be used in HTS be used to further investigate the expression of biological targets associated with human disease, which then opens new and exciting opportunities for drug discovery. Without doubt, the addition of new technologies will further increase the application of HTS in drug screening and its related fields.

Structure-based screening and design in drug discovery

Structure-based screening represents an integrated approach for the identification and optimization of hits by the combined use of nuclear magnetic resonance (NMR) spectroscopy, homology modeling and X-ray crystallography. A general feature of the methodology is the introduction of structure-based methods (NMR, modeling and X-ray) early in the drug discovery process to optimize hits in terms of their affinities and specificities. This approach promises to deliver leads with improved physicochemical properties as compared with leads generated from a traditional HTS program. This review presents examples of structure-based screening from published and in-house drug discovery projects.

Visual and computational analysis of structure--activity relationships in high-throughput screening data

Novel analytic methods are required to assimilate the large volumes of structural and bioassay data generated by combinatorial chemistry and high-throughput screening programmes in the pharmaceutical and agrochemical industries. Recent work in visualisation and data mining has been used to develop structure--activity relationships from such chemical-biological datasets.

Automation of measurements and data evaluation in biomolecular NMR screening

This article reviews the equipment required for biomolecular screening applications in the automated preparation of samples and the acquisition of a large number of NMR data sets. New hardware connecting lab-bench and NMR spectrometers is introduced. In addition, the article focuses on software used for the automated processing of data and the calculation of similarity between spectra - a prerequisite for the identification of test compounds interacting with a target molecule.