Lessons for fragment library design: analysis of output from multiple screening campaigns

A covalent fragment-based strategy targeting a novel cysteine to inhibit activity of mutant EGFR kinase

Several generations of ATP-competitive anti-cancer drugs that inhibit the activity of the intracellular kinase domain of the epidermal growth factor receptor (EGFR) have been developed over the past twenty years. The first-generation of drugs such as gefitinib bind reversibly and were followed by a second-generation such as dacomitinib that harbor an acrylamide moiety that forms a covalent bond with C797 in the ATP binding pocket. Resistance emerges through mutation of the T790 gatekeeper residue to methionine, which introduces steric hindrance to drug binding and increases the Km for ATP. A third generation of drugs, such as osimertinib were developed which were effective against T790M EGFR in which an acrylamide moiety forms a covalent bond with C797, although resistance has emerged by mutation to S797. A fragment-based screen to identify new starting points for an EGFR inhibitor serendipitously identified a fragment that reacted with C775, a previously unexploited residue in the ATP binding pocket for a covalent inhibitor to target. A number of acrylamide containing fragments were identified that selectively reacted with C775. One of these acrylamides was optimized to a highly selective inhibitor with sub-1 μM activity, that is active against T790M, C797S mutant EGFR independent of ATP concentration, providing a potential new strategy for pan-EGFR mutant inhibition.

DBGRU-SE: predicting drug-drug interactions based on double BiGRU and squeeze-and-excitation attention mechanism

The prediction of drug-drug interactions (DDIs) is essential for the development and repositioning of new drugs. Meanwhile, they play a vital role in the fields of biopharmaceuticals, disease diagnosis and pharmacological treatment. This article proposes a new method called DBGRU-SE for predicting DDIs. Firstly, FP3 fingerprints, MACCS fingerprints, Pubchem fingerprints and 1D and 2D molecular descriptors are used to extract the feature information of the drugs. Secondly, Group Lasso is used to remove redundant features. Then, SMOTE-ENN is applied to balance the data to obtain the best feature vectors. Finally, the best feature vectors are fed into the classifier combining BiGRU and squeeze-and-excitation (SE) attention mechanisms to predict DDIs. After applying five-fold cross-validation, The ACC values of DBGRU-SE model on the two datasets are 97.51 and 94.98%, and the AUC are 99.60 and 98.85%, respectively. The results showed that DBGRU-SE had good predictive performance for drug-drug interactions.

PAC-FragmentDEL - photoactivated covalent capture of DNA-encoded fragments for hit discovery

We describe a novel approach for screening fragments against a protein that combines the sensitivity of DNA-encoded library technology with the ability of fragments to explore what will bind. Each of the members of the library consists of a fragment which is linked to a photoactivatable diazirine moiety. Split and pool synthesis combines each fragment with a set of linkers with the version of the library reported here containing some 70k different compounds, each with an individual DNA code. Incubation of the library with a protein sample is followed by photoactivation, washing and subsequent PCR and sequencing which allows the individual fragment hits to be identified. We illustrate how the approach allows successful hit fragment identification using only microgram quantities of material for two targets. PAK4 is a kinase for which conventional fragment screening has generated many advance leads. The as yet undrugged target, 2-epimerase, presents a more challenging active site for identification of hit compounds. In both cases, PAC-FragmentDEL identified fragments validated as hits by ligand-observed NMR measurements and crystal structure determination of off-DNA sample binding to the proteins.

Fragment screening at AstraZeneca: developing the next generation biophysics fragment set

Fragment based drug discovery is a critical part of the lead generation toolbox and relies heavily on a readily available, high quality fragment library. Over years of use, the AstraZeneca fragment set had become partially depleted and instances of compound deterioration had been found. It was recognised that a redevelopment was required. This provided an opportunity to evolve our screening sets strategy, whilst ensuring that the quality of the fragment set met the robust requirements of fragment screening campaigns. In this communication we share the strategy employed, in particular highlighting two aspects of our approach that we believe others in the community would benefit from, namely that; (i) fragments were selected with input from Medicinal Chemists at an early stage, and (ii) the library was arranged in a layered format to ensure maximum flexibility on a per target basis.

Fragment Libraries Designed to Be Functionally Diverse Recover Protein Binding Information More Efficiently Than Standard Structurally Diverse Libraries

Current fragment-based drug design relies on the efficient exploration of chemical space by using structurally diverse libraries of small fragments. However, structurally dissimilar compounds can exploit the same interactions and thus be functionally similar. Using three-dimensional structures of many fragments bound to multiple targets, we examined if a better strategy for selecting fragments for screening libraries exists. We show that structurally diverse fragments can be described as functionally redundant, often making the same interactions. Ranking fragments by the number of novel interactions they made, we show that functionally diverse selections of fragments substantially increase the amount of information recovered for unseen targets compared to the amounts recovered by other methods of selection. Using these results, we design small functionally efficient libraries that can give significantly more information about new protein targets than similarly sized structurally diverse libraries. By covering more functional space, we can generate more diverse sets of drug leads.

Using Structure-guided Fragment-Based Drug Discovery to Target Pseudomonas aeruginosa Infections in Cystic Fibrosis

Cystic fibrosis (CF) is progressive genetic disease that predisposes lungs and other organs to multiple long-lasting microbial infections. Pseudomonas aeruginosa is the most prevalent and deadly pathogen among these microbes. Lung function of CF patients worsens following chronic infections with P. aeruginosa and is associated with increased mortality and morbidity. Emergence of multidrug-resistant, extensively drug-resistant and pandrug-resistant strains of P. aeruginosa due to intrinsic and adaptive antibiotic resistance mechanisms has failed the current anti-pseudomonal antibiotics. Hence new antibacterials are urgently needed to treat P. aeruginosa infections. Structure-guided fragment-based drug discovery (FBDD) is a powerful approach in the field of drug development that has succeeded in delivering six FDA approved drugs over the past 20 years targeting a variety of biological molecules. However, FBDD has not been widely used in the development of anti-pseudomonal molecules. In this review, we first give a brief overview of our structure-guided FBDD pipeline and then give a detailed account of FBDD campaigns to combat P. aeruginosa infections by developing small molecules having either bactericidal or anti-virulence properties. We conclude with a brief overview of the FBDD efforts in our lab at the University of Cambridge towards targeting P. aeruginosa infections.

Discovery of Novel BRD4 Ligand Scaffolds by Automated Navigation of the Fragment Chemical Space

Fragment-based drug discovery (FBDD) is a very effective hit identification method. However, the evolution of fragment hits into suitable leads remains challenging and largely artisanal. Fragment evolution is often scaffold-centric, meaning that its outcome depends crucially on the chemical structure of the starting fragment. Considering that fragment screening libraries cover only a small proportion of the corresponding chemical space, hits should be seen as probes highlighting privileged areas of the chemical space rather than actual starting points. We have developed an automated computational pipeline to mine the chemical space around any specific fragment hit, rapidly finding analogues that share a common interaction motif but are structurally novel and diverse. On a prospective application on the bromodomain-containing protein 4 (BRD4), starting from a known fragment, the platform yields active molecules with nonobvious scaffold changes. The procedure is fast and inexpensive and has the potential to uncover many hidden opportunities in FBDD.

Fragment-Derived Selective Inhibitors of Dual-Specificity Kinases DYRK1A and DYRK1B

The serine/threonine kinase DYRK1A has been implicated in regulation of a variety of cellular processes associated with cancer progression, including cell cycle control, DNA damage repair, protection from apoptosis, cell differentiation, and metastasis. In addition, elevated-level DYRK1A activity has been associated with increased severity of symptoms in Down's syndrome. A selective inhibitor of DYRK1A could therefore be of therapeutic benefit. We have used fragment and structure-based discovery methods to identify a highly selective, well-tolerated, brain-penetrant DYRK1A inhibitor which showed in vivo activity in a tumor model. The inhibitor provides a useful tool compound for further exploration of the effect of DYRK1A inhibition in models of disease.

Fragment Screening by NMR

This chapter describes the use of NMR to screen a fragment library as part of a fragment-based lead discovery (FBLD) campaign. The emphasis is on the practicalities involved in fragment screening by NMR, with particular attention to the use of 1D ligand-observed ¹H NMR experiments. An overview of the theoretical considerations underlying the choice of method and experimental configuration is given, along with a discussion of steps that can be taken in order to minimize the risk of experimental artifacts often associated with the identification of low-affinity interactions.

Mapping major SARS-CoV-2 drug targets and assessment of druggability using computational fragment screening: Identification of an allosteric small-molecule binding site on the Nsp13 helicase

The 2019 emergence of, SARS-CoV-2 has tragically taken an immense toll on human life and far reaching impacts on society. There is a need to identify effective antivirals with diverse mechanisms of action in order to accelerate preclinical development. This study focused on five of the most established drug target proteins for direct acting small molecule antivirals: Nsp5 Main Protease, Nsp12 RNA-dependent RNA polymerase, Nsp13 Helicase, Nsp16 2'-O methyltransferase and the S2 subunit of the Spike protein. A workflow of solvent mapping and free energy calculations was used to identify and characterize favorable small-molecule binding sites for an aromatic pharmacophore (benzene). After identifying the most favorable sites, calculated ligand efficiencies were compared utilizing computational fragment screening. The most favorable sites overall were located on Nsp12 and Nsp16, whereas the most favorable sites for Nsp13 and S2 Spike had comparatively lower ligand efficiencies relative to Nsp12 and Nsp16. Utilizing fragment screening on numerous possible sites on Nsp13 helicase, we identified a favorable allosteric site on the N-terminal zinc binding domain (ZBD) that may be amenable to virtual or biophysical fragment screening efforts. Recent structural studies of the Nsp12:Nsp13 replication-transcription complex experimentally corroborates ligand binding at this site, which is revealed to be a functional Nsp8:Nsp13 protein-protein interaction site in the complex. Detailed structural analysis of Nsp13 ZBD conformations show the role of induced-fit flexibility in this ligand binding site and identify which conformational states are associated with efficient ligand binding. We hope that this map of over 200 possible small-molecule binding sites for these drug targets may be of use for ongoing discovery, design, and drug repurposing efforts. This information may be used to prioritize screening efforts or aid in the process of deciphering how a screening hit may bind to a specific target protein.

Fragment-based drug discovery: opportunities for organic synthesis

This Review describes the increasing demand for organic synthesis to facilitate fragment-based drug discovery (FBDD), focusing on polar, unprotected fragments. In FBDD, X-ray crystal structures are used to design target molecules for synthesis with new groups added onto a fragment via specific growth vectors. This requires challenging synthesis which slows down drug discovery, and some fragments are not progressed into optimisation due to synthetic intractability. We have evaluated the output from Astex's fragment screenings for a number of programs, including urokinase-type plasminogen activator, hematopoietic prostaglandin D2 synthase, and hepatitis C virus NS3 protease-helicase, and identified fragments that were not elaborated due, in part, to a lack of commercially available analogues and/or suitable synthetic methodology. This represents an opportunity for the development of new synthetic research to enable rapid access to novel chemical space and fragment optimisation.

Using NMR Spectroscopy in the Fragment-Based Drug Discovery of Small-Molecule Anticancer Targeted Therapies

Against the challenge of providing personalized cancer care, the development of targeted therapies stands as a promising approach. The discovery of these agents can benefit from fragment-based drug discovery (FBDD) methods that help guide ligand design and provide key structural information on the targets of interest. In particular, nuclear magnetic resonance spectroscopy is a promising biophysical tool in fragment discovery due to its detection capabilities and versatility. This review provides an overview of FBDD, describes the basis of NMR-based fragment screening, summarizes some exciting technical advances reported over the past decades, and closes with a discussion of selected case studies where this technique has been used as part of drug discovery campaigns to produce lead compounds towards the design of anti-cancer targeted therapies.

Rapid optimisation of fragments and hits to lead compounds from screening of crude reaction mixtures

Fragment based methods are now widely used to identify starting points in drug discovery and generation of tools for chemical biology. A significant challenge is optimization of these weak binding fragments to hit and lead compounds. We have developed an approach where individual reaction mixtures of analogues of hits can be evaluated without purification of the product. Here, we describe experiments to optimise the processes and then assess such mixtures in the high throughput crystal structure determination facility, XChem. Diffraction data for crystals of the proteins Hsp90 and PDHK2 soaked individually with 83 crude reaction mixtures are analysed manually or with the automated XChem procedures. The results of structural analysis are compared with binding measurements from other biophysical techniques. This approach can transform early hit to lead optimisation and the lessons learnt from this study provide a protocol that can be used by the community.

Identifying Ortholog Selective Fragment Molecules for Bacterial Glutaredoxins by NMR and Affinity Enhancement by Modification with an Acrylamide Warhead

Illustrated here is the development of a new class of antibiotic lead molecules targeted at Pseudomonas aeruginosa glutaredoxin (PaGRX). This lead was produced to (a) circumvent efflux-mediated resistance mechanisms via covalent inhibition while (b) taking advantage of species selectivity to target a fundamental metabolic pathway. This work involved four components: a novel workflow for generating protein specific fragment hits via independent nuclear magnetic resonance (NMR) measurements, NMR-based modeling of the target protein structure, NMR guided docking of hits, and synthetic modification of the fragment hit with a vinyl cysteine trap moiety, i.e., acrylamide warhead, to generate the chimeric lead. Reactivity of the top warhead-fragment lead suggests that the ortholog selectivity observed for a fragment hit can translate into a substantial kinetic advantage in the mature warhead lead, which bodes well for future work to identify potent, species specific drug molecules targeted against proteins heretofore deemed undruggable.

Set-up and screening of a fragment library targeting the 14-3-3 protein interface

Protein-protein interactions (PPIs) are at the core of regulation mechanisms in biological systems and consequently became an attractive target for therapeutic intervention. PPIs involving the adapter protein 14-3-3 are representative examples given the broad range of partner proteins forming a complex with one of its seven human isoforms. Given the challenges represented by the nature of these interactions, fragment-based approaches offer a valid alternative for the development of PPI modulators. After having assembled a fragment set tailored on PPIs' modulation, we started a screening campaign on the sigma isoform of 14-3-3 adapter proteins. Through the use of both mono- and bi-dimensional nuclear magnetic resonance spectroscopy measurements, coupled with differential scanning fluorimetry, three fragment hits were identified. These molecules bind the protein at two different regions distant from the usual binding groove highlighting new possibilities for selective modulation of 14-3-3 complexes.

1D NMR WaterLOGSY as an efficient method for fragment-based lead discovery

WaterLOGSY is a sensitive ligand-observed NMR experiment for detection of interaction between a ligand and a protein and is now well-established as a screening technique for fragment-based lead discovery. Here we develop and assess a protocol to derive ligand epitope mapping from WaterLOGSY data and demonstrate its general applicability in studies of fragment-sized ligands binding to six different proteins (glycogen phosphorylase, protein peroxiredoxin 5, Bcl-x_L, Mcl-1, HSP90, and human serum albumin). We compare the WaterLOGSY results to those obtained from the more widely used saturation transfer difference experiments and to the 3D structures of the complexes when available. In addition, we evaluate the impact of ligand labile protons on the WaterLOGSY data. Our results demonstrate that the WaterLOGSY experiment can be used as an additional confirmation of the binding mode of a ligand to a protein.

How Size Matters: Diversity for Fragment Library Design

Fragment-based drug discovery (FBDD) has become a major strategy to derive novel lead candidates for various therapeutic targets, as it promises efficient exploration of chemical space by employing fragment-sized (MW < 300) compounds. One of the first challenges in implementing a FBDD approach is the design of a fragment library, and more specifically, the choice of its size and individual members. A diverse set of fragments is required to maximize the chances of discovering novel hit compounds. However, the exact diversity of a certain collection of fragments remains underdefined, which hinders direct comparisons among different selections of fragments. Based on structural fingerprints, we herein introduced quantitative metrics for the structural diversity of fragment libraries. Structures of commercially available fragments were retrieved from the ZINC database, from which libraries with sizes ranging from 100 to 100,000 compounds were selected. The selected libraries were evaluated and compared quantitatively, resulting in interesting size-diversity relationships. Our results demonstrated that while library size does matter for its diversity, there exists an optimal size for structural diversity. It is also suggested that such quantitative measures can guide the design of diverse fragment libraries under different circumstances.

Computational and Experimental Druggability Assessment of Human DNA Glycosylases

Due to a polar or even charged binding interface, DNA-binding proteins are considered extraordinarily difficult targets for development of small-molecule ligands and only a handful of proteins have been targeted successfully to date. Recently, however, it has been shown that development of selective and efficient inhibitors of 8-oxoguanine DNA glycosylase is possible. Here, we describe the initial druggability assessment of DNA glycosylases in a computational setting and experimentally investigate several methods to target endonuclease VIII-like 1 (NEIL1) with small-molecule inhibitors. We find that DNA glycosylases exhibit good predicted druggability in both DNA-bound and -unbound states. Furthermore, we find catalytic sites to be highly flexible, allowing for a range of interactions and binding partners. One flexible catalytic site was rationalized for NEIL1 and further investigated experimentally using both a biochemical assay in the presence of DNA and a thermal shift assay in the absence of DNA.

Establishing Drug Discovery and Identification of Hit Series for the Anti-apoptotic Proteins, Bcl-2 and Mcl-1

We describe our work to establish structure- and fragment-based drug discovery to identify small molecules that inhibit the anti-apoptotic activity of the proteins Mcl-1 and Bcl-2. This identified hit series of compounds, some of which were subsequently optimized to clinical candidates in trials for treating various cancers. Many protein constructs were designed to identify protein with suitable properties for different biophysical assays and structural methods. Fragment screening using ligand-observed NMR experiments identified several series of compounds for each protein. The series were assessed for their potential for subsequent optimization using ¹H and ¹⁵N heteronuclear single-quantum correlation NMR, surface plasmon resonance, and isothermal titration calorimetry measurements to characterize and validate binding. Crystal structures could not be determined for the early hits, so NMR methods were developed to provide models of compound binding to guide compound optimization. For Mcl-1, a benzodioxane/benzoxazine series was optimized to a K _d of 40 μM before a thienopyrimidine hit series was identified which subsequently led to the lead series from which the clinical candidate S 64315 (MIK 665) was identified. For Bcl-2, the fragment-derived series were difficult to progress, and a compound derived from a published tetrahydroquinone compound was taken forward as the hit from which the clinical candidate (S 55746) was obtained. For both the proteins, the work to establish a portfolio of assays gave confidence for identification of compounds suitable for optimization.

Screening Library Design

Thanks to technological advances and a greater understanding of the biological and chemical natures of targets and related diseases, high-throughput screening (HTS) has been allowed to be faster, cheaper, and more accessible. Yet, despite these increased technologies and understandings, the frequency of novel and drugs are being approved each year has not being increasing over the years. 2017 was considered a "bumper" year with a total of 46 approved drugs, over double that of the previous year. However, it is thought that part of the problem that HTS has not lived up to expectations is because of the contents of current chemical libraries. Therefore, new methods to design screening libraries are of great interest.

Quantitative metrics for drug-target ligandability

Ligandability is a prerequisite for druggability and is a much easier concept to understand, model and predict because it does not depend on the complex pharmacodynamic and pharmacokinetic mechanisms in the human body. In this review, we consider a metric for quantifying ligandability from experimental data. We discuss ligandability in terms of the balance between effort and reward. The metric is evaluated for a standard set of well-studied drug targets - some traditionally considered to be ligandable and some regarded as difficult. We suggest that this metric should be used to systematically improve computational predictions of ligandability, which can then be applied to novel drug targets to predict their tractability.

Approaches to target tractability assessment - a practical perspective

The assessment of the suitability of novel targets to intervention by different modalities, e.g. small molecules or antibodies, is increasingly seen as important in helping to select the most progressable targets at the outset of a drug discovery project. This perspective considers differing aspects of tractability and how it can be assessed using in silico and experimental approaches. We also share some of our experiences in using these approaches.

Current perspectives in fragment-based lead discovery (FBLD)

It is over 20 years since the first fragment-based discovery projects were disclosed. The methods are now mature for most ‘conventional’ targets in drug discovery such as enzymes (kinases and proteases) but there has also been growing success on more challenging targets, such as disruption of protein–protein interactions. The main application is to identify tractable chemical startpoints that non-covalently modulate the activity of a biological molecule. In this essay, we overview current practice in the methods and discuss how they have had an impact in lead discovery – generating a large number of fragment-derived compounds that are in clinical trials and two medicines treating patients. In addition, we discuss some of the more recent applications of the methods in chemical biology – providing chemical tools to investigate biological molecules, mechanisms and systems.

Multi-target Fragments Display Versatile Binding Modes

Promiscuity is an interesting concept in fragment-based drug design as fragments with low specificity can be advantageous for finding many screening hits. We present a PDB-wide analysis of multi-target fragments and their binding mode conservation. Focussing on multi-target fragments, we found that the majority shows non-conserved binding modes, even if they bind in a similar conformation or similar protein targets. Surprisingly, fragment properties alone are not able to predict whether a fragment will exhibit a versatile or conserved binding mode, emphasizing the interplay between protein and fragment features during a binding event and the importance of structure-based modelling.

Fragment Profiling Approach to Inhibitors of the Orphan M. tuberculosis P450 CYP144A1

Similarity between the ligand binding profiles of enzymes may aid functional characterization and be of greater relevance to inhibitor development than sequence similarity or structural homology. Fragment screening is an efficient approach for characterization of the ligand binding profile of an enzyme and has been applied here to study the family of cytochrome P450 enzymes (P450s) expressed by Mycobacterium tuberculosis (Mtb). The Mtb P450s have important roles in bacterial virulence, survival, and pathogenicity. Comparing the fragment profiles of seven of these enzymes revealed that P450s which share a similar biological function have significantly similar fragment profiles, whereas functionally unrelated or orphan P450s exhibit distinct ligand binding properties, despite overall high structural homology. Chemical structures that exhibit promiscuous binding between enzymes have been identified, as have selective fragments that could provide leads for inhibitor development. The similarity between the fragment binding profiles of the orphan enzyme CYP144A1 and CYP121A1, a characterized enzyme that is important for Mtb viability, provides a case study illustrating the subsequent identification of novel CYP144A1 ligands. The different binding modes of these compounds to CYP144A1 provide insight into structural and dynamic aspects of the enzyme, possible biological function, and provide the opportunity to develop inhibitors. Expanding this fragment profiling approach to include a greater number of functionally characterized and orphan proteins may provide a valuable resource for understanding enzyme-ligand interactions.

Native Mass Spectrometry in Fragment-Based Drug Discovery

The advent of native mass spectrometry (MS) in 1990 led to the development of new mass spectrometry instrumentation and methodologies for the analysis of noncovalent protein-ligand complexes. Native MS has matured to become a fast, simple, highly sensitive and automatable technique with well-established utility for fragment-based drug discovery (FBDD). Native MS has the capability to directly detect weak ligand binding to proteins, to determine stoichiometry, relative or absolute binding affinities and specificities. Native MS can be used to delineate ligand-binding sites, to elucidate mechanisms of cooperativity and to study the thermodynamics of binding. This review highlights key attributes of native MS for FBDD campaigns.

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.

A poised fragment library enables rapid synthetic expansion yielding the first reported inhibitors of PHIP(2), an atypical bromodomain

Research into the chemical biology of bromodomains has been driven by the development of acetyl-lysine mimetics. The ligands are typically anchored by binding to a highly conserved asparagine residue. Atypical bromodomains, for which the asparagine is mutated, have thus far proven elusive targets, including PHIP(2) whose parent protein, PHIP, has been linked to disease progression in diabetes and cancers. The PHIP(2) binding site contains a threonine in place of asparagine, and solution screening have yielded no convincing hits. We have overcome this hurdle by combining the sensitivity of X-ray crystallography, used as the primary fragment screen, with a strategy for rapid follow-up synthesis using a chemically-poised fragment library, which allows hits to be readily modified by parallel chemistry both peripherally and in the core. Our approach yielded the first reported hit compounds of PHIP(2) with measurable IC50 values by an AlphaScreen competition assay. The follow-up libraries of four poised fragment hits improved potency into the sub-mM range while showing good ligand efficiency and detailed structural data.

Chemical fragment arrays for rapid druggability assessment

Incorporation of early druggability assessment in the drug discovery process provides a means to prioritize target proteins for high-throughput screening.

A Role for Fragment-Based Drug Design in Developing Novel Lead Compounds for Central Nervous System Targets

Hundreds of millions of U.S. dollars are invested in the research and development of a single drug. Lead compound development is an area ripe for new design strategies. Therapeutic lead candidates have been traditionally found using high-throughput in vitro pharmacological screening, a costly method for assaying thousands of compounds. This approach has recently been augmented by virtual screening (VS), which employs computer models of the target protein to narrow the search for possible leads. A variant of VS is fragment-based drug design (FBDD), an emerging in silico lead discovery method that introduces low-molecular weight fragments, rather than intact compounds, into the binding pocket of the receptor model. These fragments serve as starting points for “growing” the lead candidate. Current efforts in virtual FBDD within central nervous system (CNS) targets are reviewed, as is a recent rule-based optimization strategy in which new molecules are generated within a 3D receptor-binding pocket using the fragment as a scaffold. This process not only places special emphasis on creating synthesizable molecules but also exposes computational questions worth addressing. Fragment-based methods provide a viable, relatively low-cost alternative for therapeutic lead discovery and optimization that can be applied to CNS targets to augment current design strategies.

Current Status and Future Direction of Fragment-Based Drug Discovery: A Computational Chemistry Perspective

Fragment-based drug discovery (FBDD) has become a well-established and widely used approach for lead identification. The computational chemistry community has played a central role in developing the ideas behind this area of research and computational tools are important throughout FBDD campaigns. This article discusses the evolution of best practice, on-going areas of debate and gaps in current capabilities from a computational chemistry perspective. In particular, the contribution of computational methods to areas such as fragment library design, screening analysis, data handling and the role of structure- and ligand-based design is discussed. The potential to combine FBDD with other hit-identification methods such as high-throughput screening in a more integrated approach is also highlighted.

A fluorescent approach for identifying P2X1 ligands

There are no commercially available, small, receptor-specific P2X1 ligands. There are several synthetic derivatives of the natural agonist ATP and some structurally-complex antagonists including compounds such as PPADS, NTP-ATP, suramin and its derivatives (e.g. NF279, NF449). NF449 is the most potent and selective ligand, but potencies of many others are not particularly high and they can also act at other P2X, P2Y and non-purinergic receptors. While there is clearly scope for further work on P2X1 receptor pharmacology, screening can be difficult owing to rapid receptor desensitisation. To reduce desensitisation substitutions can be made within the N-terminus of the P2X1 receptor, but these could also affect ligand properties. An alternative is the use of fluorescent voltage-sensitive dyes that respond to membrane potential changes resulting from channel opening. Here we utilised this approach in conjunction with fragment-based drug-discovery. Using a single concentration (300 μM) we identified 46 novel leads from a library of 1443 fragments (hit rate = 3.2%). These hits were independently validated by measuring concentration-dependence with the same voltage-sensitive dye, and by visualising the competition of hits with an Alexa-647-ATP fluorophore using confocal microscopy; confocal yielded k_on (1.142 × 10⁶ M⁻¹ s⁻¹) and k_off (0.136 s⁻¹) for Alexa-647-ATP (K_d = 119 nM). The identified hit fragments had promising structural diversity. In summary, the measurement of functional responses using voltage-sensitive dyes was flexible and cost-effective because labelled competitors were not needed, effects were independent of a specific binding site, and both agonist and antagonist actions were probed in a single assay. The method is widely applicable and could be applied to all P2X family members, as well as other voltage-gated and ligand-gated ion channels.

This article is part of the Special Issue entitled ‘Fluorescent Tools in Neuropharmacology’.

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A novel fluorescence-based screening approach for identifying P2X1 receptor ligand candidates.

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Fragment-based drug discovery applied to ligand-gated ion channels.

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The use of confocal microscopy to determine the kinetics and affinity of Alexa-647-ATP binding to P2X1 receptors.

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Alexa-647-ATP for imaging P2X1 receptors on live cells.

Identification and structure solution of fragment hits against kinetoplastid N-myristoyltransferase

Trypanosoma brucei N-myristoyltransferase (TbNMT) is an attractive therapeutic target for the treatment of human African trypanosomiasis. Pyrazole sulfonamide (DDD85646), a potent inhibitor of TbNMT, has been identified in previous studies; however, poor central nervous system exposure restricts its use to the haemolymphatic form (stage 1) of the disease. In order to identify new chemical matter, a fragment screen was carried out by ligand-observed NMR spectroscopy, identifying hits that occupy the DDD85646 binding site. Crystal structures of hits from this assay have been obtained in complex with the closely related NMT from Leishmania major, providing a structural starting point for the evolution of novel chemical matter.

Combinatorial Consensus Scoring for Ligand-Based Virtual Fragment Screening: A Comparative Case Study for Serotonin 5-HT(3)A, Histamine H(1), and Histamine H(4) Receptors

In the current study we have evaluated the applicability of ligand-based virtual screening (LBVS) methods for the identification of small fragment-like biologically active molecules using different similarity descriptors and different consensus scoring approaches. For this purpose, we have evaluated the performance of 14 chemical similarity descriptors in retrospective virtual screening studies to discriminate fragment-like ligands of three membrane-bound receptors from fragments that are experimentally determined to have no affinity for these proteins (true inactives). We used a complete fragment affinity data set of experimentally determined ligands and inactives for two G protein-coupled receptors (GPCRs), the histamine H1 receptor (H1R) and the histamine H4 receptor (H4R), and one ligand-gated ion channel (LGIC), the serotonin receptor (5-HT3AR), to validate our retrospective virtual screening studies. We have exhaustively tested consensus scoring strategies that combine the results of multiple actives (group fusion) or combine different similarity descriptors (similarity fusion), and for the first time systematically evaluated different combinations of group fusion and similarity fusion approaches. Our studies show that for these three case study protein targets both consensus scoring approaches can increase virtual screening enrichments compared to single chemical similarity search methods. Our cheminformatics analyses recommend to use a combination of both group fusion and similarity fusion for prospective ligand-based virtual fragment screening.

Biophysical methods for identifying fragment-based inhibitors of protein-protein interactions

Fragment-based lead discovery complements high-throughput screening and computer-aided drug design for the discovery of small-molecule inhibitors of protein-protein interactions. Fragments are molecules with molecular masses ca 280 Da or smaller, and are generally screened using structural or biophysical approaches. Several methods of fragment-based screening are feasible for any soluble protein that can be expressed and purified; specific techniques also have size limitations and/or require multiple milligrams of protein. This chapter describes some of the most common fragment-discovery methods, including surface plasmon resonance, nuclear magnetic resonance, differential scanning fluorimetry, and X-ray crystallography.

Large scale meta-analysis of fragment-based screening campaigns: privileged fragments and complementary technologies

A first step in fragment-based drug discovery (FBDD) often entails a fragment-based screen (FBS) to identify fragment "hits." However, the integration of conflicting results from orthogonal screens remains a challenge. Here we present a meta-analysis of 35 fragment-based campaigns at Novartis, which employed a generic 1400-fragment library against diverse target families using various biophysical and biochemical techniques. By statistically interrogating the multidimensional FBS data, we sought to investigate three questions: (1) What makes a fragment amenable for FBS? (2) How do hits from different fragment screening technologies and target classes compare with each other? (3) What is the best way to pair FBS assay technologies? In doing so, we identified substructures that were privileged for specific target classes, as well as fragments that were privileged for authentic activity against many targets. We also revealed some of the discrepancies between technologies. Finally, we uncovered a simple rule of thumb in screening strategy: when choosing two technologies for a campaign, pairing a biochemical and biophysical screen tends to yield the greatest coverage of authentic hits.

Efficient exploration of chemical space by fragment-based screening

Screening methods seek to sample a vast chemical space in order to identify starting points for further chemical optimisation. Fragment based drug discovery exploits the superior sampling of chemical space that can be achieved when the molecular weight is restricted. Here we show that commercially available fragment space is still relatively poorly sampled and argue for highly sensitive screening methods to allow the detection of smaller fragments. We analyse the properties of our fragment library versus the properties of X-ray hits derived from the library. We particularly consider properties related to the degree of planarity of the fragments.

Using chiral molecules as an approach to address low-druggability recognition sites

The content of chiral carbon atoms or structural complexity, which is known to correlate well with relevant physicochemical properties of small molecules, represents a promising descriptor that could fill the gap in existing drug discovery between ligand library filtering rules and the corresponding properties of the target's recognition site. Herein, we present an in silico study on the yet unclear underlying correlations between molecular complexity and other more sophisticated physicochemical and biological properties. By analyzing thousands of protein-ligand complexes from DrugBank, we show that increasing molecular complexity of drugs is an approach to addressing particularly low-druggability and polar recognition sites. We also show that biologically relevant protein classes characteristically bind molecules with a certain degree of structural complexity. Three distinct behaviors toward drug recognition are described. The reported results set the basis for a better understanding of protein-drug recognition, and open the possibility of including target information in the filtering of large ligand libraries for screening.