Fragment-based screening with natural products for novel anti-parasitic disease drug discovery

Decoding the molecular interplay in the central dogma: An overview of mass spectrometry-based methods to investigate protein-metabolite interactions

With the emergence of next-generation nucleotide sequencing and mass spectrometry-based proteomics and metabolomics tools, we have comprehensive and scalable methods to analyze the genes, transcripts, proteins, and metabolites of a multitude of biological systems. Despite the fascinating new molecular insights at the genome, transcriptome, proteome and metabolome scale, we are still far from fully understanding cellular organization, cell cycles and biology at the molecular level. Significant advances in sensitivity and depth for both sequencing as well as mass spectrometry-based methods allow the analysis at the single cell and single molecule level. At the same time, new tools are emerging that enable the investigation of molecular interactions throughout the central dogma of molecular biology. In this review, we provide an overview of established and recently developed mass spectrometry-based tools to probe metabolite-protein interactions-from individual interaction pairs to interactions at the proteome-metabolome scale.

Total Synthesis of Kopsone

A total synthesis of kopsone was achieved, featuring stereoselective preparation of an acyclic aldehyde having a protected hydroxylamine moiety via Ireland-Claisen rearrangement and intramolecular cycloaddition of an eight-membered cyclic nitrone to form the 2-azabicyclo[3.3.1]nonane skeleton.

Green Drug Discovery: Novel Fragment Space from the Biomass-Derived Molecule Dihydrolevoglucosenone (CyreneTM)

Biomass-derived molecules can provide a basis for sustainable drug discovery. However, their full exploration is hampered by the dominance of millions of old-fashioned screening compounds in classical high-throughput screening (HTS) libraries frequently utilized. We propose a fragment-based drug discovery (FBDD) approach as an efficient method to navigate biomass-derived drug space. Here, we perform a proof-of-concept study with dihydrolevoglucosenone (Cyrene^TM), a pyrolysis product of cellulose. Diverse synthetic routes afforded a 100-membered fragment library with a diversity in functional groups appended. The library overall performs well in terms of novelty, physicochemical properties, aqueous solubility, stability, and three-dimensionality. Our study suggests that Cyrene-based fragments are a valuable green addition to the drug discovery toolbox. Our findings can help in paving the way for new hit drug candidates that are based on renewable resources.

Design, Synthesis and Structure-Activity Relationships of Phenylalanine-Containing Peptidomimetics as Novel HIV-1 Capsid Binders Based on Ugi Four-Component Reaction

As a key structural protein, HIV capsid (CA) protein plays multiple roles in the HIV life cycle, and is considered a promising target for anti-HIV treatment. Based on the structural information of CA modulator PF-74 bound to HIV-1 CA hexamer, 18 novel phenylalanine derivatives were synthesized via the Ugi four-component reaction. In vitro anti-HIV activity assays showed that most compounds exhibited low-micromolar-inhibitory potency against HIV. Among them, compound I-19 exhibited the best anti-HIV-1 activity (EC50 = 2.53 ± 0.84 μM, CC50 = 107.61 ± 27.43 μM). In addition, I-14 displayed excellent HIV-2 inhibitory activity (EC50 = 2.30 ± 0.11 μM, CC50 > 189.32 μM) with relatively low cytotoxicity, being more potent than that of the approved drug nevirapine (EC50 > 15.02 μM, CC50 > 15.2 μM). Additionally, surface plasmon resonance (SPR) binding assays demonstrated direct binding to the HIV CA protein. Moreover, molecular docking and molecular dynamics simulations provided additional information on the binding mode of I-19 to HIV-1 CA. In summary, we further explored the structure—activity relationships (SARs) and selectivity of anti-HIV-1/HIV-2 of PF-74 derivatives, which is conducive to discovering efficient anti-HIV drugs.

Design of a Potent, Selective, and Brain-Penetrant Inhibitor of Wnt-Deactivating Enzyme Notum by Optimization of a Crystallographic Fragment Hit

Notum is a carboxylesterase that suppresses Wnt signaling through deacylation of an essential palmitoleate group on Wnt proteins. There is a growing understanding of the role Notum plays in human diseases such as colorectal cancer and Alzheimer's disease, supporting the need to discover improved inhibitors, especially for use in models of neurodegeneration. Here, we have described the discovery and profile of 8l (ARUK3001185) as a potent, selective, and brain-penetrant inhibitor of Notum activity suitable for oral dosing in rodent models of disease. Crystallographic fragment screening of the Diamond-SGC Poised Library for binding to Notum, supported by a biochemical enzyme assay to rank inhibition activity, identified 6a and 6b as a pair of outstanding hits. Fragment development of 6 delivered 8l that restored Wnt signaling in the presence of Notum in a cell-based reporter assay. Assessment in pharmacology screens showed 8l to be selective against serine hydrolases, kinases, and drug targets.

Efficient discovery of potential inhibitors for SARS-CoV-2 3C-like protease from herbal extracts using a native MS-based affinity-selection method

The 3C-like protease (3CLpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is essential to the virus life cycle and is supposed to be a potential target for the treatment of coronaviral infection. Traditional Chinese medicines (TCMs) have played an impressive role in the treatment of COVID-19 in China. The effectiveness of TCM formulations prompts scientists to take continuous effort on searching for bioactive small molecules from the ancient resources. Herein, we developed a native mass spectrometry-based affinity-selection method for rapid screening of active small molecules from crude herbal extracts applied for COVID-19 therapy. Six common herbs named Lonicera japonica, Scutellaria baicalensis, Forsythia suspensa, Glycyrrhiza uralensis, Cirsium japonicum, and Andrographis paniculata were investigated. After preliminary separation of the crude extracts, the fractions were incubated with 3CLpro. A native MS-based affinity screening assay was then conducted to search for the protein-ligand complexes. A UHPLC-Q/TOF-MS with UNIFI data acquisition and data processing software was applied to identify the hit compounds. Standard compounds were used to verify the outcomes. Among the 16 hits, three flavonoids, baicalein, scutellarein and ganhuangenin, were identified as potential noncovalent inhibitors against 3CLpro with IC₅₀ values of 0.94, 3.02, and 0.84 μM, respectively. Their binding affinities were further characterized by native MS, with K_d values being 1.43, 3.85, and 1.09 μM, respectively. Overall, we established an efficient native MS-based strategy for discovering 3CLpro ligands from crude mixtures, which supplies a potential strategy of small molecule lead discovery from TCMs.

Advanced Computational Methodologies Used in the Discovery of New Natural Anticancer Compounds

Natural chemical compounds have been widely investigated for their programmed necrosis causing characteristics. One of the conventional methods for screening such compounds is the use of concentrated plant extracts without isolation of active moieties for understanding pharmacological activity. For the last two decades, modern medicine has relied mainly on the isolation and purification of one or two complicated active and isomeric compounds. The idea of multi-target drugs has advanced rapidly and impressively from an innovative model when first proposed in the early 2000s to one of the popular trends for drug development in 2021. Alternatively, fragment-based drug discovery is also explored in identifying target-based drug discovery for potent natural anticancer agents which is based on well-defined fragments opposite to use of naturally occurring mixtures. This review summarizes the current key advancements in natural anticancer compounds; computer-assisted/fragment-based structural elucidation and a multi-target approach for the exploration of natural compounds.

Discovery of new non-pyrimidine scaffolds as Plasmodium falciparum DHFR inhibitors by fragment-based screening

In various malaria-endemic regions, the appearance of resistance has precluded the use of pyrimidine-based antifolate drugs. Here, a three-step fragment screening was used to identify new non-pyrimidine Plasmodium falciparum dihydrofolate reductase (PfDHFR) inhibitors. Starting from a 1163-fragment commercial library, a two-step differential scanning fluorimetry screen identified 75 primary fragment hits. Subsequent enzyme inhibition assay identified 11 fragments displaying IC₅₀ in the 28-695 μM range and selectivity for PfDHFR. In addition to the known pyrimidine, three new anti-PfDHFR chemotypes were identified. Fragments from each chemotype were successfully co-crystallized with PfDHFR, revealing a binding in the active site, in the vicinity of catalytic residues, which was confirmed by molecular docking on all fragment hits. Finally, comparison with similar non-hit fragments provides preliminary input on available growth vectors for future drug development.

Feature-Based Molecular Network-Guided Dereplication of Natural Bioactive Products from Leaves of Stryphnodendron pulcherrimum (Willd.) Hochr

Stryphnodendron pulcherrimum is a species known to have a high content of tannins. Accordingly, its preparations are used in southern Pará, Brazil, for their anti-inflammatory and antimicrobial activities, but so far, its chemical profile composition remains essentially unknown. We herein describe the compounds present in a hydro-acetonic extract from S. pulcherrimum leaves as revealed by dereplication via ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry. The data were combined with spectral organization, spectral matching through the Global Natural Products Social platform, in silico annotation and taxonomical ponderation. Several types of phenolic compounds were identified such as gallic acids, flavan-3-ols and flavone-like compounds. From these, 5 have been recently reported by our group, whereas 44 are reported here for the first time in this tree species, and 41 (out of 49) for this genus. The results highlight the possible role of Stryphnodendron pulcherrimum as a renewable source for natural bioactive products with potential pharmaceutical applications.

Applications of Solution NMR in Drug Discovery

During the past decades, solution nuclear magnetic resonance (NMR) spectroscopy has demonstrated itself as a promising tool in drug discovery. Especially, fragment-based drug discovery (FBDD) has benefited a lot from the NMR development. Multiple candidate compounds and FDA-approved drugs derived from FBDD have been developed with the assistance of NMR techniques. NMR has broad applications in different stages of the FBDD process, which includes fragment library construction, hit generation and validation, hit-to-lead optimization and working mechanism elucidation, etc. In this manuscript, we reviewed the current progresses of NMR applications in fragment-based drug discovery, which were illustrated by multiple reported cases. Moreover, the NMR applications in protein-protein interaction (PPI) modulators development and the progress of in-cell NMR for drug discovery were also briefly summarized.

LEADS-FRAG: A Benchmark Data Set for Assessment of Fragment Docking Performance

Fragment-based drug design is a popular approach in drug discovery, which makes use of computational methods such as molecular docking. To assess fragment placement performance of molecular docking programs, we constructed LEADS-FRAG, a benchmark data set containing 93 high-quality protein-fragment complexes that were selected from the Protein Data Bank using a rational and unbiased process. The data set contains fully prepared protein and fragment structures and is publicly available. Moreover, we used LEADS-FRAG for evaluating the small-molecule docking programs AutoDock, AutoDock Vina, FlexX, and GOLD for their fragment docking performance. GOLD in combination with the scoring function ChemPLP and AutoDock Vina performed best and generated near-native conformations (root mean square deviation <1.5 Å) for more than 50% of the data set considering the top-ranked docking pose. Taking into account all docking poses, the tested programs generated near-native conformations for up to 86% of the fragments in LEADS-FRAG. By rescoring all docking poses with the GOLD scoring functions and the Protein-Ligand Informatics force field, the number of near-native conformations increased up to 40% with respect to the top-rescored poses. Our results show that conventional small-molecule docking programs achieve a satisfactory fragment docking performance when utilizing rescoring.

Exploiting the tolerant region I of the non-nucleoside reverse transcriptase inhibitor (NNRTI) binding pocket. Part 2: Discovery of diarylpyrimidine derivatives as potent HIV-1 NNRTIs with high Fsp3 values and favorable drug-like properties

To yield potent HIV-1 non-nucleoside reverse transcriptase inhibitors (NNRTIs) with favorable drug-like properties, a series of novel diarylpyrimidine derivatives targeting the tolerant region I of the NNRTI binding pocket were designed, synthesized and biologically evaluated. The most active inhibitor 10c exhibited outstanding antiviral activity against most of the viral panel, being about 2-fold (wild-type, EC₅₀ = 0.0021 μM), 1.7-fold (K103N, EC₅₀ = 0.0019 μM), and slightly more potent (E138K, EC₅₀ = 0.0075 μM) than the NNRTI drug etravirine (ETR). Additionally, 10c was endowed with relatively low cytotoxicity (CC₅₀ = 18.52 μM). More importantly, 10c possessed improved drug-like properties compared to those of ETR with an increased Fsp³ (Fraction of sp³ carbon atoms) value. Furthermore, the molecular dynamics simulation and molecular docking studies were implemented to reveal the binding mode of 10c in the binding pocket. Taken together, 10c is a promising lead compound that is worth further investigation.

Combining structure and genomics to understand antimicrobial resistance

Antimicrobials against bacterial, viral and parasitic pathogens have transformed human and animal health. Nevertheless, their widespread use (and misuse) has led to the emergence of antimicrobial resistance (AMR) which poses a potentially catastrophic threat to public health and animal husbandry. There are several routes, both intrinsic and acquired, by which AMR can develop. One major route is through non-synonymous single nucleotide polymorphisms (nsSNPs) in coding regions. Large scale genomic studies using high-throughput sequencing data have provided powerful new ways to rapidly detect and respond to such genetic mutations linked to AMR. However, these studies are limited in their mechanistic insight. Computational tools can rapidly and inexpensively evaluate the effect of mutations on protein function and evolution. Subsequent insights can then inform experimental studies, and direct existing or new computational methods. Here we review a range of sequence and structure-based computational tools, focussing on tools successfully used to investigate mutational effect on drug targets in clinically important pathogens, particularly Mycobacterium tuberculosis. Combining genomic results with the biophysical effects of mutations can help reveal the molecular basis and consequences of resistance development. Furthermore, we summarise how the application of such a mechanistic understanding of drug resistance can be applied to limit the impact of AMR.

Combined Protein- and Ligand-Observed NMR Workflow to Screen Fragment Cocktails against Multiple Proteins: A Case Study Using Bromodomains

As fragment-based drug discovery has become mainstream, there has been an increase in various screening methodologies. Protein-observed ¹⁹F (PrOF) NMR and ¹H CPMG NMR are two fragment screening assays that have complementary advantages. Here, we sought to combine these two NMR-based assays into a new screening workflow. This combination of protein- and ligand-observed experiments allows for a time- and resource-efficient multiplexed screen of mixtures of fragments and proteins. PrOF NMR is first used to screen mixtures against two proteins. Hit mixtures for each protein are identified then deconvoluted using ¹H CPMG NMR. We demonstrate the benefit of this fragment screening method by conducting the first reported fragment screens against the bromodomains of BPTF and Plasmodium falciparum (Pf) GCN5 using 467 3D-enriched fragments. The hit rates were 6%, 5% and 4% for fragments binding BPTF, PfGCN5, and fragments binding both proteins, respectively. Select hits were characterized, revealing a broad range of affinities from low µM to mM dissociation constants. Follow-up experiments supported a low-affinity second binding site on PfGCN5. This approach can be used to bias fragment screens towards more selective hits at the onset of inhibitor development in a resource- and time-efficient manner.

Concepts and Core Principles of Fragment-Based Drug Design

In this review, a general introduction to fragment-based drug design and the underlying concepts is given. General considerations and methodologies ranging from library selection/construction over biophysical screening and evaluation methods to in-depth hit qualification and subsequent optimization strategies are discussed. These principles can be generally applied to most classes of drug targets. The examples given for fragment growing, merging, and linking strategies at the end of the review are set in the fields of enzyme-inhibitor design and macromolecule–macromolecule interaction inhibition. Building upon the foundation of fragment-based drug discovery (FBDD) and its methodologies, we also highlight a few new trends in FBDD.