Fragment screening: an introduction

There are clearly many different philosophies associated with adapting fragment screening into mainstream Drug Discovery Lead Generation strategies. Scientists at Astex, for instance, focus entirely on strategies involving use of X-ray crystallography and NMR. However, AstraZeneca uses a number of different fragment screening strategies. One approach is to screen a 2000 compound fragment set (with close to "lead-like" complexity) at 100 microM in parallel with every HTS such that the data are obtained on the entire screening collection at 10 microM plus the extra samples at 100 microM; this provides valuable compound potency data in a concentration range that is usually unexplored. The fragments are then screen-specific "privileged structures" that can be searched for in the rest of the HTS output and other databases as well as having synthesis follow-up. A typical workflow for a fragment screen within AstraZeneca is shown below (Figure 24) and highlights the desirability (particularly when screening >100 microM) for NMR and X-ray information to validate weak hits and give information on how to optimise them. In this chapter, we have provided an introduction to the theoretical and practical issues associated with the use of fragment methods and lead-likeness. Fragment-based approaches are still in an early stage of development and are just one of many interrelated techniques that are now used to identify novel lead compounds for drug development. Fragment based screening has some advantages, but like every other drug hunting strategy will not be universally applicable. There are in particular some practical challenges associated with fragment screening that relate to the generally lower level of potency that such compounds initially possess. Considerable synthetic effort has to be applied for post-fragment screening to build the sort of potency that would be expected to be found from a traditional HTS. However, if there are no low-hanging fruit in a screening collection to be found by HTS then the use of fragment screening can help find novelty that may lead to a target not being discarded as intractable. As such, the approach offers some significant advantages by providing less complex molecules, which may have better potential for novel drug optimisation and by enabling new chemical space to be more effectively explored. Many literature examples that cover examples of fragment screening approaches are still at the "proof of concept" stage and although delivering inhibitors or ligands, may still prove to be unsuitable when further ADMET and toxicity profiling is done. The next few years should see a maturing of the area, and as our understanding of how the concepts can be best applied, there are likely to be many more examples of attractive, small molecule hits, leads and candidate drugs derived from the approaches described.     

A simple strategy for mitigating the effect of data variability on the identification of active chemotypes from high-throughput screening data

Among the several goals of a high-throughput screening campaign is the identification of as many active chemotypes as possible for further evaluation. Often, however, the number of concentration response curves (e.g., IC(50)s or K(i)s) that can be collected following a primary screen is limited by practical constraints such as protein supply, screening workload, and so forth. One possible approach to this dilemma is to cluster the hits from the primary screen and sample only a few compounds from each cluster. This introduces the question as to how many compounds must be selected from a cluster to ensure that an active compound is identified, if it exists at all. This article seeks to address this question using a Monte Carlo simulation in which the dependence of the success of sampling is directly linked to screening data variability. Furthermore, the authors demonstrate that the use of replicated compounds in the screening collection can easily assess this variability and provide a priori guidance to the screener and chemist as to the extent of sampling required to maximize chemotype identification during the triage process. The individual steps of the Monte Carlo simulation provide insight into the correspondence between the percentage inhibition and eventual IC(50) curves.     

Fragment-based screening using X-ray crystallography and NMR spectroscopy

Approaches which start from a study of the interaction of very simple molecules (fragments) with the protein target are proving to be valuable additions to drug design. Fragment-based screening allows the complementarity between a protein active site and drug-like molecules to be rapidly and effectively explored, using structural methods. Recent improvements in the intensities of laboratory X-ray sources permits the collection of greater amounts of high-quality diffraction data and have been matched by developments in automation, crystallisation and data analysis. Developments in NMR screening, including the use of cryogenically cooled NMR probes and (19)F-containing reporter molecules have expanded the scope of this technique, while increasing the availability of binding site and quantitative affinity data for the fragments. Application of these methods has led to a greater knowledge of the chemical variety, structural features and energetics of protein-fragment interactions. While fragment-based screening has already been shown to reduce the timescales of the drug discovery process, a more detailed characterisation of fragment screening hits can reveal unexpected similarities between fragment chemotypes and protein active sites leading to improved understanding of the pharmacophores and the re-use of this information against other protein targets.     

Pharmacophore modeling and structure-based virtual screening to identify potent inhibitors targeting LuxP of Vibrio harveyi

The main aim of the study is to identify molecules that can disrupt quorum sensing (QS) system of Vibrio harveyi and therefore perhaps the production of toxins. Recently, a novel class of dioxazaborocane derivatives has been found to block AI-2 QS by targeting LuxPQ, but the mechanism of protein inhibition is still unclear. In order to investigate the possible binding modes, all the derivatives were docked into the binding site of LuxP using induced fit docking (IFD). The computed binding affinity is in good agreement with the experimental data. Resultant protein–ligand complexes were simulated using Desmond module and the result revealed better binding of ligands in the binding site of LuxP. Both pharmacophore- and structure-based virtual screening was performed to identify novel hits against LuxP. A filtering protocol, including lipinski filters, number of rotatable bonds and three levels of docking precisions were used for the selection of hits with specific properties. The virtual screening results were then combined and analyzed, which retrieved six hits with significant Glide score, binding affinity toward LuxP. The pharmacokinetic properties of the retrieved hits are in the acceptable range. Enrichment calculation was performed to validate the final hits, to discriminate the active compounds from the inactive compounds. The identified hits could serve as a base for further drug development against LuxP of Vibrio harveyi.     

A miniaturized high-throughput screening assay for fucosyltransferase VII

Fucosyltransferase VII (FucTVII) is a very promising drug target for treatment of inflammatory skin diseases. Its activity is required for synthesis of the sialyl-Lewis X glycoepitopes on the E- and P-selectin ligands, necessary for lymphocyte migration into the skin. High-throughput screening (HTS) of large chemical libraries has become the main source of novel chemical entities for the pharmaceutical industry. The screening of very large compound collections requires the use of specialized assay techniques that minimize time and costs. We describe the development of a miniaturized scintillation proximity assay for human FucTVII based on a oligosaccharide acceptor substrate that is identical to the glycosylation of the physiological substrate. In addition to assay development, the assay performance in a HTS campaign is shown. We screened 798,131 compounds from the Schering AG HTS library and identified 233 IC50 hits; 229 hits were FucTVII specific in so far as they did not inhibit either alpha-fucosidase or galactosyltransferase. In addition to screening a drug-like small-molecule collection, we worked on rational approaches to develop inhibitors or glycosidic decoys based on oligosaccharide-substrate analogues. The structure-activity relationship observed thereby is very narrow and shows strict requirements that are consistent with the described substrate specificity of FucTVII.     

High-capacity screening of arylalkylamine N-acetyltransferase inhibitors using a high-performance liquid chromatography system

Systematic screening is a natural development of any pharmacological program. Most enzyme inhibitor screens use indirect or "aspecific" methods, such as colorimetric or fluorimetric ones. These screening methods cause quite a few false-positive and false-negative hits. In order to limit these as much as possible, we developed a methodology using a high-performance liquid chromatography (HPLC) system for the medium throughput screening of serotonin N-acetyltransferase inhibitors. The core of this screening system is (1) the dramatic shortening of the analytical time down to 100 s per run by using a high-performance analytical column (Turbo), and (2) the use of absorption as opposed to radioactivity for detection of the product of the reaction (N-acetylserotonin). This system permits the analysis of about 1,000 compounds per day to be performed with a single HPLC system. This enzymatic system was taken as an example, because the methodology can be extended to many other enzymes, particularly transferases, phosphatases, and kinases.     

Integrating virtual screening in lead discovery

Target- and ligand-based virtual screening have emerged as resource-saving techniques that have been successfully applied to identify novel chemotypes in biologically active molecules. Eight confirmed virtual screening hits have recently been described and are discussed in this review, with focus on the workflow. These are then evaluated in the light of pharmacokinetics prediction (e.g. Caco-2 permeability, cytochrome P450 inhibition and hERG binding). We anticipate problems for five of these hits (e.g. cardiac toxicity), which warrant further experiments. Future challenges include dynamic tautomer/protonation treatment for both ligands and targets and improved pre- and post- virtual screening filters.     

Identification of metabotropic glutamate receptor antagonists using an automated high-throughput screening system

Antagonists to the human metabotropic glutamate receptor subtype 5a(mGluR(5a)) have been implicated as potential therapeutics for the treatment of a variety of nervous system disorders, including pain, anxiety, and Parkinson's disease. To discover novel antagonists to the mGluR(5a), a functional assay measuring agonist-induced intracellular calcium release was developed. The assay was used for the high-throughput screening of a large collection of compounds in single wells using a fully automated robotic platform. Primary high-throughput screening hits were subjected to a combination of data analysis and counterscreening assays to identify several compounds with both efficacy and selectivity for the metabotropic glutamate receptor target.     

Early phase drug discovery: Cheminformatics and computational techniques in identifying lead series

Early drug discovery processes rely on hit finding procedures followed by extensive experimental confirmation in order to select high priority hit series which then undergo further scrutiny in hit-to-lead studies. The experimental cost and the risk associated with poor selection of lead series can be greatly reduced by the use of many different computational and cheminformatic techniques to sort and prioritize compounds. We describe the steps in typical hit identification and hit-to-lead programs and then describe how cheminformatic analysis assists this process. In particular, scaffold analysis, clustering and property calculations assist in the design of high-throughput screening libraries, the early analysis of hits and then organizing compounds into series for their progression from hits to leads. Additionally, these computational tools can be used in virtual screening to design hit-finding libraries and as procedures to help with early SAR exploration.     

A chemoinformatics analysis of hit lists obtained from high-throughput affinity-selection screening

The high-throughput affinity-selection screening platform SpeedScreen was recently reported by the Novartis Institutes for BioMedical Research as a homogeneous, label-free screening technology with mass-spectrometry readout. SpeedScreen relies on the screening of compound mixtures with various target proteins and uses fast size-exclusion chromatography to separate target-bound from unbound substances. After disintegration of the target-binder complex, the binder molecules are identified by their molecular masses using liquid chromatography/mass spectrometry. The authors report an analysis of the molecular properties of hits obtained with SpeedScreen on 26 targets screened within the past few years at Novartis using this technology. Affinity-based SpeedScreen is a robust high-throughput screening technology that does not accumulate frequent hitters or potential covalent binders. The hits are representative of the most commonly identified scaffold classes observed for known drugs. Validated SpeedScreen hits tend to be enriched on more lipophilic and larger-molecular-weight compounds compared to the whole library. The potential for a reduced SpeedScreen screening set to be used in case only limited protein quantities are available is evaluated. Such a reduced compound set should also maximize the coverage of the high-performing regions of the chemical property and class spaces; chemoinformatics methods including genetic algorithms and divisive K-means clustering are used for this aim.     

Spiroimidazolidinone NPC1L1 inhibitors. 1: Discovery by 3D-similarity-based virtual screening

A series of spiroimidazolidinone NPC1L1 inhibitors was discovered by virtual screening of the Merck corporate sample repository using 3D-similarity-based screening. Selection of 330 compounds for testing in an in vitro NPC1L1 binding assay yielded six hits in six distinct chemical series. Follow-up 2D similarity searching yielded several sub- to low-micromolar leads; among these was spiroimidazolidinone 10, with an IC₅₀ of 2.5 μM. Compound 10 provided a useful scaffold to initiate a medicinal chemistry campaign.     

Using clustering techniques to improve hit selection in high-throughput screening

A typical modern high-throughput screening (HTS) operation consists of testing thousands of chemical compounds to select active ones for future detailed examination. The authors describe 3 clustering techniques that can be used to improve the selection of active compounds (i.e., hits). They are designed to identify quality hits in the observed HTS measurements. The considered clustering techniques were first tested on simulated data and then applied to analyze the assay inhibiting Escherichia coli dihydrofo-late reductase produced at the HTS laboratory of McMaster University.     

Integrating computational and mixture-based screening of combinatorial libraries

Mixture-based synthetic combinatorial library (MB-SCL) screening is a well-established experimental approach for rapidly retrieving structure–activity relationships (SAR) and identifying hits. Virtual screening is also a powerful approach that is increasingly being used in drug discovery programs and has a growing number of successful applications. However, limited efforts have been made to integrate both techniques. To this end, we combined experimental data from a MB-SCL of bicyclic guanidines screened against the κ-opioid receptor and molecular similarity methods. The activity data and similarity analyses were integrated in a biometric analysis–similarity map. Such a map allows the molecules to be categorized as actives, activity cliffs, low similarity to the reference compounds, or missed hits. A compound with IC₅₀ = 309 nM was found in the “missed hits” region, showing that active compounds can be retrieved from a MS-SCL via computational approaches. The strategy presented in this work is general and is envisioned as a general-purpose approach that can be applied to other MB-SCLs.     

An ultrahigh-throughput screening platform based on flow cytometric droplet sorting for mining novel enzymes from metagenomic libraries

Uncultivable microbial communities provide enormous reservoirs of enzymes, but their experimental identification by functional metagenomics is challenging, mainly due to the difficulty of screening enormous metagenomic libraries. Here, we propose a reliable and convenient ultrahigh-throughput screening platform based on flow cytometric droplet sorting (FCDS). The FCDS platform employs water-in-oil-in-water double emulsion droplets serving as single-cell enzymatic micro-reactors and a commercially available flow cytometer, and it can efficiently isolate novel biocatalysts from metagenomic libraries by processing single cells as many as 10⁸ per day. We demonstrated the power of this platform by screening a metagenomic library constructed from domestic running water samples. The FCDS assay screened 30 million micro-reactors in only 1 h, yielding a collection of esterase genes. Among these positive hits, Est WY was identified as a novel esterase with high catalytic efficiency and distinct evolutionary origin from other lipolytic enzymes. Our study manifests that the FCDS platform is a robust tool for functional metagenomics, with the potential to significantly improve the efficiency of exploring novel enzymes from nature.     

The identification of neurotensin NTS1 receptor partial agonists through a ligand-based virtual screening approach

We identified small molecule NTS1R agonist compounds through virtual screening of the corporate database using a ROCS approach that searches multi-conformer representations efficiently. As a starting point for the ROCS search, we used the known NTS1R selective antagonist, SR-48527, based on the hypothesis that NT agonists and antagonists might share similar binding regions. Conformations were expanded and selected as database search queries based on a cluster analysis. The search provided us with virtual hits that were tested in intracellular calcium mobilization assays of NTS1R agonist and antagonist activities measured in FLIPR format as well as in [(3)H]NT competition binding studies. The results indicated that two initial hits produced partial agonist activity with potency in the moderate micromolar range.     

Post-high-throughput screening analysis: an empirical compound prioritization scheme

An empirical scheme to evaluate and prioritize screening hits from high-throughput screening (HTS) is proposed. Negative scores are given when chemotypes found in the HTS hits are present in annotated databases such as MDDR and WOMBAT or for testing positive in toxicity-related experiments reported in TOXNET. Positive scores were given for higher measured biological activities, for testing negative in toxicity-related literature, and for good overlap when profiled against drug-related properties. Particular emphasis is placed on estimating aqueous solubility to prioritize in vivo experiments. This empirical scheme is given as an illustration to assist the decision-making process in selecting chemotypes and individual compounds for further experimentation, when confronted with multiple hits from high-throughput experiments. The decision-making process is discussed for a set of G-protein coupled receptor antagonists and validated on a literature example for dihydrofolate reductase inhibition.     

Discovery of a novel pyrazole series of group X secreted phospholipase A2 inhibitor (sPLA2X) via fragment based virtual screening

The discovery of potent novel pyrazole containing group X secreted phospholipase A2 inhibitors via structure based virtual screening is reported. Docking was applied on a large set of in-house fragment collection and pharmacophore feature matching was used to filter docking poses. The selected virtual screening hits was run in NMR screening, a potent pyrazole containing fragment hit was identified and confirmed by its complex X-ray structure and the following biochemical assay result. Expansion on the fragment hit has led to further improvement of potency while maintaining high ligand efficiency, thus supporting the further development of this chemical series.     

An image-based high-content screening assay for compounds targeting intracellular Leishmania donovani amastigotes in human macrophages

Leishmaniasis is a tropical disease threatening 350 million people from endemic regions. The available drugs for treatment are inadequate, with limitations such as serious side effects, parasite resistance or high cost. Driven by this need for new drugs, we developed a high-content, high-throughput image-based screening assay targeting the intracellular amastigote stage of different species of Leishmania in infected human macrophages. The in vitro infection protocol was adapted to a 384-well-plate format, enabling acquisition of a large amount of readouts by automated confocal microscopy. The reading method was based on DNA staining and required the development of a customized algorithm to analyze the images, which enabled the use of non-modified parasites. The automated analysis generated parameters used to quantify compound activity, including infection ratio as well as the number of intracellular amastigote parasites and yielded cytotoxicity information based on the number of host cells. Comparison of this assay with one that used the promastigote form to screen 26,500 compounds showed that 50% of the hits selected against the intracellular amastigote were not selected in the promastigote screening. These data corroborate the idea that the intracellular amastigote form of the parasite is the most appropriate to be used in primary screening assay for Leishmania.     

Structure-based screening,ADMET profiling,and molecular dynamic studies on mGlu2 receptor for identification of newer antiepileptic agents

Structure-based screening approach targeting mGlu2 receptor was carried out to identify good chemical starting points for anti-epileptic therapy. Interactive modes of final 12 compounds identified on the basis of screening of Asinex library, binding energy analysis, ADME profiling with special emphasis for CNS ranges, and toxicity analysis were studied and showed good binding modes in the mGluR2-active site. Enrichment studies for validating screening protocol were carried out which gave ROC values 0.98 (AUC = 0.96) for SP, 0.97 (AUC = 0.95) for XP with BEDROC analysis. Our results indicate that all the 12 hits showed good CNS drug-like properties, have better binding free energy and ADME profile as compared to co-crystallized ligand with the best ligand hit retaining conserved hydrogen bond interactions with Ala-166, Thr-168, Ser-145, and Arg-61 residues in bilobatevenus fly-trap domain of mGluR2 receptor. Molecular dynamics simulations proved that the two potential hits, qualifying all screening parameters, are stable in the receptor active site pocket, confirming the potential of the identified hits as a specific target for mGluR2. Because the newly discovered mGluR2 agonists are structurally different with T_c values ranging from 0.57 to 0.92, all of them can be considered for further de novo design methods.