Activity-based Screening Research Articles

Large-scale activity-based SCRA screening on patient serum samples: CB1 bioassay supported by machine learning

Synthetic cannabinoid receptor agonists (SCRAs) are a prominent danger to public health. Emerging SCRAs are most often highly active at the CB1 cannabinoid receptor. This high activity imposes serious health threats, illustrated by intoxications with SCRAs presenting at emergency departments (EDs). The rapid emergence of novel analogs makes the detection of these new derivatives challenging. However, there is a strong need for continuous monitoring of these compounds to adapt legislations and ensure public health. The EDs of some hospitals, located in relevant areas regarding drug abuse, serve as some kind of ‘sentinels’, allowing to keep guard on circulating, potentially highly dangerous SCRAs. An example is the ED of Guy's and St-Thomas’ Hospital in central London, which is ideally positioned to keep track of the latest changes on the illicit drug market. In the context of screening ED patient samples, the ideal assay is easy-to-perform and easily implementable. To speed up the work process and reduce the workload in the case of activity-based screening, we assessed whether machine learning could be of any help to the expert in deciding the eventual outcome of the screening assay. Following up on the success of a prior large-scale screening of serum samples for the presence of SCRA activity (Cannaert et al., Clinical Chemistry, 2019, 65, 347-349), we set out to screen a new large set (968 samples, inclusion from February 2019 to February 2020 inclusive), with the following aims: 1) assess the performance of the assay to using biological samples potentially containing newer circulating SCRAs, 2) exploration of a more structured way of manual scoring, and 3) exploration of computer-based scoring. Serum samples were subjected to activity-based SCRA screening using a cell-based bioluminescence CB1 reporter assay and to High Resolution Mass Spectrometry (HRMS)-based analysis for confirmation and identification. Both strategies were run independently and were performed blind-coded. Screening results from the bioassay (obtained through an improved scoring system by the expert) were compared with analytical (HRMS) results (considered as the ‘gold standard’). Additionally, a machine learning model was built to evaluate the possibility of computer-assisted sample scoring based on the bioassay read-out (receptor-activation profiles). Two cross-validation settings were employed to evaluate the performance of potential machine learning models and to assess the robustness of the machine learning approach. The activity-based bioassay yielded a sensitivity of 94.6% and a specificity of 98.5%. Within the sample set six different SCRAs and/or their metabolites were detected: 4F-MDMB-BINACA, 5F-MDMB-PICA, 5F-MDMB-BINACA, MDMB-CHMICA, MDMB-4en-PICA and MDMB-4en-PINACA. The sensitivity and specificity obtained by manual scoring of screening results could be matched by the machine learning model through different model settings. The performance of the activity-based screening method is in concordance with previous studies. The panel of identified SCRAs is largely distinct from the panel identified from April to December 2016, exemplifying the well-known phenomenon of market dynamics and, importantly, also underscoring the universal nature of activity-based screening. The successfully designed machine learning model could automatically discriminate positive from negative samples and enables optimal balancing of sensitivity and specificity based on model settings (pre-set threshold). Depending on the desired sensitivity/specificity and the corresponding settings applied within the model, we can conclude that machine learning is an adequate alternative for manual scoring by the expert (e.g. sensitivity and specificity of 94% at a 0.055 threshold). Automation of this scoring process results in significant time saving and reduction of the workload (Janssens et al., Clinical Chemistry, 2022, in press, https://doi.org/10.1093/clinchem/hvac027).

A Small-Molecule Inhibitor of the Anthranilyl-CoA Synthetase PqsA for the Treatment of Multidrug-Resistant Pseudomonas aeruginosa.

ABSTRACTOne of the challenges associated with the treatment of Pseudomonas aeruginosa infections is the high prevalence of multidrug resistance (MDR). Since conventional antibiotics are ineffective at treating such bacterial infections, innovative antibiotics acting upon novel targets or via mechanisms are urgently required. In this study, we identified a quorum sensing inhibitor (QSI), norharmane, that uniquely shows weak antibacterial activity but strongly inhibits pyocyanin production and biofilm formation of MDR P. aeruginosa. Biophysical experiments and molecular docking studies showed that norharmane competes with anthraniloyl-AMP for anthranilyl-CoA synthetase PqsA of P. aeruginosa at the ligand-binding pocket, which is not exploited by current inhibitors, thereby altering transcription regulatory activity. Moreover, norharmane exhibits synergy with polymyxin B. This synergism exhibits a high killing rate, low probability of resistance selection, and minimal cytotoxicity. Notably, norharmane can effectively boost polymyxin B activity against MDR P. aeruginosa-associated infections in animal models. Together, our findings provide novel insight critical to the design of improved PqsA inhibitors, and an effective combination strategy to overcome multiantibiotic bacterial resistance using conventional antibiotics and QSIs.IMPORTANCE Pseudomonas aeruginosa is a dominant hospital-acquired bacterial pathogen typically found in immunocompromised individuals. It is particularly dangerous for patients with chronic lung diseases and was identified as a serious threat for patients in the 2019 Antimicrobial Resistance Threats report (https://www.cdc.gov/drugresistance/biggest-threats.html). In this study, we used activity-based high-throughput screening to identify norharmane, a potent and selective inhibitor of P. aeruginosa PqsA, which is a well-conserved master quorum sensing (QS) regulator in multidrug resistant (MDR) P. aeruginosa. This compound competitively binds anthranilyl-CoA synthetase PqsA at the anthraniloyl-AMP binding domain, which has not been exploited by known inhibitors. Remarkably, norharmane can significantly block the production of the virulence factor, pyocyanin (87%), and biofilm formation (80%) in MDR P. aeruginosa. Furthermore, norharmane is capable of augmenting polymyxin B activity against MDR P. aeruginosa in cell cultures and animal models. Taken together, these results suggest that norharmane may be an effective adjuvant for combating multiantibiotic bacterial resistance.

RNA-templated chemical synthesis of proapoptotic L- and d-peptides

Nucleic acid-programmed reactions find application in drug screening and nucleic acid diagnosis, and offer prospects for a RNA-sensitive prodrug approach. We aim for the development of a nucleic acid-templated reaction providing nucleic acid-linked molecules that can act on intracellular protein targets. Such reactions would be useful for in situ drug synthesis and activity-based DNA-encoded library screening. In this report, we show native chemical ligation-like chemical peptidyl transfer reactions between peptide-PNA conjugates. The reaction proceeds on RNA templates. As a chemical alternative to ribosomal peptide synthesis access to both L- and d-peptides is provided. In reactions affording 9 to 14 amino acid long pro-apoptotic L- and d-peptides, we found that certain PNA sequence motifs and combinations of cell penetrating peptides (CPPs) cause surprisingly high reactivity in absence of a template. Viability measurements demonstrate that the products of templated peptidyl transfer act on HeLa cells and HEK293 cells. Of note, the presence of cysteine, which is required for NCL chemistry, can enhance the bioactivity. The study provides guidelines for the application of peptide-PNA conjugates in templated synthesis and is of interest for in situ drug synthesis and activity-based DNA-encoded library screening.

Suppression of p53 response by targeting p53-Mediator binding with a stapled peptide.

DNA-binding transcription factors (TFs) remain challenging to target with molecular probes. Many TFs function in part through interaction with Mediator, a 26-subunit complex that controls RNA polymerase II activity genome-wide. We sought to block p53 function by disrupting the p53-Mediator interaction. Through rational design and activity-based screening, we characterize a stapled peptide, with functional mimics of both p53 activation domains, that blocks p53-Mediator binding and selectively inhibits p53-dependent transcription in human cells; importantly, this "bivalent" peptide has negligible impact, genome-wide, on non-p53 target genes. Our proof-of-concept strategy circumvents the TF entirely and targets the TF-Mediator interface instead, with desired functional outcomes (i.e., selective inhibition of p53 activation). Furthermore, these results demonstrate that TF activation domains represent viable starting points for Mediator-targeting molecular probes, as an alternative to large compound libraries. Different TFs bind Mediator through different subunits, suggesting this strategy could be broadly applied to selectively alter gene expression programs.

Machine Learning to Assist in Large-Scale, Activity-Based Synthetic Cannabinoid Receptor Agonist Screening of Serum Samples.

Synthetic cannabinoid receptor agonists (SCRAs) are amongst the largest groups of new psychoactive substances (NPS). Their often high activity at the CB1 cannabinoid receptor frequently results in intoxication, imposing serious health risks. Hence, continuous monitoring of these compounds is important, but challenged by the rapid emergence of novel analogues that are missed by traditional targeted detection strategies. We addressed this need by performing an activity-based, universal screening on a large set (n = 968) of serum samples from patients presenting to the emergency department with acute recreational drug or NPS toxicity. We assessed the performance of an activity-based method in detecting newly circulating SCRAs compared with liquid chromatography coupled to high-resolution mass spectrometry. Additionally, we developed and evaluated machine learning models to reduce the screening workload by automating interpretation of the activity-based screening output. Activity-based screening delivered outstanding performance, with a sensitivity of 94.6% and a specificity of 98.5%. Furthermore, the developed machine learning models allowed accurate distinction between positive and negative patient samples in an automatic manner, closely matching the manual scoring of samples. The performance of the model depended on the predefined threshold, e.g., at a threshold of 0.055, sensitivity and specificity were both 94.0%. The activity-based bioassay is an ideal candidate for untargeted screening of novel SCRAs. The combination of this universal screening assay and a machine learning approach for automated sample scoring is a promising complement to conventional analytical methods in clinical practice.

Identification of Glycoside Transporters From the Human Gut Microbiome.

Transport is a crucial step in the metabolism of glycosides by bacteria, which is itself key for microbiota function and equilibrium. However, most transport proteins are function-unknown or only predicted, limiting our understanding of how bacteria utilize glycosides. Here, we present an activity-based screening method to identify functional glycoside transporters from microbiomes. The method is based on the co-expression in Escherichia coli of genes encoding transporters and carbohydrate-active enzymes (CAZymes) from metagenomic polysaccharide utilization loci (PULs) cloned in fosmids. To establish the proof of concept of the methodology, we used two different metagenomic libraries derived from human gut microbiota to select 18 E. coli clones whose metagenomic sequence contained at least one putative glycoside transporter and one functional CAZyme, identified by screening for various glycoside-hydrolase activities. Growth tests were performed on plant-derived glycosides, which are the target substrates of the CAZymes identified in each PUL. This led to the identification of 10 clones that are able to utilize oligosaccharides as sole carbon sources, thanks to the production of transporters from the PTS, ABC, MFS, and SusCD families. Six of the 10 hit clones contain only one transporter, providing direct experimental evidence that these transporters are functional. In the six cases where two transporters are present in the sequence of a clone, the transporters’ function can be predicted from the flanking CAZymes or from similarity with transporters characterized previously, which facilitates further functional characterization. The results expand the understanding of how glycosides are selectively metabolized by bacteria and offers a new approach to screening for glycoside-transporter specificity toward oligosaccharides with defined structures.

Discovery of Non-Cysteine-Targeting Covalent Inhibitors by Activity-Based Proteomic Screening with a Cysteine-Reactive Probe.

Covalent inhibitors of enzymes are increasingly appreciated as pharmaceutical seeds, yet discovering non-cysteine-targeting inhibitors remains challenging. Herein, we report an intriguing experience during our activity-based proteomic screening of 1601 reactive small molecules, in which we monitored the ability of library molecules to compete with a cysteine-reactive iodoacetamide probe. One epoxide molecule, F8, exhibited unexpected enhancement of the probe reactivity for glyceraldehyde-3-phosphate dehydrogenase (GAPDH), a rate-limiting glycolysis enzyme. In-depth mechanistic analysis suggests that F8 forms a covalent adduct with an aspartic acid in the active site to displace NAD+, a cofactor of the enzyme, with concomitant enhancement of the probe reaction with the catalytic cysteine. The mechanistic underpinning permitted the identification of an optimized aspartate-reactive GAPDH inhibitor. Our findings exemplify that activity-based proteomic screening with a cysteine-reactive probe can be used for discovering covalent inhibitors that react with non-cysteine residues.

Identification of polo-like kinase 1 as a therapeutic target in murine lupus.

IntroductionThe signalling cascades that contribute to lupus pathogenesis are incompletely understood. We address this by using an unbiased activity‐based kinome screen of murine lupus.MethodsAn unbiased activity‐based kinome screen (ABKS) of 196 kinases was applied to two genetically different murine lupus strains. Systemic and renal lupus were evaluated following in vivo PLK1blockade. The upstream regulators and downstream targets of PLK1 were also interrogated.ResultsMultiple signalling cascades were noted to be more active in murine lupus spleens, including PLK1. In vivo administration of a PLK1‐specific inhibitor ameliorated splenomegaly, anti‐dsDNA antibody production, proteinuria, BUN and renal pathology in MRL.lpr mice (P < 0.05). Serum IL‐6, IL‐17 and kidney injury molecule 1 (KIM‐1) were significantly decreased after PLK1 inhibition. PLK1 inhibition reduced germinal centre and marginal zone B cells in the spleen, but changes in T cells were not significant. In vitro, splenocytes were treated with anti‐mouse CD40 Ab or F(ab’)2 fragment anti‐mouse IgM. After 24‐h stimulation, IL‐6 secretion was significantly reduced upon PLK1 blockade, whereas IL‐10 production was significantly increased. The phosphorylation of mTOR was assessed in splenocyte subsets, which revealed a significant change in myeloid cells. PLK1 blockade reduced phosphorylation associated with mTOR signalling, while Aurora‐A emerged as a potential upstream regulator of PLK1.ConclusionThe Aurora‐A → PLK1 → mTOR signalling axis may be central in lupus pathogenesis, and emerges as a potential therapeutic target.

MINTIA: a metagenomic INserT integrated assembly and annotation tool.

The earth harbors trillions of bacterial species adapted to very diverse ecosystems thanks to specific metabolic function acquisition. Most of the genes responsible for these functions belong to uncultured bacteria and are still to be discovered. Functional metagenomics based on activity screening is a classical way to retrieve these genes from microbiomes. This approach is based on the insertion of large metagenomic DNA fragments into a vector and transformation of a host to express heterologous genes. Metagenomic libraries are then screened for activities of interest, and the metagenomic DNA inserts of active clones are extracted to be sequenced and analysed to identify genes that are responsible for the detected activity. Hundreds of metagenomics sequences found using this strategy have already been published in public databases. Here we present the MINTIA software package enabling biologists to easily generate and analyze large metagenomic sequence sets, retrieved after activity-based screening. It filters reads, performs assembly, removes cloning vector, annotates open reading frames and generates user friendly reports as well as files ready for submission to international sequence repositories. The software package can be downloaded from https://github.com/Bios4Biol/MINTIA.

Structural and Biochemical Studies Enlighten the Unspecific Peroxygenase from Hypoxylon sp. EC38 as an Efficient Oxidative Biocatalyst

Unspecific peroxygenases (UPO) are glycosylated fungal enzymes that can selectively oxidize C-H bonds. UPOs employ hydrogen peroxide as oxygen donor and reductant. With such an easy-to-handle co-substrate and without the need of a reducing agent, UPOs are emerging as convenient oxidative biocatalysts. Here, an unspecific peroxygenase from Hypoxylon sp. EC38 (HspUPO) was identified in an activity-based screen of six putative peroxygenase enzymes that were heterologously expressed in Pichia pastoris. The enzyme was found to tolerate selected organic solvents such as acetonitrile and acetone. HspUPO is a versatile catalyst performing various reactions, such as the oxidation of prim- and sec-alcohols, epoxidations and hydroxylations. Semi-preparative biotransformations were demonstrated for the non-enantioselective oxidation of racemic 1-phenylethanol rac -1b (TON = 13000), giving the product with 88% isolated yield, and the oxidation of indole 6a to give indigo 6b (TON = 2800) with 98% isolated yield. HspUPO features a compact and rigid three-dimensional conformation that wraps around the heme and defines a funnel-shaped tunnel that leads to the heme iron from the protein surface. The tunnel extends along a distance of about 12 Å with a fairly constant diameter in its innermost segment. Its surface comprises both hydrophobic and hydrophilic groups for dealing with small-to-medium size substrates of variable polarities. The structural investigation of several protein-ligand complexes revealed that the active site of HspUPO is accessible to molecules of varying bulkiness and polarity with minimal or no conformational changes, explaining the relatively broad substrate scope of the enzyme. With its convenient expression system, robust operational properties, relatively small size, well-defined structural features, and diverse reaction scope, HspUPO is an exploitable candidate for peroxygenase-based biocatalysis.

A global survey reveals a divergent extradiol dioxygenase clade as a widespread complementary contributor to the biodegradation of mono- and polycyclic aromatic hydrocarbons

Extradiol dioxygenation is a key reaction in the microbial aerobic degradation of mono- and polycyclic aromatic hydrocarbon catecholic derivatives. It has been reported that many bacterial enzymes exhibiting such converging functions act on a wide range of catecholic substrates. The present study reports a new subfamily of extradiol dioxygenases (EXDOs) with broad substrate specificity, the HrbC EXDOs. The new clade belongs to the XII cluster within family 2 of the vicinal oxygen chelate superfamily (EXDO-VC2), which is typically characterized by a preference for bicyclic substrates. Coding hrbC orthologs were isolated by activity-based screening of fosmid metagenomic libraries from large DNA fragments derived from heavily PAH-contaminated soils. They occurred as solitary genes within conserved sequences encoding enzymes for amino acid metabolism and were stably maintained in the chromosomes of the Betaproteobacteria lineages harboring them. Analysis of contaminated aquifers revealed coexpression of hrbC as a polycistronic mRNA component. The predicted open reading frames were verified by cloning and heterologous expression, confirming the expected molecular mass and meta-cleavage activity of the recombinant enzymes. Evolutionary analysis of the HrbC protein sequences grouped them into a discrete cluster of 1,2-dihydroxynaphthalene dioxygenases represented by a cultured PAH degrader, Rugosibacter aromaticivorans strain Ca6. The ecological importance and relevance of the new EXDO genes were confirmed by PCR-based mapping in different biogeographical localities contaminated with a variety of mono- and polycyclic aromatic compounds. The cosmopolitan distribution of hrbC in PAH-contaminated aquifers supports our hypothesis about its auxiliary role in the degradation of toxic catecholic intermediates, contributing to the composite EXDO catabolic capacity of the world's microbiomes.

Screening of Neutrophil Activating Factors from a Metagenome Library of Sponge-Associated Bacteria.

Marine sponge-associated bacteria are known as bio-active compound produce. We have constructed metagenome libraries of the bacteria and developed a metagenomic screening approach. Activity-based screening successfully identified novel genes and novel enzymes; however, the efficiency was only in 1 out of 104 clones. Therefore, in this study, we thought that bioinformatics could help to reduce screening efforts, and combined activity-based screening with database search. Neutrophils play an important role for the immune system to recognize excreted bacterial by-products as chemotactic factors and are recruited to infection sites to kill pathogens via phagocytosis. These excreted by-products are considered critical triggers that engage the immune system to mount a defense against infection, and identifying these factors may guide developments in medicine and diagnostics. We focused on genes encoding amino acid ligase and peptide synthetase and selected from an in-house sponge metagenome database. Cell-free culture medium of each was used in a neutrophil chemiluminescence assay in luminol reaction. The clone showing maximum activity had a genomic sequence expected to produce a molecule like a phospho-N-acetylmuramyl pentapeptide by the metagenome fragment analysis.

Physical and Chemical methods of extraction of Bioactive Molecules from Lepidium sativum Linn. and Antioxidant Activity-based screening and selection of extracts-Probable Phytochemical, Chromatography and mass spectroscopy analysis-based correlates

Identification and isolation of active principles from Lepidium sativum L. garden cress seeds and their chemical/biological characterization would aid in drug development (templates for synthesizing derivatives or as a value-added product). Initially, this study dealt with the phytochemical, qualitative and quantitative analysis for phenolic and flavonoid compounds. Subsequently, different physical and chemical extraction techniques -Simple Crude extraction (CRU), Ultra Sonication-Assisted Extraction (UAE), Microwave-Assisted Extraction (MAE) and classical Soxhlet extraction were adopted to select the best Lepidium sativum L. seed extract based on their activity in certain classical, in vitro antioxidant assay systems. The selected best extract was further analyzed for characterization using UPLC, GC-MS. CRU MeOH extracts showed a higher Total phenolic content of 4464.1±349.7mg GAE/100g. The UAE method showed a higher total flavonoid content of 1520.6±182.2mg QUE/100g. CRU-MeOH showed good antioxidant activity based on the free radical scavenging DPPH assay (IC50: 50.61µg/mL). A 100µg/mL concentration of CRU-MeOH was found to be 217.82±12.82 FRAP value. At 400 µg/mL, the NO scavenging assay was reported to be 62.11±4.84%. The present study indicates that extracts from the polar solvents shows better antioxidant scavenging potential than that of the non-polar extracts. Based on the relatively superior performance of the CRU-MeOH extract, UPLC-PDA data was generated. The validity of our chromatography conditions was shown by the presence of quercetin at a retention time 8.555 (validated by our internal standard), apart from the presence of this important bioactive molecule in our extract. As another strand of evidence for the presence of important bioactive molecules, p-coumaric acid, and ferulic acid were also present in our extracts, following correlation of their UPLC-PDA data with published findings. Also, GC-MS analysis of the CRU MeOH extract showed that 24 compounds (8 major and 16 minor peaks). One of the compounds detected (cis-vaccenic acid) is in consonance with published data. The presence of bioactive components, with known antioxidant and cell death potential, validates our experimental flow for the development and/or refinement of crude extract-based drugs. However, the variability perforce warrants an inter-laboratory harmonization of protocols for making meaningful comparisons.

A di-Copper Peptidyl Complex Mimics the Activity of Catalase, a Key Antioxidant Metalloenzyme.

Catalases (CAT) are antioxidant metalloenzymes necessary for life in oxygen-metabolizing cells to regulate H2O2 concentration by accelerating its dismutation. Many physiopathological situations are associated with oxidative stress resulting from H2O2 overproduction, during which antioxidant defenses are overwhelmed. We have used a combinatorial approach associated with an activity-based screening to discover a first peptidyl di-copper complex mimicking CAT. The complex was studied in detail and characterized for its CAT activity both in solutions and in cells using different analytical methods. The complex exhibited CAT activity in solutions and, more interestingly, on HyPer HeLa cells that possess a genetically encoded ratiometric fluorescent sensors of H2O2. These results highlight the efficiency of a combinatorial approach for the discovery of peptidyl complexes that exhibit catalytic activity.

Sugar phosphate activation of the stress sensor eIF2B

The multi-subunit translation initiation factor eIF2B is a control node for protein synthesis. eIF2B activity is canonically modulated through stress-responsive phosphorylation of its substrate eIF2. The eIF2B regulatory subcomplex is evolutionarily related to sugar-metabolizing enzymes, but the biological relevance of this relationship was unknown. To identify natural ligands that might regulate eIF2B, we conduct unbiased binding- and activity-based screens followed by structural studies. We find that sugar phosphates occupy the ancestral catalytic site in the eIF2Bα subunit, promote eIF2B holoenzyme formation and enhance enzymatic activity towards eIF2. A mutant in the eIF2Bα ligand pocket that causes Vanishing White Matter disease fails to engage and is not stimulated by sugar phosphates. These data underscore the importance of allosteric metabolite modulation for proper eIF2B function. We propose that eIF2B evolved to couple nutrient status via sugar phosphate sensing with the rate of protein synthesis, one of the most energetically costly cellular processes.

Biosynthetic Strategies for Macrocyclic Peptides.

Macrocyclic peptides are predominantly peptide structures bearing one or more rings and spanning multiple amino acid residues. Macrocyclization has become a common approach for improving the pharmacological properties and bioactivity of peptides. A variety of ribosomal-derived and non-ribosomal synthesized cyclization approaches have been established. The biosynthesis of backbone macrocyclic peptides using seven new emerging methodologies will be discussed with regard to the features and strengths of each platform rather than medicinal chemistry tools. The mRNA display variant, known as the random nonstandard peptide integrated discovery (RaPID) platform, utilizes flexible in vitro translation (FIT) to access macrocyclic peptides containing nonproteinogenic amino acids (NAAs). As a new discovery approach, the ribosomally synthesized and post-translationally modified peptides (RiPPs) method involves the combination of ribosomal synthesis and the phage screening platform together with macrocyclization chemistries to generate libraries of macrocyclic peptides. Meanwhile, the split-intein circular ligation of peptides and proteins (SICLOPPS) approach relies on the in vivo production of macrocyclic peptides. In vitro and in vivo peptide library screening is discussed as an advanced strategy for cyclic peptide selection. Specifically, biosynthetic bicyclic peptides are highlighted as versatile and attractive modalities. Bicyclic peptides represent another type of promising therapeutics that allow for building blocks with a heterotrimeric conjugate to address intractable challenges and enable multimer complexes via linkers. Additionally, we discuss the cell-free chemoenzymatic synthesis of macrocyclic peptides with a non-ribosomal catalase known as the non-ribosomal synthetase (NRPS) and chemo-enzymatic approach, with recombinant thioesterase (TE) domains. Novel insights into the use of peptide library tools, activity-based two-hybrid screening, structure diversification, inclusion of NAAs, combinatorial libraries, expanding the toolbox for macrocyclic peptides, bicyclic peptides, chemoenzymatic strategies, and future perspectives are presented. This review highlights the broad spectrum of strategy classes, novel platforms, structure diversity, chemical space, and functionalities of macrocyclic peptides enabled by emerging biosynthetic platforms to achieve bioactivity and for therapeutic purposes.

The microbiome-shaping roles of bacteriocins.

The microbiomes on human body surfaces affect health in multiple ways. They include not only commensal or mutualistic bacteria but also potentially pathogenic bacteria, which can enter sterile tissues to cause invasive infection. Many commensal bacteria produce small antibacterial molecules termed bacteriocins that have the capacity to eliminate specific colonizing pathogens; as such, bacteriocins have attracted increased attention as potential microbiome-editing tools. Metagenome-based and activity-based screening approaches have strongly expanded our knowledge of the abundance and diversity of bacteriocin biosynthetic gene clusters and the properties of a continuously growing list of bacteriocin classes. The dynamic acquisition, diversification or loss of bacteriocin genes can shape the fitness of a bacterial strain that is in competition with bacteriocin-susceptible bacteria. However, a bacteriocin can only provide a competitive advantage if its fitness benefit exceeds the metabolic cost of production, if it spares crucial mutualistic partner strains and if major competitors cannot develop resistance. In contrast to most currently available antibiotics, many bacteriocins have only narrow activity ranges and could be attractive agents for precision therapy and prevention of infections. A common scientific strategy involving multiple disciplines is needed to uncover the immense potential of microbiome-shaping bacteriocins.

A Blueprint for High Affinity SARS-CoV-2 Mpro Inhibitors from Activity-Based Compound Library Screening Guided by Analysis of Protein Dynamics.

The SARS-CoV-2 coronavirus outbreak continues to spread at a rapid rate worldwide. The main protease (Mpro) is an attractive target for anti-COVID-19 agents. Unexpected difficulties have been encountered in the design of specific inhibitors. Here, by analyzing an ensemble of ∼30 000 SARS-CoV-2 Mpro conformations from crystallographic studies and molecular simulations, we show that small structural variations in the binding site dramatically impact ligand binding properties. Hence, traditional druggability indices fail to adequately discriminate between highly and poorly druggable conformations of the binding site. By performing ∼200 virtual screenings of compound libraries on selected protein structures, we redefine the protein’s druggability as the consensus chemical space arising from the multiple conformations of the binding site formed upon ligand binding. This procedure revealed a unique SARS-CoV-2 Mpro blueprint that led to a definition of a specific structure-based pharmacophore. The latter explains the poor transferability of potent SARS-CoV Mpro inhibitors to SARS-CoV-2 Mpro, despite the identical sequences of the active sites. Importantly, application of the pharmacophore predicted novel high affinity inhibitors of SARS-CoV-2 Mpro, that were validated by in vitro assays performed here and by a newly solved X-ray crystal structure. These results provide a strong basis for effective rational drug design campaigns against SARS-CoV-2 Mpro and a new computational approach to screen protein targets with malleable binding sites.

The Use of Acoustic Mist Ionization Mass Spectrometry for High-Throughput Screening.

It is clear from the analysis of the distribution of approved drug targets that enzymes continue to be a major target class for the pharmaceutical industry. The application of high-throughput screens designed to monitor the activity of these enzyme targets, and the ability of test compounds to modulate this activity, is still the predominant hit finding approach in the industry. The widespread use of enzyme activity-based screens has led to the development of several useful guidelines for the development and validation of robust and reliable assays. Key learnings for the development, validation, and implementation of acoustic mist ionization mass spectrometry for high-throughput enzyme assays are described.

A roadmap for metagenomic enzyme discovery.

Covering: up to 2021Metagenomics has yielded massive amounts of sequencing data offering a glimpse into the biosynthetic potential of the uncultivated microbial majority. While genome-resolved information about microbial communities from nearly every environment on earth is now available, the ability to accurately predict biocatalytic functions directly from sequencing data remains challenging. Compared to primary metabolic pathways, enzymes involved in secondary metabolism often catalyze specialized reactions with diverse substrates, making these pathways rich resources for the discovery of new enzymology. To date, functional insights gained from studies on environmental DNA (eDNA) have largely relied on PCR- or activity-based screening of eDNA fragments cloned in fosmid or cosmid libraries. As an alternative, shotgun metagenomics holds underexplored potential for the discovery of new enzymes directly from eDNA by avoiding common biases introduced through PCR- or activity-guided functional metagenomics workflows. However, inferring new enzyme functions directly from eDNA is similar to searching for a ‘needle in a haystack’ without direct links between genotype and phenotype. The goal of this review is to provide a roadmap to navigate shotgun metagenomic sequencing data and identify new candidate biosynthetic enzymes. We cover both computational and experimental strategies to mine metagenomes and explore protein sequence space with a spotlight on natural product biosynthesis. Specifically, we compare in silico methods for enzyme discovery including phylogenetics, sequence similarity networks, genomic context, 3D structure-based approaches, and machine learning techniques. We also discuss various experimental strategies to test computational predictions including heterologous expression and screening. Finally, we provide an outlook for future directions in the field with an emphasis on meta-omics, single-cell genomics, cell-free expression systems, and sequence-independent methods.