Fragment-Based Lead Discovery and Design

Fragment-based approaches to discover ligands for tumor-specific E3 ligases

INTRODUCTION

Targeted protein degradation (TPD) has emerged as an innovative therapeutic strategy through selective degradation of specific proteins by harnessing the cellular ubiquitin-proteasome system (UPS), which involves over 600 E3 ubiquitin ligases. Recent proteome profiling reported tumor-specific E3 ligases in human. Development of those tumor-specific E3 ligase ligands would provide a solution for tumor-specific TPD for effective cancer treatment.

AREAS COVERED

This review provides a comprehensive list of E3 ligases found only in specific types of tumor from public databases and highlights examples of their ligands discovered through fragment-based approaches. It details their discovery process and potential applications for precise TPD and effective cancer treatments.

EXPERT OPINION

Current TPD strategies using proteolysis-targeting chimeras (PROTACs) primarily utilize general E3 ligases, such as CRBN and VHL. Since these E3 ligases demonstrate effective protein degradation activity in most human cell types, CRBN and VHL-based PROTACs can exhibit undesired TPD in off-target tissues, which often leads to the side effects. Therefore, developing tumor-specific E3 ligase ligands can be crucial for effective cancer treatments. Fragment-based ligand discovery (FBLD) approaches would accelerate the identification of these tumor-specific E3 ligase ligands and associated PROTACs, thereby advancing the field of targeted cancer therapies.

Identifying novel chemical matter against the Chikungunya virus nsP3 macrodomain through crystallographic fragment screening

Chikungunya virus (CHIKV) causes severe fever, rash and debilitating joint pain that can last for months1,2or even years. Millions of people have been infected with CHIKV, mostly in low and middle-income countries, and the virus continues to spread into new areas due to the geographical expansion of its mosquito hosts. Its genome encodes a macrodomain, which functions as an ADP-ribosyl hydrolase, removing ADPr from viral and host-cell proteins interfering with the innate immune response. Mutational studies have shown that the CHIKV nsP3 macrodomain is necessary for viral replication, making it a potential target for the development of antiviral therapeutics. We, therefore, performed a high-throughput crystallographic fragment screen against the CHIKV nsP3 macrodomain, yielding 109 fragment hits covering the ADPr-binding site and two adjacent subsites that are absent in the homologous macrodomain of SARS-CoV-2 but may be present in other alphaviruses, such as Venezuelan equine encephalitis virus (VEEV) and eastern equine encephalitis virus (EEEV). Finally, a subset of overlapping fragments was used to manually design three fragment merges covering the adenine and oxyanion subsites. The rich dataset of chemical matter and structural information discovered from this fragment screen is publicly available and can be used as a starting point for developing a CHIKV nsP3 macrodomain inhibitor.

Fluoromethylketone-Fragment Conjugates Designed as Covalent Modifiers of EcDsbA are Atypical Substrates

Disulfide bond protein A (DsbA) is an oxidoreductase enzyme that catalyzes the formation of disulfide bonds in Gram-negative bacteria. In Escherichia coli, DsbA (EcDsbA) is essential for bacterial virulence, thus inhibitors have the potential to act as antivirulence agents. A fragment-based screen was conducted against EcDsbA and herein we describe the development of a series of compounds based on a phenylthiophene hit identified from the screen. A novel thiol reactive and "clickable" ethynylfluoromethylketone was designed for reaction with azide-functionalized fragments to enable rapid and versatile attachment to a range of fragments. The resulting fluoromethylketone conjugates showed selectivity for reaction with the active site thiol of EcDsbA, however unexpectedly, turnover of the covalent adduct was observed. A mechanism for this turnover was investigated and proposed which may have wider ramifications for covalent reactions with dithiol-disulfide oxidoreducatases.

Synthesis and Chemoinformatic Analysis of Fluorinated Piperidines as 3D Fragments for Fragment-Based Drug Discovery

The concise synthesis of a small library of fluorinated piperidines from readily available dihydropyridinone derivatives has been described. The effect of the fluorination on different positions has then been evaluated by chemoinformatic tools. In particular, the compounds' pKa's have been calculated, revealing that the fluorine atoms notably lowered their basicity, which is correlated to the affinity for hERG channels resulting in cardiac toxicity. The "lead-likeness" and three-dimensionality have also been evaluated to assess their ability as useful fragments for drug design. A random screening on a panel of representative proteolytic enzymes was then carried out and revealed that one scaffold is recognized by the catalytic pocket of 3CLPro (main protease of SARS-CoV-2 coronavirus).

Fragment-based Drug Discovery Strategy and its Application to the Design of SARS-CoV-2 Main Protease Inhibitor

Severe Acute Respiratory Syndrome Coronavirus Type 2 (SARS-CoV-2) emerged at the end of 2019, causing a highly infectious and pathogenic disease known as 2019 coronavirus disease. This disease poses a serious threat to human health and public safety. The SARS-CoV-2 main protease (Mpro) is a highly sought-after target for developing drugs against COVID-19 due to its exceptional specificity. Its crystal structure has been extensively documented. Numerous strategies have been employed in the investigation of Mpro inhibitors. This paper is primarily concerned with Fragment-based Drug Discovery (FBDD), which has emerged as an effective approach to drug design in recent times. Here, we summarize the research on the approach of FBDD and its application in developing inhibitors for SARS-CoV-2 Mpro.

Hot-Spot Residue-Based Virtual Screening of Novel Selective Estrogen-Receptor Degraders for Breast Cancer Treatment

The estrogen-receptor alfa (ERα) is considered pivotal for breast cancer treatment. Although selective estrogen-receptor degraders (SERDs) have been developed to induce ERα degradation and antagonism, their agonistic effect on the uterine tissue and poor pharmacokinetic properties limit further application of ERα; thus, discovering novel SERDs is necessary. The ligand preferentially interacts with several key residues of the protein (defined as hot-spot residues). Improving the interaction with hot-spot residues of ERα offers a promising avenue for obtaining novel SERDs. In this study, pharmacophore modeling, molecular mechanics/generalized Born surface area (MM/GBSA), and amino-acid mutation were combined to determine several hot-spot residues. Focusing on the interaction with these hot-spot residues, hit fragments A1-A3 and A9 were virtually screened from two fragment libraries. Finally, these hit fragments were linked to generate compounds B1-B3, and their biological activities were evaluated. Remarkably, compound B1 exhibited potent antitumor activity against MCF-7 cells (IC50 = 4.21 nM), favorable ERα binding affinity (Ki = 14.6 nM), and excellent ERα degradative ability (DC50 = 9.7 nM), which indicated its potential to evolve as a promising SERD for breast cancer treatment.

Fragment-Based Approaches to Identify RNA Binders

Although fragment-based drug discovery (FBDD) has been successfully implemented and well-explored for protein targets, its feasibility for RNA targets is emerging. Despite the challenges associated with the selective targeting of RNA, efforts to integrate known methods of RNA binder discovery with fragment-based approaches have been fruitful, as a few bioactive ligands have been identified. Here, we review various fragment-based approaches implemented for RNA targets and provide insights into experimental design and outcomes to guide future work in the area. Indeed, investigations surrounding the molecular recognition of RNA by fragments address rather important questions such as the limits of molecular weight that confer selective binding and the physicochemical properties favorable for RNA binding and bioactivity.

Galileo: Three-dimensional searching in large combinatorial fragment spaces on the example of pharmacophores

Fragment spaces are an efficient way to model large chemical spaces using a handful of small fragments and a few connection rules. The development of Enamine's REAL Space has shown that large spaces of readily available compounds may be created this way. These are several orders of magnitude larger than previous libraries. So far, searching and navigating these spaces is mostly limited to topological approaches. A way to overcome this limitation is optimization via metaheuristics which can be combined with arbitrary scoring functions. Here we present Galileo, a novel Genetic Algorithm to sample fragment spaces. We showcase Galileo in combination with a novel pharmacophore mapping approach, called Phariety, enabling 3D searches in fragment spaces. We estimate the effectiveness of the approach with a small fragment space. Furthermore, we apply Galileo to two pharmacophore searches in the REAL Space, detecting hundreds of compounds fulfilling a HSP90 and a FXIa pharmacophore.

FastGrow: on-the-fly growing and its application to DYRK1A

Fragment-based drug design is an established routine approach in both experimental and computational spheres. Growing fragment hits into viable ligands has increasingly shifted into the spotlight. FastGrow is an application based on a shape search algorithm that addresses this challenge at high speeds of a few milliseconds per fragment. It further features a pharmacophoric interaction description, ensemble flexibility, as well as geometry optimization to become a fully fledged structure-based modeling tool. All features were evaluated in detail on a previously reported collection of fragment growing scenarios extracted from crystallographic data. FastGrow was also shown to perform competitively versus established docking software. A case study on the DYRK1A kinase, using recently reported new chemotypes, illustrates FastGrow's features in practice and its ability to identify active fragments. FastGrow is freely available to the public as a web server at https://fastgrow.plus/ and is part of the SeeSAR 3D software package.

Fragment hopping protocol for the design of small-molecule protein-protein interaction inhibitors

Fragment-based ligand discovery (FBLD) is one of the most successful approaches to designing small-molecule protein-protein interaction (PPI) inhibitors. The incorporation of computational tools to FBLD allows the exploration of chemical space in a time- and cost-efficient manner. Herein, a computational protocol for the development of small-molecule PPI inhibitors using fragment hopping, a fragment-based de novo design approach, is described and a case study is presented to illustrate the efficiency of this protocol. Fragment hopping facilitates the design of PPI inhibitors from scratch solely based on key binding features in the PPI complex structure. This approach is an open system that enables the inclusion of different state-of-the-art programs and softwares to improve its performances.

Genetic validation of Aspergillus fumigatus phosphoglucomutase as a viable therapeutic target in invasive aspergillosis

Aspergillus fumigatus is the causative agent of invasive aspergillosis, an infection with mortality rates of up to 50%. The glucan-rich cell wall of A. fumigatus is a protective structure that is absent from human cells and is a potential target for antifungal treatments. Glucan is synthesized from the donor uridine diphosphate glucose, with the conversion of glucose-6-phosphate to glucose-1-phosphate by the enzyme phosphoglucomutase (PGM) representing a key step in its biosynthesis. Here, we explore the possibility of selectively targeting A. fumigatus PGM (AfPGM) as an antifungal treatment strategy. Using a promoter replacement strategy, we constructed a conditional pgm mutant and revealed that pgm is required for A. fumigatus growth and cell wall integrity. In addition, using a fragment screen, we identified the thiol-reactive compound isothiazolone fragment of PGM as targeting a cysteine residue not conserved in the human ortholog. Furthermore, through scaffold exploration, we synthesized a para-aryl derivative (ISFP10) and demonstrated that it inhibits AfPGM with an IC50 of 2 μM and exhibits 50-fold selectivity over the human enzyme. Taken together, our data provide genetic validation of PGM as a therapeutic target and suggest new avenues for inhibiting AfPGM using covalent inhibitors that could serve as tools for chemical validation.

Novel Starting Points for Human Glycolate Oxidase Inhibitors, Revealed by Crystallography-Based Fragment Screening

Primary hyperoxaluria type I (PH1) is caused by AGXT gene mutations that decrease the functional activity of alanine:glyoxylate aminotransferase. A build-up of the enzyme’s substrate, glyoxylate, results in excessive deposition of calcium oxalate crystals in the renal tract, leading to debilitating renal failure. Oxidation of glycolate by glycolate oxidase (or hydroxy acid oxidase 1, HAO1) is a major cellular source of glyoxylate, and siRNA studies have shown phenotypic rescue of PH1 by the knockdown of HAO1, representing a promising inhibitor target. Here, we report the discovery and optimization of six low-molecular-weight fragments, identified by crystallography-based fragment screening, that bind to two different sites on the HAO1 structure: at the active site and an allosteric pocket above the active site. The active site fragments expand known scaffolds for substrate-mimetic inhibitors to include more chemically attractive molecules. The allosteric fragments represent the first report of non-orthosteric inhibition of any hydroxy acid oxidase and hold significant promise for improving inhibitor selectivity. The fragment hits were verified to bind and inhibit HAO1 in solution by fluorescence-based activity assay and surface plasmon resonance. Further optimization cycle by crystallography and biophysical assays have generated two hit compounds of micromolar (44 and 158 µM) potency that do not compete with the substrate and provide attractive starting points for the development of potent and selective HAO1 inhibitors.

Critical Assessment of a Structure-Based Screening Campaign for IDO1 Inhibitors: Tips and Pitfalls

Over the last two decades, indoleamine 2,3-dioxygenase 1 (IDO1) has attracted wide interest as a key player in immune regulation, fostering the design and development of small molecule inhibitors to restore immune response in tumor immunity. In this framework, biochemical, structural, and pharmacological studies have unveiled peculiar structural plasticity of IDO1, with different conformations and functional states that are coupled to fine regulation of its catalytic activity and non-enzymic functions. The large plasticity of IDO1 may affect its ligand recognition process, generating bias in structure-based drug design campaigns. In this work, we report a screening campaign of a fragment library of compounds, grounding on the use of three distinct conformations of IDO1 that recapitulate its structural plasticity to some extent. Results are instrumental to discuss tips and pitfalls that, due to the large plasticity of the enzyme, may influence the identification of novel and differentiated chemical scaffolds of IDO1 ligands in structure-based screening campaigns.

Trends in coordination of rhenium organometallic complexes in the Protein Data Bank

Radiopharmaceutical development has similar overall characteristics to any biomedical drug development requiring a compound's stability, aqueous solubility and selectivity to a specific disease site. However, organometallic complexes containing 188/186Re or 99mTc involve a d-block transition-metal radioactive isotope and therefore bring additional factors such as metal oxidation states, isotope purity and half life into play. This topical review is focused on the development of radiopharmaceuticals containing the radioisotopes of rhenium and technetium and, therefore, on the occurrence of these organometallic complexes in protein structures in the Worldwide Protein Data Bank (wwPDB). The purpose of incorporating the group 7 transition metals of rhenium/technetium in the protein and the reasons for study by protein crystallography are described, as certain PDB studies were not aimed at drug development. Technetium is used as a medical diagnostic agent and involves the 99mTc isotope which decays to release gamma radiation, thereby employed for its use in gamma imaging. Due to the periodic relationship among group 7 transition metals, the coordination chemistry of rhenium is similar (but not identical) to that of technetium. The types of reactions the potential model radiopharmaceutical would prefer to partake in, and by extension knowing which proteins and biomolecules the compound would react with in vivo, are needed. Crystallography studies, both small molecule and macromolecular, are a key aspect in understanding chemical coordination. Analyses of bonding modes, coordination to particular residues and crystallization conditions are presented. In our Forward look as a concluding summary of this topical review, the question we ask is: what is the best way for this field to progress?

Construction of 2-alkynyl aza-spiro[4,5]indole scaffolds via sequential C-H activations for modular click chemistry libraries

Herein, we have developed a strategy of sequential C-H activations of indole to construct novel 2-alkynyl aza-spiro[4,5]indole scaffolds, which incorporated both alkyne and spiro-units into indole. Gram-scale synthesis and a one-pot, three-step synthesis demonstrated the utility of this protocol. Hybrid conjugates with an oseltamivir derivative further offered a powerful tool for the construction of a versatile spiroindole-containing library via click chemistry.

Fragment Screening Reveals Starting Points for Rational Design of Galactokinase 1 Inhibitors to Treat Classic Galactosemia

Classic galactosemia is caused by loss-of-function mutations in galactose-1-phosphate uridylyltransferase (GALT) that lead to toxic accumulation of its substrate, galactose-1-phosphate. One proposed therapy is to inhibit the biosynthesis of galactose-1-phosphate, catalyzed by galactokinase 1 (GALK1). Existing inhibitors of human GALK1 (hGALK1) are primarily ATP-competitive with limited clinical utility to date. Here, we determined crystal structures of hGALK1 bound with reported ATP-competitive inhibitors of the spiro-benzoxazole series, to reveal their binding mode in the active site. Spurred by the need for additional chemotypes of hGALK1 inhibitors, desirably targeting a nonorthosteric site, we also performed crystallography-based screening by soaking hundreds of hGALK1 crystals, already containing active site ligands, with fragments from a custom library. Two fragments were found to bind close to the ATP binding site, and a further eight were found in a hotspot distal from the active site, highlighting the strength of this method in identifying previously uncharacterized allosteric sites. To generate inhibitors of improved potency and selectivity targeting the newly identified binding hotspot, new compounds were designed by merging overlapping fragments. This yielded two micromolar inhibitors of hGALK1 that were not competitive with respect to either substrate (ATP or galactose) and demonstrated good selectivity over hGALK1 homologues, galactokinase 2 and mevalonate kinase. Our findings are therefore the first to demonstrate inhibition of hGALK1 from an allosteric site, with potential for further development of potent and selective inhibitors to provide novel therapeutics for classic galactosemia.

Shape-Based Descriptors for Efficient Structure-Based Fragment Growing

Structure-based fragment growing is one of the key techniques in fragment-based drug design. Fragment growing is commonly practiced based on structural and biophysical data. Computational workflows are employed to predict which fragment elaborations could lead to high-affinity binders. Several such workflows exist but many are designed to be long running noninteractive systems. Shape-based descriptors have been proven to be fast and perform well at virtual-screening tasks. They could, therefore, be applied to the fragment-growing problem to enable an interactive fragment-growing workflow. In this work, we describe and analyze the use of specific shape-based directional descriptors for the task of fragment growing. The performance of these descriptors that we call ray volume matrices (RVMs) is evaluated on two data sets containing protein-ligand complexes. While the first set focuses on self-growing, the second measures practical performance in a cross-growing scenario. The runtime of screenings using RVMs as well as their robustness to three dimensional perturbations is also investigated. Overall, it can be shown that RVMs are useful to prefilter fragment candidates. For up to 84% of the 3299 generated self-growing cases and for up to 66% of the 326 generated cross-growing cases, RVMs could create poses with less than 2 Å root-mean-square deviation to the crystal structure with average query speeds of around 30,000 conformations per second. This opens the door for fast explorative screenings of fragment libraries.

Combining fragment docking with graph theory to improve ligand docking for homology model structures

Computational protein–ligand docking is well-known to be prone to inaccuracies in input receptor structures, and it is challenging to obtain good docking results with computationally predicted receptor structures (e.g. through homology modeling). Here we introduce a fragment-based docking method and test if it reduces requirements on the accuracy of an input receptor structures relative to non-fragment docking approaches. In this method, small rigid fragments are docked first using AutoDock Vina to generate a large number of favorably docked poses spanning the receptor binding pocket. Then a graph theory maximum clique algorithm is applied to find combined sets of docked poses of different fragment types onto which the complete ligand can be properly aligned. On the basis of these alignments, possible binding poses of complete ligand are determined. This docking method is first tested for bound docking on a series of Cytochrome P450 (CYP450) enzyme–substrate complexes, in which experimentally determined receptor structures are used. For all complexes tested, ligand poses of less than 1 Å root mean square deviations (RMSD) from the actual binding positions can be recovered. Then the method is tested for unbound docking with modeled receptor structures for a number of protein–ligand complexes from different families including the very recent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) protease. For all complexes, poses with RMSD less than 3 Å from actual binding positions can be recovered. Our results suggest that for docking with approximately modeled receptor structures, fragment-based methods can be more effective than common complete ligand docking approaches.

SyntaLinker: automatic fragment linking with deep conditional transformer neural networks

Linking fragments to generate a focused compound library for a specific drug target is one of the challenges in fragment-based drug design (FBDD). Hereby, we propose a new program named SyntaLinker, which is based on a syntactic pattern recognition approach using deep conditional transformer neural networks. This state-of-the-art transformer can link molecular fragments automatically by learning from the knowledge of structures in medicinal chemistry databases (e.g. ChEMBL database). Conventionally, linking molecular fragments was viewed as connecting substructures that were predefined by empirical rules. In SyntaLinker, however, the rules of linking fragments can be learned implicitly from known chemical structures by recognizing syntactic patterns embedded in SMILES notations. With deep conditional transformer neural networks, SyntaLinker can generate molecular structures based on a given pair of fragments and additional restrictions. Case studies have demonstrated the advantages and usefulness of SyntaLinker in FBDD.

Fragment Screening Hit Draws Attention to a Novel Transient Pocket Adjacent to the Recognition Site of the tRNA-Modifying Enzyme TGT

Fragment-based lead discovery was applied to tRNA-guanine transglycosylase, an enzyme modifying post-transcriptionally tRNAs in Shigella, the causative agent of shigellosis. TGT inhibition prevents translation of Shigella's virulence factor VirF, hence reducing pathogenicity. One discovered fragment opens a transient subpocket in the preQ₁-recognition site by pushing back an aspartate residue. This step is associated with reorganization of further amino acids structurally transforming a loop adjacent to the recognition site by duplicating the volume of the preQ₁-recognition pocket. We synthesized 6-carboxamido-, 6-hydrazido-, and 4-guanidino-benzimidazoles to target the opened pocket, including a dihydro-imidazoquinazoline with a propyn-1-yl exit vector pointing into the transient pocket and displacing a conserved water network. MD simulations and hydration-site analysis suggest water displacement to contribute favorably to ligand binding. A cysteine residue, exclusively present in bacterial TGTs, serves as gatekeeper of the transient subpocket. It becomes accessible upon pocket opening for selective covalent attachment of electrophilic ligands in eubacterial TGTs.

Molecular docking and dynamics simulations studies of OmpATb identifies four potential novel natural product-derived anti-Mycobacterium tuberculosis compounds

The outer membrane protein A (OmpATb) of Mycobacterium tuberculosis is a virulence factor that neutralizes the host pH to impede the uptake of hydrophilic antitubercular drugs. Identifying natural compounds with the potential to inhibit OmpATb could allow circumvention of the porin-like activities of OmpATb. Four potential leads comprising ZINC000003958185, ZINC000000157405, ZINC000000001392 and ZINC000034268676 were obtained by virtual screening of 6394 diverse natural products. Characterization of the binding interactions of the potential leads with OmpATb revealed nine critical residues comprising ARG86, LEU110, LEU113, LEU114, ALA115, PHE142, SER145, VAL146, and PHE151. Molecular dynamics simulations also revealed very stable protein-lead complexes. Most residues contributed lower binding energies to the overall molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) binding free energies of the interactions between the molecules and OmpATb protein. Induced Fit Docking (IFD) of the compounds regenerated poses of the molecular docking using AutoDock Vina. These molecules could be starting templates for designing inhibitors to bypass the pore mediating activities of OmpATb. Based on structural similarity, ZINC000034268676 was suggested as a potential scaffold for designing efflux pump inhibitors of the gate mediating activities of OmpATb and may enhance the uptake of hydrophilic drugs to reduce the duration time of tuberculosis treatment. Furthermore, structurally similar compounds available in the DrugBank database with a similarity threshold of 0.7 have been reported to exhibit antitubercular and anti-mycobacterial activities. These biomolecules can be further characterized experimentally to corroborate their antitubercular activity. Also, the skeletons of the molecules can be adopted as sub-structures for the design of future anti-mycobacterial drugs.

The design and development of covalent protein-protein interaction inhibitors for cancer treatment

Protein-protein interactions (PPIs) are central to a variety of biological processes, and their dysfunction is implicated in the pathogenesis of a range of human diseases, including cancer. Hence, the inhibition of PPIs has attracted significant attention in drug discovery. Covalent inhibitors have been reported to achieve high efficiency through forming covalent bonds with cysteine or other nucleophilic residues in the target protein. Evidence suggests that there is a reduced risk for the development of drug resistance against covalent drugs, which is a major challenge in areas such as oncology and infectious diseases. Recent improvements in structural biology and chemical reactivity have enabled the design and development of potent and selective covalent PPI inhibitors. In this review, we will highlight the design and development of therapeutic agents targeting PPIs for cancer therapy.

In silico Strategies to Support Fragment-to-Lead Optimization in Drug Discovery

Fragment-based drug (or lead) discovery (FBDD or FBLD) has developed in the last two decades to become a successful key technology in the pharmaceutical industry for early stage drug discovery and development. The FBDD strategy consists of screening low molecular weight compounds against macromolecular targets (usually proteins) of clinical relevance. These small molecular fragments can bind at one or more sites on the target and act as starting points for the development of lead compounds. In developing the fragments attractive features that can translate into compounds with favorable physical, pharmacokinetics and toxicity (ADMET-absorption, distribution, metabolism, excretion, and toxicity) properties can be integrated. Structure-enabled fragment screening campaigns use a combination of screening by a range of biophysical techniques, such as differential scanning fluorimetry, surface plasmon resonance, and thermophoresis, followed by structural characterization of fragment binding using NMR or X-ray crystallography. Structural characterization is also used in subsequent analysis for growing fragments of selected screening hits. The latest iteration of the FBDD workflow employs a high-throughput methodology of massively parallel screening by X-ray crystallography of individually soaked fragments. In this review we will outline the FBDD strategies and explore a variety of in silico approaches to support the follow-up fragment-to-lead optimization of either: growing, linking, and merging. These fragment expansion strategies include hot spot analysis, druggability prediction, SAR (structure-activity relationships) by catalog methods, application of machine learning/deep learning models for virtual screening and several de novo design methods for proposing synthesizable new compounds. Finally, we will highlight recent case studies in fragment-based drug discovery where in silico methods have successfully contributed to the development of lead compounds.

Fragments as Novel Starting Points for tRNA-Guanine Transglycosylase Inhibitors Found by Alternative Screening Strategies

Crystallography provides structural information crucial for fragment optimization, however several criteria must be met to screen directly on protein crystals as soakable, well-diffracting specimen must be available. We screened a 96-fragment library against the tRNA-modifying enzyme TGT using crystallography. Eight hits, some with surprising binding poses, were detected. However, the amount of data collection, reduction and refinement is assumed substantial. Therefore, having a reliable cascade of fast and cost-efficient methods available for pre-screening before embarking to elaborate crystallographic screening appears beneficial. This allows filtering of compounds to the most promising hits, available to rapidly progress from hit-to-lead. But how to ensure that this workflow is reliable? To answer this question, we also applied SPR and NMR to the same screening sample to study whether identical hits are retrieved. Upon hit-list comparisons, crystallography shows with NMR and SPR, only one overlapping hit and all three methods shared no common hits. This questions a cascade-type screening protocol at least in the current example. Compared to crystallography, SPR and NMR detected higher percentages of non-active-site binders suggesting the importance of running reporter ligand-based competitive screens in SPR and NMR, a requirement not needed in crystallography. Although not specific, NMR proved a more sensitive method relative to SPR and crystallography, as it picked up the highest numbers of binders.

Establishing Trypanosoma cruzi farnesyl pyrophosphate synthase as a viable target for biosensor driven fragment-based lead discovery

Procedures for producing and exploring Trypanosoma cruzi farnesyl pyrophosphate synthase (tcFPPS) for surface plasmon resonance (SPR) biosensor‐driven fragment‐based discovery have been established. The method requires functional sensor surfaces with high sensitivity for extended times and appropriate controls. Initial problems with protein stability and lack of useful reference compounds motivated optimization of experimental procedures and conditions. The improved methods enabled the production of pure, folded and dimeric protein, and identified procedures for storage and handling. A new coupled enzymatic assay, using luciferase for detection of pyrophosphate, was developed and used to confirm that the purified enzyme was active after purification and storage. It also confirmed that sensor surfaces prepared with structurally intact protein was active. An SPR‐biosensor assay for fragment library screening and hit confirmation was developed. A thermal shift assay was used in parallel. A library of 90 fragments was efficiently screened by both assays at a single concentration in the presence and absence of the catalytic cofactor Mg²⁺. Hits were selected on the basis of response levels or ΔT_m > 1°C and selectivity for tcFPPS in the presence of Mg²⁺. Characterization of hits by SPR showed that all had low affinities and the relationships between steady‐state responses and concentrations were not sufficiently hyperbolic for determination of K_D‐values. Instead, ranking could be performed from the slope of the linear relationship at low concentrations. This pilot screen confirms that the procedures developed herein enables SPR‐biosensor driven fragment‐based discovery of leads targeting tcFPPS, despite the lack of a reference compound.

Significance Statement

To enable the discovery of drugs, it is essential to have access to relevant forms of the target protein and valid biochemical methods for studying the protein and effects of compounds that may be evolved into drugs. We have established methods for the discovery of drugs for treatment of American Trypanosomiasis (Chagas disease), using farnesyl pyrophosphate synthase from Trypanosoma cruzi as a target.

Identification and characterization of fragment binding sites for allosteric ligand design using the site identification by ligand competitive saturation hotspots approach (SILCS-Hotspots)

BACKGROUND

Fragment-based ligand design is used for the development of novel ligands that target macromolecules, most notably proteins. Central to its success is the identification of fragment binding sites that are spatially adjacent such that fragments occupying those sites may be linked to create drug-like ligands. Current experimental and computational approaches that address this problem typically identify only a limited number of sites as well as use a limited number of fragment types.

METHODS

The site-identification by ligand competitive saturation (SILCS) approach is extended to the identification of fragment bindings sites, with the method termed SILCS-Hotspots. The approach involves precomputation of the SILCS FragMaps following which the identification of Hotspots, performed by identifying of all possible fragment binding sites on the full 3D structure of the protein followed by spatial clustering.

RESULTS

The SILCS-Hotspots approach identifies a large number of sites on the target protein, including many sites not accessible in experimental structures due to low binding affinities and binding sites on the protein interior. The identified sites are shown to recapitulate the location of known drug-like molecules in both allosteric and orthosteric binding sites on seven proteins including the androgen receptor, the CDK2 and Erk5 kinases, PTP1B phosphatase and three GPCRs; the β2-adrenergic, GPR40 fatty-acid binding and M2-muscarinic receptors. Analysis indicates the importance of considering all possible fragment binding sites, and not just those accessible to experimental methods, when identifying novel binding sites and performing ligand design versus just considering the most favorable sites. The approach is shown to identify a larger number of known binding sites of drug-like molecules versus the commonly used FTMap and Fpocket methods.

GENERAL SIGNIFICANCE

The present results indicate the potential utility of the SILCS-Hotspots approach for fragment-based rational design of ligands, including allosteric modulators.

Fundamental physical and chemical concepts behind “drug-likeness” and “natural product-likeness”

The discovery of a drug is known to be quite cumbersome, both in terms of the microscopic fundamental research behind it and the industrial scale manufacturing process. A major concern in drug discovery is the acceleration of the process and cost reduction. The fact that clinical trials cannot be accelerated, therefore, emphasizes the need to accelerate the strategies for identifying lead compounds at an early stage. We, herein, focus on the definition of what would be regarded as a “drug-like” molecule and a “lead-like” one. In particular, “drug-likeness” is referred to as resemblance to existing drugs, whereas “lead-likeness” is characterized by the similarity with structural and physicochemical properties of a “lead”compound, i.e. a reference compound or a starting point for further drug development. It is now well known that a huge proportion of the drug discovery is inspired or derived from natural products (NPs), which have larger complexity as well as size when compared with synthetic compounds. Therefore, similar definitions of “drug-likeness” and “lead-likeness” cannot be applied for the NP-likeness. Rather, there is the dire need to define and explain NP-likeness in regard to chemical structure. An attempt has been made here to give an overview of the general concepts associated with NP discovery, and to provide the foundational basis for defining a molecule as a “drug”, a “lead” or a “natural compound.”

Recent advances in the discovery and development of glyoxalase I inhibitors

Glyoxalase I (GLO1) is a homodimeric Zn²⁺-metalloenzyme that catalyses the transformation of methylglyoxal (MG) to d-lacate through the intermediate S-d-lactoylglutathione. Growing evidence indicates that GLO1 has been identified as a potential target for the treatment cancer and other diseases. Various inhibitors of GLO1 have been discovered or developed over the past several decades including natural or natural product-based inhibitors, GSH-based inhibitors, non-GSH-based inhibitors, etc. The aim of this review is to summarize recent achievements of concerning discovery, design strategies, as well as pharmacological aspects of GLO1 inhibitors with the target of promoting their development toward clinical application.

Why is interoperability between the two fields of chemical crystallography and protein crystallography so difficult?

The interoperability of chemical and biological crystallographic data is a key challenge to research and its application to pharmaceutical design. Research attempting to combine data from the two disciplines, small-molecule or chemical crystallography (CX) and macromolecular crystallography (MX), will face unique challenges including variations in terminology, software development, file format and databases which differ significantly from CX to MX. This perspective overview spans the two disciplines and originated from the investigation of protein binding to model radiopharmaceuticals. The opportunities of interlinked research while utilizing the two databases of the CSD (Cambridge Structural Database) and the PDB (Protein Data Bank) will be highlighted. The advantages of software that can handle multiple file formats and the circuitous route to convert organometallic small-molecule structural data for use in protein refinement software will be discussed. In addition some pointers to avoid being shipwrecked will be shared, such as the care which must be taken when interpreting data precision involving small molecules versus proteins.

Pharmacoinformatics-based identification of potential bioactive compounds against Ebola virus protein VP24

BACKGROUND

The impact of Ebola virus disease (EVD) is devastating with concomitant high fatalities. Currently, various drugs and vaccines are at different stages of development, corroborating the need to identify new therapeutic molecules. The VP24 protein of the Ebola virus (EBOV) plays a key role in the pathology and replication of the EVD. The VP24 protein interferes with the host immune response to viral infections and promotes nucleocapsid formation, thus making it a viable drug target. This study sought to identify putative lead compounds from the African flora with potential to inhibit the activity of the EBOV VP24 protein using pharmacoinformatics and molecular docking.

METHODS

An integrated library of 7675 natural products originating from Africa obtained from the AfroDB and NANPDB databases, as well as known inhibitors were screened against VP24 (PDB ID: 4M0Q) utilising AutoDock Vina after energy minimization using GROMACS. The top 19 compounds were physicochemically and pharmacologically profiled using ADMET Predictor™, SwissADME and DataWarrior. The mechanisms of binding between the molecules and EBOV VP24 were characterised using LigPlot+. The performance of the molecular docking was evaluated by generating a receiver operating characteristic (ROC) by screening known inhibitors and decoys against EBOV VP24. The prediction of activity spectra for substances (PASS) and machine learning-based Open Bayesian models were used to predict the anti-viral and anti-Ebola activity of the molecules, respectively.

RESULTS

Four natural products, namely, ZINC000095486070, ZINC000003594643, ZINC000095486008 and sarcophine were found to be potential EBOV VP24-inhibitiory molecules. The molecular docking results showed that ZINC000095486070 had high binding affinity of -9.7 kcal/mol with EBOV VP24, which was greater than those of the known VP24-inhibitors used as standards in the study including Ouabain, Nilotinib, Clomiphene, Torimefene, Miglustat and BCX4430. The area under the curve of the generated ROC for evaluating the performance of the molecular docking was 0.77, which was considered acceptable. The predicted promising molecules were also validated using induced-fit docking with the receptor using Schrödinger and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations. The molecules had better binding mechanisms and were pharmacologically profiled to have plausible efficacies, negligible toxicity as well as suitable for designing anti-Ebola scaffolds. ZINC000095486008 and sarcophine (NANPDB135) were predicted to possess anti-viral activity, while ZINC000095486070 and ZINC000003594643 to be anti-Ebola compounds.

CONCLUSION

The identified compounds are potential inhibitors worthy of further development as EBOV biotherapeutic agents. The scaffolds of the compounds could also serve as building blocks for designing novel Ebola inhibitors.

Formation of a highly dense tetra-rhenium cluster in a protein crystal and its implications in medical imaging

The fact that a protein crystal can serve as a chemical reaction vessel is intrinsically fascinating. That it can produce an electron-dense tetranuclear rhenium cluster compound from a rhenium tri-carbonyl tri-bromo starting compound adds to the fascination. Such a cluster has been synthesized previously in vitro, where it formed under basic conditions. Therefore, its synthesis in a protein crystal grown at pH 4.5 is even more unexpected. The X-ray crystal structures presented here are for the protein hen egg-white lysozyme incubated with a rhenium tri-carbonyl tri-bromo compound for periods of one and two years. These reveal a completed, very well resolved, tetra-rhenium cluster after two years and an intermediate state, where the carbonyl ligands to the rhenium cluster are not yet clearly resolved, after one year. A dense tetranuclear rhenium cluster, and its technetium form, offer enhanced contrast in medical imaging. Stimulated by these crystallography results, the unusual formation of such a species directly in an in vivo situation has been considered. It offers a new option for medical imaging compounds, particularly when considering the application of the pre-formed tetranuclear cluster, suggesting that it may be suitable for medical diagnosis because of its stability, preference of formation and biological compatibility.

Inhibition of autotransporter biogenesis by small molecules

Disarming pathogens by targeting virulence factors is a promising alternative to classic antibiotics. Many virulence factors in Gram-negative bacteria are secreted via the autotransporter (AT) pathway, also known as Type 5 secretion. These factors are secreted with the assistance of two membrane-based protein complexes: Sec and Bam. To identify inhibitors of the AT pathway, we used transcriptomics analysis to develop a fluorescence-based high-throughput assay that reports on the stress induced by the model AT hemoglobin protease (Hbp) when its secretion across the outer membrane is inhibited. Screening a library of 1600 fragments yielded the compound VUF15259 that provokes cell envelope stress and secretion inhibition of the ATs Hbp and Antigen-43. VUF15259 also impairs β-barrel folding activity of various outer membrane proteins. Furthermore, we found that mutants that are compromised in outer membrane protein biogenesis are more susceptible to VUF15259. Finally, VUF15259 induces the release of vesicles that appear to assemble in short chains. Taken together, VUF15259 is the first reported compound that inhibits AT secretion and our data are mostly consistent with VUF15259 interfering with the Bam-complex as potential mode of action. The validation of the presented assay incites its use to screen larger compound libraries with drug-like compounds.

Structure-based identification of novel CK2 inhibitors with a linear 2-propenone scaffold as anti-cancer agents

Protein kinase CK2 has emerged as an attractive cancer therapeutic target. Previous studies have highlighted the challenge of optimizing CK2 ATP-competitive inhibitors that have low druggability due to their polycyclic ring scaffolds. Therefore the development of novel inhibitors with non-polycyclic scaffolds emerges as a promising strategy for drug discovery targeting CK2. In this current study, based on the similar predicted binding poses of the linear 2-propenone scaffold of isoliquiritigenin with that of the polycyclic inhibitor CX-4945, a series of 2-propenone derivatives containing an amine-substituted five-membered heterocycle and a benzoic acid were designed, synthesized and evaluated for their in vitro CK2 inhibition and anti-cancer activity. Compound 8b was found to be the most potent CK2 inhibitor (IC₅₀ = 0.6 μM) with the anti-proliferative activity on HepG2 cancer cells (IC₅₀ = 14 μM), compared to the activity of isoliquiritigenin (IC₅₀ = 17 μM and 51 μM, respectively). Molecular docking was performed to understand the binding modes of the newly designed 2-propenone derivatives with CK2. Compound 8b formed the most favorable network of hydrogen bonds with both the hinge region and positive area. Our results indicate that CK2 derivatives with a linear 2-propenone scaffold are promising candidates for anti-cancer drug discovery.

Embracing the Diversity of Halogen Bonding Motifs in Fragment-Based Drug Discovery-Construction of a Diversity-Optimized Halogen-Enriched Fragment Library

Halogen bonds have recently gained attention in life sciences and drug discovery. However, it can be difficult to harness their full potential, when newly introducing them into an established hit or lead structure by molecular design. A possible solution to overcome this problem is the use of halogen-enriched fragment libraries (HEFLibs), which consist of chemical probes that provide the opportunity to identify halogen bonds as one of the main features of the binding mode. Initially, we have suggested the HEFLibs concept when constructing a focused library for finding p53 mutant stabilizers. Herein, we broaden and extent this concept aiming for a general HEFLib comprising a huge diversity of binding motifs and, thus, increasing the applicability to various targets. Using the construction principle of feature trees, we represent each halogenated fragment by treating all simple to complex substituents as modifiers of the central (hetero)arylhalide. This approach allows us to focus on the proximal binding interface around the halogen bond and, thus, its integration into a network of interactions based on the fragment's binding motif. As a first illustrative example, we generated a library of 198 fragments that unifies a two-fold strategy: Besides achieving a diversity-optimized basis of the library, we have extended this "core" by structurally similar "satellite compounds" that exhibit quite different halogen bonding interfaces. Tuning effects, i.e., increasing the magnitude of the σ-hole, can have an essential influence on the strength of the halogen bond. We were able to implement this key feature into the diversity selection, based on the rapid and efficient prediction of the highest positive electrostatic potential on the electron isodensity surface, representing the σ-hole, by VmaxPred.

Metal-Binding Pharmacophore Library Yields the Discovery of a Glyoxalase 1 Inhibitor

Anxiety and depression are common, highly comorbid psychiatric diseases that account for a large proportion of worldwide medical disability. Glyoxalase 1 (GLO1) has been identified as a possible target for the treatment of anxiety and depression. GLO1 is a Zn²⁺-dependent enzyme that isomerizes a hemithioacetal, formed from glutathione and methylglyoxal, to a lactic acid thioester. To develop active inhibitors of GLO1, fragment-based drug discovery was used to identify fragments that could serve as core scaffolds for lead development. After screening a focused library of metal-binding pharmacophores, 8-(methylsulfonylamino)quinoline (8-MSQ) was identified as a hit. Through computational modeling and synthetic elaboration, a potent GLO1 inhibitor was developed with a novel sulfonamide core pharmacophore. A lead compound was demonstrated to penetrate the blood-brain barrier, elevate levels of methylglyoxal in the brain, and reduce depression-like behavior in mice. These findings provide the basis for GLO1 inhibitors to treat depression and related psychiatric illnesses.

Towards Unraveling the Histone Code by Fragment Blind Docking

Histones serve as protein spools for winding the DNA in the nucleosome. High variability of their post-translational modifications result in a unique code system often responsible for the pathomechanisms of epigenetics-based diseases. Decoding is performed by reader proteins via complex formation with the N-terminal peptide tails of histones. Determination of structures of histone-reader complexes would be a key to unravel the histone code and the design of new drugs. However, the large number of possible histone complex variations imposes a true challenge for experimental structure determination techniques. Calculation of such complexes is difficult due to considerable size and flexibility of peptides and the shallow binding surfaces of the readers. Moreover, location of the binding sites is often unknown, which requires a blind docking search over the entire surface of the target protein. To accelerate the work in this field, a new approach is presented for prediction of the structure of histone H3 peptide tails docked to their targets. Using a fragmenting protocol and a systematic blind docking method, a collection of well-positioned fragments of the H3 peptide is produced. After linking the fragments, reconstitution of anchoring regions of the target-bound H3 peptide conformations was possible. As a first attempt of combination of blind and fragment docking approaches, our new method is named fragment blind docking (FBD).

Progress in Allosteric Database

An allosteric mechanism refers to the biological regulation process wherein macromolecules propagate the effect of ligand binding at one site to a spatially distant orthosteric locus, thus affecting activity. The theory has remained a trending topic in biology research for over 50 years, since the understanding of allostery is fundamental for gleaning numerous biological processes and developing new drug therapies. In the past two decades, the allosteric paradigm has evolved into more descriptive models, with ever-expanding amounts of experimental data pertaining to newly identified allosteric molecules. The AlloSteric Database (ASD, accessible at http://mdl.shsmu.edu.cn/ASD ), which is a comprehensive knowledge repository, has provided the public with integrated information encompassing allosteric proteins, modulators, sites, pathways, and networks to investigate allostery since 2009. In this chapter, we introduce the history and usage of the ASD and give attention to specific applications that have benefited from the ASD.

Generation of Polar Semi-Saturated Bicyclic Pyrazoles for Fragment-Based Drug-Discovery Campaigns

Synthesising polar semi-saturated bicyclic heterocycles can lead to better starting points for fragment-based drug discovery (FBDD) programs. We report the application of diverse chemistry to construct bicyclic systems from a common intermediate, where pyrazole, a privileged heteroaromatic able to bind effectively to biological targets, is fused to diverse saturated counterparts. The generated fragments can be further developed either after confirmation of their binding pose or early in the process, as their synthetic intermediates. Essential quality control (QC) for selection of small molecules to add to a fragment library is discussed.

In silico fragment-based drug design with SEED

We report on two fragment-based drug design protocols, SEED2XR and ALTA, which start by high-throughput docking. SEED2XR is a two-stage protocol for fragment-based drug design. The first stage is in silico and consists of the automatic docking of 10³-10⁴ fragments using SEED, which requires about 1 s per fragment. SEED is a docking software developed specifically for fragment docking and binding energy evaluation by a force field with implicit solvent. In the second stage of SEED2XR, the 10-10² fragments with the most favorable predicted binding energies are validated by protein X-ray crystallography. The recent applications of SEED2XR to bromodomains demonstrate that the whole SEED2XR protocol can be carried out in about a week of working time, with hit rates ranging from 10% to 40%. Information on fragment-target interactions generated by the SEED2XR protocol or directly from SEED docking has been used for the discovery of hundreds of hits. ALTA is a computational protocol for screening which identifies candidate ligands that preserve the interactions between the optimal SEED fragments and the protein target. Medicinal chemistry optimization of ligands predicted by ALTA has resulted in pre-clinical candidates for protein kinases and bromodomains. The high-throughput, very low cost, sustainability, and high hit rate of the SEED-based protocols, unreachable by purely experimental techniques, make them perfectly suitable for both academic and industrial drug discovery research.

Exhaustive sampling of the fragment space associated to a molecule leading to the generation of conserved fragments

The first step in hit optimization is the identification of the pharmacophore, which is normally achieved by deconstruction of the hit molecule to generate "deletion analogues." In silico fragmentation approaches often focus on the generation of small fragments that do not describe properly the fragment space associated to the deletion analogues. We present significant modifications to the molecular fragmentation programme molBLOCKS, which allows the exhaustive sampling of the fragment space associated with a molecule to generate all possible molecular fragments. This generates larger fragments, by combining the smallest fragments. Additionally, it has been modified to deal with the problem of changing pharmacophoric properties through fragmentation, by highlighting bond cuts. The modified molBLOCKS programme was used on a set of drug compounds, where it generated more unique fragments than standard fragmentation approaches by increasing the number of fragments derived per compound. This fragment set was found to be more diverse than those generated by standard fragmentation programmes and was relevant to drug discovery as it contains the key fragments representing the pharmacophoric elements associated with ligand recognition. The use of dummy atoms to highlight bond cuts further increases the information content of fragments by visualizing their previous bonding pattern.

Binding-Site Compatible Fragment Growing Applied to the Design of β2-Adrenergic Receptor Ligands

Fragment-based drug discovery is intimately linked to fragment extension approaches that can be accelerated using software for de novo design. Although computers allow for the facile generation of millions of suggestions, synthetic feasibility is however often neglected. In this study we computationally extended, chemically synthesized, and experimentally assayed new ligands for the β₂-adrenergic receptor (β₂AR) by growing fragment-sized ligands. In order to address the synthetic tractability issue, our in silico workflow aims at derivatized products based on robust organic reactions. The study started from the predicted binding modes of five fragments. We suggested a total of eight diverse extensions that were easily synthesized, and further assays showed that four products had an improved affinity (up to 40-fold) compared to their respective initial fragment. The described workflow, which we call "growing via merging" and for which the key tools are available online, can improve early fragment-based drug discovery projects, making it a useful creative tool for medicinal chemists during structure-activity relationship (SAR) studies.

Designing model imino bifunctional chelators for radiopharmaceuticals – in vitro antitumor activity, photoluminescence and structural analysis

Designed bifunctional chelators for the radionuclides of ^188/186Re or ^99mTc. Structure, DFT calculations, antitumor and imaging properties are described.

Virtual screening for inhibitors of the human TSLP:TSLPR interaction

The pro-inflammatory cytokine thymic stromal lymphopoietin (TSLP) plays a pivotal role in the pathophysiology of various allergy disorders that are mediated by type 2 helper T cell (Th2) responses, such as asthma and atopic dermatitis. TSLP forms a ternary complex with the TSLP receptor (TSLPR) and the interleukin-7-receptor subunit alpha (IL-7Rα), thereby activating a signaling cascade that culminates in the release of pro-inflammatory mediators. In this study, we conducted an in silico characterization of the TSLP:TSLPR complex to investigate the drugability of this complex. Two commercially available fragment libraries were screened computationally for possible inhibitors and a selection of fragments was subsequently tested in vitro. The screening setup consisted of two orthogonal assays measuring TSLP binding to TSLPR: a BLI-based assay and a biochemical assay based on a TSLP:alkaline phosphatase fusion protein. Four fragments pertaining to diverse chemical classes were identified to reduce TSLP:TSLPR complex formation to less than 75% in millimolar concentrations. We have used unbiased molecular dynamics simulations to develop a Markov state model that characterized the binding pathway of the most interesting compound. This work provides a proof-of-principle for use of fragments in the inhibition of TSLP:TSLPR complexation.