Are We Opening the Door to a New Era of Medicinal Chemistry or Being Collapsed to a Chemical Singularity?

Ligand and structure-based virtual screening approaches in drug discovery: minireview

The compilation of ligand and structure-based molecular modeling methods has become an important practice in virtual screening applied to drug discovery. This systematic review addresses and ranks various virtual screening strategies to drive the selection of the optimal method for studies that have as their starting point a multi-ligand investigation and investigation based on the protein structure of a therapeutic target. This study shows examples of applications and an evaluation based on the objective and problematic of a series of virtual screening studies present in the ScienceDirect® database. The results showed that the molecular docking technique is widely used in scientific production, indicating that approaches that use protein structure as a starting point are the most promising strategy for drug discovery that relies on virtual screening-based research.

Ligand-based analysis of the antifungal potential of phytosterols and triterpenes isolated from Cryptostegia grandiflora against Candida auris FKBP12

Candida auris, a pathogenic fungus, has posed significant challenges to conventional medical treatments due to its increasing resistance to antifungal agents. Consequently, due to their promising pharmacological properties, there is a compelling interest in exploring novel bioactive compounds, such as phytosterols and triterpenes. This study aimed to conduct virtual screening utilizing computational methods, including ADMET, molecular docking, and molecular dynamics, to assess the activity and feasibility of phytosterols extracted from Cryptostegia grandiflora as potential therapeutic agents. Computational predictions suggest that compounds bearing structural similarities to Fsp3-rich molecules hold promise for inhibiting enzymes and G protein-coupled receptor (GPCR) modulators, with particular emphasis on ursolic acid, which, in its conjugated form, exhibits high oral bioavailability and metabolic stability, rendering it a compelling drug candidate. Molecular docking calculations identified ursolic acid and stigmasterol as promising ligands. While stigmasterol displayed superior affinity during molecular dynamics simulations, it exhibited instability, contrasting with ursolic acid's slightly lower affinity yet sustained stability throughout the dynamic assessments. This suggests that ursolic acid is a robust candidate for inhibiting the FKBP12 isomerase in C. auris. Moreover, further investigations could focus on experimentally validating the molecular docking predictions and evaluating the efficacy of ursolic acid as an FKBP12 isomerase inhibitor in models of C. auris infection.

Expanding chemistry through in vitro and in vivo biocatalysis

Living systems contain a vast network of metabolic reactions, providing a wealth of enzymes and cells as potential biocatalysts for chemical processes. The properties of protein and cell biocatalysts-high selectivity, the ability to control reaction sequence and operation in environmentally benign conditions-offer approaches to produce molecules at high efficiency while lowering the cost and environmental impact of industrial chemistry. Furthermore, biocatalysis offers the opportunity to generate chemical structures and functions that may be inaccessible to chemical synthesis. Here we consider developments in enzymes, biosynthetic pathways and cellular engineering that enable their use in catalysis for new chemistry and beyond.

Active and machine learning-enhanced discovery of new FGFR3 inhibitor, Rhapontin, through virtual screening of receptor structures and anti-cancer activity assessment

Introduction: This study bridges traditional remedies and modern pharmacology by exploring the synergy between natural compounds and Ceritinib in treating Non-Small Cell Lung Cancer (NSCLC), aiming to enhance efficacy and reduce toxicities. Methods: Using a combined approach of computational analysis, machine learning, and experimental procedures, we identified and analyzed PD173074, Isoquercitrin, and Rhapontin as potential inhibitors of fibroblast growth factor receptor 3 (FGFR3). Machine learning algorithms guided the initial selection, followed by Quantitative Structure-Activity Relationship (QSAR) modeling and molecular dynamics simulations to evaluate the interaction dynamics and stability of Rhapontin. Physicochemical assessments further verified its drug-like properties and specificity. Results: Our experiments demonstrate that Rhapontin, when combined with Ceritinib, significantly suppresses tumor activity in NSCLC while sparing healthy cells. The molecular simulations and physicochemical evaluations confirm Rhapontin's stability and favorable interaction with FGFR3, highlighting its potential as an effective adjunct in NSCLC therapy. Discussion: The integration of natural compounds with established cancer therapies offers a promising avenue for enhancing treatment outcomes in NSCLC. By combining the ancient wisdom of natural remedies with the precision of modern science, this study contributes to evolving cancer treatment paradigms, potentially mitigating the side effects associated with current therapies.

Structure-based virtual screening of mangiferin derivatives with antidiabetic action: a molecular docking and dynamics study and MPO-based drug-likeness approach

Extracts from Mangifera indica leaves and its main component, mangiferin, have proven antidiabetic activity. In this study, mangiferin and its natural derivatives Homomangiferin (HMF), Isomangiferin (IMF), Neomangiferin (NMF), Glucomangiferin (GMF), Mangiferin 6'-gallate (MFG), and Norathyriol (NRT) were compared regarding their action on Diabetes mellitus (DM), employing docking and molecular dynamics (MD) simulations to analyze interactions with the aldose reductase enzyme, the precursor to the conversion of glucose into sorbitol. Notably, HMF showed significant affinity to residues in the active site of the enzyme, including Trp 79, His 110, Trp 111, Phe 122, and Phe 300, with an energy of - 7.2 kcal/mol, observed in the molecular docking simulations. MD reinforced the formation of stable complexes for HMF and MFG with the aldose reductase, with interaction potential energies (IPE) in the order of - 300.812 ± 52 kJ/mol and - 304.812 ± 52 kJ/mol, respectively. The drug-likeness assessment, by multiparameter optimization (MPO), highlighted that HMF and IMF have similarities with polyphenols and glycosidic flavonoids recently patented as antidiabetics, revealing that high polarity (TPSA > 180 Å2) is a favorable property for subcutaneous administration, especially because of the gradual passive cell permeability values in biological tissues, with Papp values estimated at < 10 × 10-6 cm/s. These compounds are metabolically stable against metabolic enzymes, resulting in a low toxic incidence by metabolic activation, corroborating with a lethal dose (LD50) greater than 2000 mg/kg. In this way, HMF showed a systematic alignment between predicted pharmacokinetics and pharmacodynamics, characterizing it as the most favorable substance for inhibiting aldose reductase.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-024-03978-9.

In vitro-in silico pharmacology and chemistry of Stercularin, isolated from Sterculia diversifolia

Stercularin is a coumarin, isolated from the ethyl acetate fraction of stem bark and leaves of S. diversifolia. Pharmacologically it is active against cancer, diabetes, and inflammation etc. The molecule is further screened for in vitro pharmacological activities. In addition, a detailed description on its drug likeness and pharmacokinetic profile has been established to further explore its fate as a drug candidate. Stercularin exhibited antiglycation, immunomodulatory, and leishmanicidal activity in three different in vitro models. The IC50 values obtained in these three assays were 80.22 ± 0.46 mg/ml, 12.8 ± 1.6 μg/ml, and 8.32 ± 0.42 μg/ml, respectively. In case of drug likeness evaluation, Stercularin has acceptable physicochemical properties and compliant with major drug likeness descriptors i.e., Lipinski rule, Pfizer rule, GSK rule, and "golden triangle". Accepting Lipinski rule implies the oral drug development of Stercularin. Pharmacokinetically, Stercularin is permeable to Caco-2 and MDCK cell lines. 'Boiled-egg' plot suggest intestinal route of absorption, blood brain barrier nonpermeating, and not affected by p-glycoprotein. Stercularin has high plasma protein binding with low free fraction circulating in the plasma. Stercularin proved to be the substrate and/or inhibitor of CYP 450 system with a moderate half-life and clearance rate to allow flexible dosing regimen. Finally, slight risk of toxicity exists for Stercularin, but not being limiting factors of drug knock out. A nature isolated Stercularin possess pharmacological activities and is predicted to have acceptable pharmacokinetic profile. Further drug development and in vivo studies are desirable for optimization.

Synthesis and anxiolytic effect of europium metallic complex containing lapachol [Eu(DBM)3. LAP] in adult zebrafish through serotonergic neurotransmission: in vivo and in silico approach

Anxiety-related mental health problems are estimated at 3.6% globally, benzodiazepines (BZDs) are the class of drugs indicated for the treatment of anxiety, including lorazepam and diazepam. However, concerns have been raised about the short- and long-term risks associated with BZDs. Therefore, despite anxiolytic and antidepressant drugs, there is a need to develop more effective pharmacotherapies with fewer side effects than existing drugs. The present work reported the synthesis, anxiolytic activity, mechanism of action in Adult Zebrafish (Danio rerio) and in silico study of a europium metallic complex with Lapachol, [Eu(DBM)3. LAP]. Each animal (n = 6/group) was treated intraperitoneally (i.p.; 20 µL) with the synthesized complex (4, 20 and 40 mg/Kg) and with the vehicle (DMSO 3%; 20 µL), being submitted to the tests of locomotor activity and 96h acute toxicity. The light/dark test was also performed, and the serotonergic mechanism (5-HT) was evaluated through the antagonists of the 5-HTR1, 5-HTR2A/2C and 5-HTR3A/3B receptors. The complex was characterized using spectrometric techniques, and the anxiolytic effect of complex may be involved the neuromodulation of receptors 5-HT3A/3B, since the pre-treatment with pizotifen and cyproheptadine did not block the anxiolytic effect of [Eu(DBM)3. LAP], unlike fluoxetine had its anxiolytic effect reversed. In addition, molecular docking showed interaction between the [Eu(DBM)3. LAP] and 5HT3A receptor with binding energy -7.8 kcal/mol and the ADMET study showed that complex has low toxic risk. It is expected that the beginning of this study will allow the application of the new anxiolytic drugs, given the pharmacological potential of the lapachol complex.Communicated by Ramaswamy H. Sarma.

The search for new efficient inhibitors of SARS-COV-2 through the De novo drug design developed by artificial intelligence

The pandemic caused by Sars-CoV-2 is a viral infection that has generated one of the most significant health problems worldwide. Previous studies report the main protease (Mpro) as a potential target for this virus, as it is considered a crucial enzyme in mediating replication and viral transcription. This work presented the construction of new bioactive compounds for possible inhibition. The De novo molecular design of drugs method in the incremental construction of a ligant model within a receptor model was used, producing new structures with the help of artificial intelligence. The research algorithm and the scoring function responsible for predicting orientation and affinity in the molecular target at the time of coupling showed, as a result of the simulation, the compound with the highest bioaffinity value, Hit 998, with the energy of -17.62 kcal/mol, and synthetic viability close to 50%. While hit 1103 presented better synthetic viability (80%), its affinity energy of -10.28 kcal/mol. Both were compared with the reference linker N3, with a binding affinity of -7.5 kcal/mol. ADMET tests demonstrated that simulated compounds have a low risk of metabolic activation and do not exert effective distribution in the CNS, suggesting a pharmacokinetic mechanism based on local action, even with high topological polarity, which resulted in low oral bioavailability. In conclusion, MMGBSA, H-bonds, RMSD, SASA, and RMSF values were also obtained through molecular dynamics to verify the stability of the receptor-ligant complex within the active protein site to seek new therapeutic propositions in the fight against the pandemic.Communicated by Ramaswamy H. Sarma.

Exploring molecular interactions of potential inhibitors against the spleen tyrosine kinase implicated in autoimmune disorders via virtual screening and molecular dynamics simulations

The spleen tyrosine kinase (Syk) plays a pivotal role in immune cells' signal transduction mechanism. While fostamatinib, an FDA-approved Syk inhibitor, is currently used to treat immune thrombocytopenia, the search for improved Syk-targeted medications to treat autoimmune diseases is still underway. Herein, we screened 38,493 compounds against Syk and selected eight leads based on the docking score and ADMET properties, and performed 3× 200 ns long molecular dynamics simulations of the apo and Syk-ligand complexes. We considered R406, the active component of fostamatinib, as a control. The molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations demonstrated the lead1 (Δ G b i n d  = -30.35 kcal/mol) exhibited a similar binding free energy as the control (Δ G b i n d = -29.82 kcal/mol). The Syk stabilizing effect of lead1 was also indicated in its network features, sampling space, and residual correlation motion analysis. We further generated 100 structural analogues of lead1 using deep learning, and one of the analogues displayed a better binding free energy (Δ G b i n d = -47.58 kcal/mol) compared to the control or lead1, facilitated by more favourable van der Waals interactions and lesser binding-opposing net polar forces. This analogue may be further exploited to develop effective therapeutics against Syk-associated diseases after validation in vitro and in vivo.

Expanding Bioactive Fragment Space with the Generated Database GDB-13s

Identifying innovative fragments for drug design can help medicinal chemistry address new targets and overcome the limitations of the classical molecular series. By deconstructing molecules into ring fragments (RFs, consisting of ring atoms plus ring-adjacent atoms) and acyclic fragments (AFs, consisting of only acyclic atoms), we find that public databases of molecules (i.e., ZINC and PubChem) and natural products (i.e., COCONUT) contain mostly RFs and AFs of up to 13 atoms. We also find that many RFs and AFs are enriched in bioactive vs inactive compounds from ChEMBL. We then analyze the generated database GDB-13s, which enumerates 99 million possible molecules of up to 13 atoms, for RFs and AFs resembling ChEMBL bioactive RFs and AFs. This analysis reveals a large number of novel RFs and AFs that are structurally simple, have favorable synthetic accessibility scores, and represent opportunities for synthetic chemistry to contribute to drug innovation in the context of fragment-based drug discovery.

Oxetanes in Drug Discovery Campaigns

The oxetane ring is an emergent, underexplored motif in drug discovery that shows attractive properties such as low molecular weight, high polarity, and marked three-dimensionality. Oxetanes have garnered further interest as isosteres of carbonyl groups and as molecular tools to fine-tune physicochemical properties of drug compounds such as pKa, LogD, aqueous solubility, and metabolic clearance. This perspective highlights recent applications of oxetane motifs in drug discovery campaigns (2017-2022), with emphasis on the effect of the oxetane on medicinally relevant properties and on the building blocks used to incorporate the oxetane ring. Based on this analysis, we provide an overview of the potential benefits of appending an oxetane to a drug compound, as well as potential pitfalls, challenges, and future directions.

Overfit deep neural network for predicting drug-target interactions

Drug-target interactions (DTIs) prediction is an important step in drug discovery. As traditional biological experiments or high-throughput screening are high cost and time-consuming, many deep learning models have been developed. Overfitting must be avoided when training deep learning models. We propose a simple framework, called OverfitDTI, for DTI prediction. In OverfitDTI, a deep neural network (DNN) model is overfit to sufficiently learn the features of the chemical space of drugs and the biological space of targets. The weights of trained DNN model form an implicit representation of the nonlinear relationship between drugs and targets. Performance of OverfitDTI on three public datasets showed that the overfit DNN models fit the nonlinear relationship with high accuracy. We identified fifteen compounds that interacted with TEK, a receptor tyrosine kinase contributing to vascular homeostasis, and the predicted AT9283 and dorsomorphin were experimentally demonstrated as inhibitors of TEK in human umbilical vein endothelial cells (HUVECs).

De novo design of bioactive phenol and chromone derivatives for inhibitors of Spike glycoprotein of SARS-CoV-2 in silico

This work presents the synthesis of 12 phenol and chromone derivatives, prepared by the analogs, and the possibility of conducting an in silico study of its derivatives as a therapeutic alternative to combat the SARS-CoV-2, pathogen responsible for COVID-19 pandemic, using its S-glycoprotein as a macromolecular target. After the initial screening for the ranking of the products, it was chosen which structure presented the best energy bond with the target. As a result, derivative 4 was submitted to a molecular growth study using artificial intelligence, where 8436 initial structures were obtained that passed through the interaction filters and similarity to the active glycoprotein pocket through the MolAICal computational package. Thus, 557 Hits with active configuration were generated, which is very promising compared to the BLA reference link for inhibiting the biological target. Molecular dynamics also simulated these compounds to verify their stability within the active protein site to seek new therapeutic propositions to fight against the pandemic. The Hit 48 and 250 are the most active compounds against SARS-CoV-2. In summary, the results show that the Hit 250 would be more active than the natural compound, which could be further developed for further testing against SARS-CoV-2. The study employs the de novo approach to design new drugs, combining artificial intelligence and molecular dynamics simulations to create efficient molecular structures. This research aims to contribute to the development of effective therapeutic strategies against the pandemic.

Quantum computing for near-term applications in generative chemistry and drug discovery

In recent years, drug discovery and life sciences have been revolutionized with machine learning and artificial intelligence (AI) methods. Quantum computing is touted to be the next most significant leap in technology; one of the main early practical applications for quantum computing solutions is predicted to be in quantum chemistry simulations. Here, we review the near-term applications of quantum computing and their advantages for generative chemistry and highlight the challenges that can be addressed with noisy intermediate-scale quantum (NISQ) devices. We also discuss the possible integration of generative systems running on quantum computers into established generative AI platforms.

Today's drug discovery and the shadow of the rule of 5

INTRODUCTION

The rule of 5 developed by Lipinski et al., a landmark and prescient piece of scholarship, focused the minds of drug hunters by systematically characterizing the physical make-up of drug molecules for the first time, noting many sub-optimal compounds identified by high-throughput screening practices. Its profound influence on thinking and practices, whilst providing benefit, perhaps etched the guidelines too strongly in the minds of some drug hunters who applied the bounds too literally without understanding the implications of the underlying statistics.

AREAS COVERED

This opinion is based on recent key developments that take thinking, measurements, and standards beyond those first set out, particularly the influences of molecular weight and the understanding, measurement, and calculation of lipophilicity.

EXPERT OPINION

Techniques and technologies for physicochemical estimations set new standards. It is timely to celebrate the significance and influence of the rule of 5, whilst taking thinking to new levels with better characterizations. The shadow of the rule of 5 may be long, but it is not dark, as new measurements, predictions and principles emerge as guiding lights in the design and prioritization of higher-quality molecules redefining the meaning of beyond the rule of 5.

T52 attenuates oncogenic STAT3 signaling and suppresses osteosarcoma

BACKGROUND

T52 is a steroidal saponin extracted from the traditional Chinese herb Rohdea fargesii (Baill.), and it is reported to possess strong anti-proliferative capabilities in human pharyngeal carcinoma cell lines. However, whether T52 has anti-osteosarcoma properties, and its potential mechanism is remains unknown.

PURPOSE

To examine the outcome and underlying mechanism of T52 in osteosarcomas (OS).

METHODS/STUDY DESIGNS

The physiological roles of T52 in OS cells were examined using CCK-8, colony formation (CF), EdU staining, cell cycle/apoptosis and cell migration/invasion assays. The relevant T52 targets against OS were assessed via bioinformatics prediction, and the binding sites were analyzed by molecular docking. Western blot analysis was carried out to examine the levels of factors associated with apoptosis, cell cycle, and STAT3 signaling pathway activation.

RESULTS

T52 markedly diminished the proliferation, migration, and invasion of OS cells, and promoted G2/M arrest and apoptosis in a dose-dependent fashion (DDF) in vitro. Mechanistically, molecular docking predicted that T52 stably associated with STAT3 Src homology 2 (SH2) domain residues. Western blot revealed that T52 suppressed the STAT3 signaling pathway, as well as the expression of the downstream targets, such as, Bcl-2, Cyclin D1, and c-Myc. In addition, the anti-OS property of T52 were partially reversed by STAT3 reactivation, which confirmed that STAT3 signaling is critical for regulating the anti-OS property of T52.

CONCLUSION

We firstly demonstrated that T52 possessed strong anti-osteosarcoma property in vitro, which was brought on by the inhibition of the STAT3 signaling pathway. Our findings provided pharmacological support for treating OS with T52.

Microwave-Assisted Synthesis, Structure, and Preliminary Biological Evaluation of Novel 6-Methoxy-5,6-dihydro-5-azapurines

We herein disclose the microwave-assisted synthesis of previously unreported 6-methoxy-5,6-dihydro-5-azapurines, whose purine-like scaffold is promising for drug discovery. The method is simple, fast, and relies on easily accessible reagents such as trimethyl orthoformate, acetic acid, and aminotriazole-derived N,N'-disubstituted formamidines. The preliminary biological evaluation revealed that selected representatives of synthesized 6-methoxy-5,6-dihydro-5-azapurines dose-dependently reduce the viability of HepG2 and A549 cancer cells having little to no influence on five tested purinergic receptors.

MolFilterGAN: a progressively augmented generative adversarial network for triaging AI-designed molecules

Artificial intelligence (AI)-based molecular design methods, especially deep generative models for generating novel molecule structures, have gratified our imagination to explore unknown chemical space without relying on brute-force exploration. However, whether designed by AI or human experts, the molecules need to be accessibly synthesized and biologically evaluated, and the trial-and-error process remains a resources-intensive endeavor. Therefore, AI-based drug design methods face a major challenge of how to prioritize the molecular structures with potential for subsequent drug development. This study indicates that common filtering approaches based on traditional screening metrics fail to differentiate AI-designed molecules. To address this issue, we propose a novel molecular filtering method, MolFilterGAN, based on a progressively augmented generative adversarial network. Comparative analysis shows that MolFilterGAN outperforms conventional screening approaches based on drug-likeness or synthetic ability metrics. Retrospective analysis of AI-designed discoidin domain receptor 1 (DDR1) inhibitors shows that MolFilterGAN significantly increases the efficiency of molecular triaging. Further evaluation of MolFilterGAN on eight external ligand sets suggests that MolFilterGAN is useful in triaging or enriching bioactive compounds across a wide range of target types. These results highlighted the importance of MolFilterGAN in evaluating molecules integrally and further accelerating molecular discovery especially combined with advanced AI generative models.

Physicochemical Properties, Drug Likeness, ADMET, DFT Studies and in vitro antioxidant activity of Oxindole Derivatives

Poor pharmacokinetic and safety profiles create significant hurdles in the drug development process. This work focuses on a detailed understanding of drug discovery interplay among physicochemical, pharmacokinetic, toxicity endpoints, and antioxidant properties of oxindole derivatives. DFT compıutations were also performed at B3LYP/6-311G** level to evaluate the physicochemical properties, global reactivity features, and intramolecular interactions. The BOILED-Egg pharmacokinetic model envisaged gastrointestinal absorption, blood-brain barrier penetration, and no interaction with p-glycoprotein for compounds C1 and C2. The physicochemical evaluation revealed that C1 possesses superior drug-like properties fit for oral absorption. Both derivatives were predicted to have high plasma protein binding, efficient distribution, and inhibiting CYP 450 major isoforms but serve as substrates only for a few of them. Both molecules have mild to moderate clearance rates. Out of ten toxicity parameters, only hepatotoxicity was predicted. DFT results implied that the meta position of the -OH group made the possibility of charge transfer greater than -para positioned -OH, due to the ΔN_max (eV) values of molecules C1 and C2 being calculated at 2.596 and 2.477, respectively. Both C1 and C2 exhibited a concentration dependant DPPH and ABTS radical scavenging activity. The chemical structure-physicochemical-pharmacokinetic relationship identified the meta position as the favorite for the electron-withdrawing hydroxyl group. This provides useful insight to medicinal chemists to design 6-chlorooxindole derivatives with an acceptable drug-like and pharmacokinetic property.

Chemistry42: An AI-Driven Platform for Molecular Design and Optimization

Chemistry42 is a software platform for de novo small molecule design and optimization that integrates Artificial Intelligence (AI) techniques with computational and medicinal chemistry methodologies. Chemistry42 efficiently generates novel molecular structures with optimized properties validated in both in vitro and in vivo studies and is available through licensing or collaboration. Chemistry42 is the core component of Insilico Medicine's Pharma.ai drug discovery suite. Pharma.ai also includes PandaOmics for target discovery and multiomics data analysis, and inClinico─a data-driven multimodal forecast of a clinical trial's probability of success (PoS). In this paper, we demonstrate how the platform can be used to efficiently find novel molecular structures against DDR1 and CDK20.

Computational pharmacology and computational chemistry of 4-hydroxyisoleucine: Physicochemical, pharmacokinetic, and DFT-based approaches

Computational pharmacology and chemistry of drug-like properties along with pharmacokinetic studies have made it more amenable to decide or predict a potential drug candidate. 4-Hydroxyisoleucine is a pharmacologically active natural product with prominent antidiabetic properties. In this study, ADMETLab 2.0 was used to determine its important drug-related properties. 4-Hydroxyisoleucine is compliant with important drug-like physicochemical properties and pharma giants' drug-ability rules like Lipinski's, Pfizer, and GlaxoSmithKline (GSK) rules. Pharmacokinetically, it has been predicted to have satisfactory cell permeability. Blood-brain barrier permeation may add central nervous system (CNS) effects, while a very slight probability of being CYP2C9 substrate exists. None of the well-known toxicities were predicted in silico, being congruent with wet lab results, except for a "very slight risk" for respiratory toxicity predicted. The molecule is non ecotoxic as analyzed with common indicators such as bioconcentration and LC₅₀ for fathead minnow and daphnia magna. The toxicity parameters identified 4-hydroxyisoleucine as non-toxic to androgen receptors, PPAR-γ, mitochondrial membrane receptor, heat shock element, and p53. However, out of seven parameters, not even a single toxicophore was found. The density functional theory (DFT) study provided support to the findings obtained from drug-like property predictions. Hence, it is a very logical approach to proceed further with a detailed pharmacokinetics and drug development process for 4-hydroxyisoleucine.

Diterpene Sonderianin isolated from Croton blanchetianus exhibits acetylcholinesterase inhibitory action and anxiolytic effect in adult zebrafish (Danio rerio) by 5-HT system

Croton blanchetianus is known as 'marmeleiro preto', a very widespread shrub in Northeast Brazil. Terpenoids, steroids and phenolic compounds are among the reported secondary metabolites of the Croton genus that are a potential source of bioactive compounds. This study evaluated the anxiolytic potential of clerodine-type diterpene, sonderianin (CBWS) isolated from the stem bark of C. blanchetianus and its mechanism of action in adult zebrafish (Danio rerio) (ZFa). The anticonvulsant and anti-acetylcholinesterase effects have also been explored. ZFa (n = 6/group) were treated intraperitoneally (ip; 20 µL) with CBWS (4, 12 and 40 mg/kg) and vehicle (3% DMSO; 20 µL) and subjected to locomotor activity tests, as well as toxicity acute 96 h. CBWS was also administered for analysis in the light/dark test. The involvement of the serotonergic system (5-HT) was investigated using 5-HTR₁, 5-HTR_2A/2C and 5-HTR_3A/3B receptor antagonists. Anxiolytic doses were tested for pentylenetetrazol-induced seizure in ZFa. The inhibitory activity of the enzyme acetylcholinesterase (AChE) was measured. CBWS was not considered toxic and reduced locomotor activity. The results of the present study identified for the first time the interaction of the diterpene sonderianina in the CNS. This study provides evidence that CBWS has an anxiolytic effect mediated by serotonergic (5-HT) involvement and anti-acetylcholinesterase action. The 5-HTR₁ and 5-HTR_2A/2C receptors may be implicated in the low anticonvulsant effect in CBWS.Communicated by Ramaswamy H. Sarma.

In silico and in vitro evaluation of efflux pumps inhibition of α,β-amyrin

The use of the bacterial efflux pump mechanism to reduce the concentrations of antibiotics in the intracellular to the extracellular region is one of the main mechanisms by which bacteria acquire resistance to antibiotics. The present study aims to evaluate the antibacterial activity of the α,β-amyrin mixture isolated from Protium heptaphyllum against the multidrug-resistant strains of Escherichia coli 06 and Staphylococcus aureus 10, and to verify the inhibition of the efflux resistance mechanisms against the strains of S. aureus 1199B and K2068, carrying the NorA and MepA efflux pumps, respectively. The α,β-amyrin did not show clinically relevant direct bacterial activity. However, the α,β-amyrin when associated with the gentamicin antibiotic presented synergistic effect against the multidrug-resistant bacterial strain of S. aureus 10. In strains with efflux pumps, α,β-amyrin was able to inhibit the action of the efflux protein NorA against Ethidium Bromide. However, this inhibitory effect was not observed in the MepA efflux pump. In addition, when evaluating the effect of standard efflux pump inhibitors, clorptomazine and CCCP, α,β-amyrin showed a decrease in MIC, demonstrating the presence of the efflux mechanism through synergism. Docking studies indicate that α, β-amyrin have a higher affinity energy to MepA, and NorA than ciprofloxacin and norfloxacin. Also, α, β-amyrin bind to the same region of the binding site as these antibiotics. It was concluded that the α, β-amyrin has the potential to increase antibacterial activity with the association of antibiotics, together with the ability to be a strong candidate for an efflux pump inhibitor.Communicated by Ramaswamy H. Sarma.

Molecular Docking, Drug-Likeness Analysis, In Silico Pharmacokinetics, and Toxicity Studies of p-Nitrophenyl Hydrazones as Anti-inflammatory Compounds against COX-2, 5-LOX, and H+/K+ ATPase

Nonsteroidal anti-inflammatory drugs (NSAIDs) and coxibs are traditional medicines for the treatment of inflammation, yet associated with serious side effects. Hence, the need for discovering novel compounds with valuable clinical benefits is of great importance. In this study, 18 derivatives of p-nitrophenyl hydrazones were docked against COX-2, 5-LOX, and H+/K+ ATPase, followed by predicting their drug-likeness and absorption, distribution, metabolism, and excretion (ADME) properties. From the docking analysis, 1-(4-nitrophenyl)-2-[(3,4,5-trimethoxyphenyl)methylidene]hydrazine (3), 4-hydroxy-2-methyl-6-[(2-(4-nitrophenyl)hydraz-1-ylidene)methyl]thiochroman-1,1-dioxide (6), 4-methoxy-2-methyl-6-[(2-(4-nitrophenyl)hydraz-1-ylidene)methyl]thiochroman-1,1-dioxide (8), 2-methyl-6-[(2-(4-nitrophenyl)hydraz-1-ylidene)methyl]-4-(trifluoromethyl)thiochroman-1,1-dioxide (11), 4-[(2-(4-nitrophenyl)hydraz-1-ylidene)methyl]benzenesulfonamide (13), 4-[(2-(4-nitrophenyl)hydraz-1-ylidene)methyl]-3-(trifluoromethyl)benzenesulfonamide (14), 5-methyl-6-{4-[(2-(4-nitrophenyl)hydraz-1-ylidene)methyl]phenyl}-2,3,4,5-tetrahydropyridazin-3-ol (16), and 5-methyl-6-{4-[(2-(4-nitrophenyl)hydraz-1-ylidene)methyl]phenyl}-4,5-dihydropyridazin-3(2H)-one (17) showed promise as potent multi-target inhibitors of COX-2, 5-LOX, and H+/K+ ATPase. These compounds are less COX-2 selective than the control (celecoxib). “Drug-likeness” analysis passed Lipinski's, Egan's, Veber's, Muegge's, and Ghose's rules. The compounds also passed Pfizer and GSK rules, as well as golden triangle's rule for identification of potent and metabolically stable drugs. The pharmacokinetic profiles of the compounds were excellent, safe, and compliant with their potential anti-inflammatory activity. The results of the study can be used for future optimization of those derivatives for better molecular interactions against COX-2, 5-LOX, and H+/K+ ATPase, and inflammation-effective inhibition.

Trends in small molecule drug properties: A developability molecule assessment perspective

Developability molecule assessment is a key interfacial capability across the biopharmaceutical industry, screening and staging molecules discovered by medicinal chemists for successful chemistry manufacturing controls (CMC) development and launch. The breadth of responsibility and expertise such teams possess puts them in a unique position to understand the impact of the physicochemical properties of a drug during its initial discovery and subsequent development. However, most of the publications describing trends in physicochemical properties are written from a medicinal chemistry perspective with the aim to identify molecules with better ADMET profiles that are either lead-like or drug-like, failing to describe the impact these properties have on CMC development. To systematically uncover knowledge obtained from recent trends in physicochemical properties and the corresponding impact on CMC development, a comprehensive analysis was conducted on molecules in the drug repurposing hub dataset. The only physicochemical property that seems to have been preserved in FDA-approved oral molecules over the decades (1900-2020) is a constant H-bond donor count, highlighting the importance this property has on cell permeability and lattice energy. Pharmaceutical attrition analysis suggests that partition-distribution coefficient, H-bond acceptors, polar surface area and the fraction of sp³ carbons are properties that are associated with compound attrition. Looking at pharmaceutical attrition asynchronously with the temporal analysis of FDA-approved oral molecules highlights the opposing trends, risks and diminishing effects some of these physiochemical properties (cLogP, cLogD and Fsp3) have on describing compound attrition during the past decade. Trellising the dataset by target class suggests that certain formulation and drug delivery strategies can be anticipated or put into place based on target class of a molecule. For example, molecules binding to nuclear hormone receptors are amenable to lipid-based drug delivery systems with proven commercial success. Although the poor solubility of kinase inhibitors is a combination of hydrophobicity (due to aromaticity) required to bind to its target and high lattice energy (melting point), they are a challenging target class to formulate. The influence of drug targets on physicochemical properties and the temporal nature of these properties is highlighted when comparing molecules in the drug repurposing dataset to those developed at Amgen. An improved understanding of the impact of molecular properties on performance attributes can accelerate decisions and facilitate risk assessments during candidate selection and development.

Hizikia fusiforme functional oil (HFFO) prevents neuroinflammation and memory deficits evoked by lipopolysaccharide/aluminum trichloride in zebrafish

Background

Oxidative stress, cholinergic deficiency, and neuroinflammation are hallmarks of most neurodegenerative disorders (NDs). Lipids play an important role in brain development and proper functioning. Marine-derived lipids have shown good memory-improving potentials, especially those from fish and microalgae. The cultivated macroalga Hizikia fusiforme is healthy food and shows benefits to memory, but the study is rare on the brain healthy value of its oil. Previously, we had reported that the Hizikia fusiforme functional oil (HFFO) contains arachidonic acid, 11,14,17-eicosatrienoic acid, phytol, and other molecules displaying in vitro acetylcholinesterase inhibitory and nitroxide scavenging activity; however, the in vivo effect remains unclear. In this study, we further investigated its potential effects against lipopolysaccharides (LPS)- or aluminum trichloride (AlCl3)-induced memory deficiency in zebrafish and its drug-related properties in silica.

Methods

We established memory deficit models in zebrafish by intraperitoneal (i.p.) injection of lipopolysaccharides (LPS) (75 ng) or aluminum trichloride (AlCl3) (21 μg), and assessed their behaviors in the T-maze test. The interleukin-1β (IL-1β), tumor necrosis factor-α (TNF-α), acetylcholine (ACh), and malondialdehyde (MDA) levels were measured 24 h after the LPS/AlCl3 injection as markers of inflammation, cholinergic activity, and oxidative stress. Furthermore, the interaction of two main components, 11,14,17-eicosatrienoic acid and phytol, was investigated by molecular docking, with the important anti-inflammatory targets nuclear factor kappa B (NF-κB) and cyclooxygenase 2 (COX-2). Specifically, the absorption, distribution, metabolism, excretion, and toxicity (ADMET) and drug-likeness properties of HFFO were studied by ADMETlab.

Results

The results showed that HFFO reduced cognitive deficits in zebrafish T-maze induced by LPS/AlCl3. While the LPS/AlCl3 treatment increased MDA content, lowered ACh levels in the zebrafish brain, and elevated levels of central and peripheral proinflammatory cytokines, these effects were reversed by 100 mg/kg HFFO except for MDA. Moreover, 11,14,17-eicosatrienoic acid and phytol showed a good affinity with NF-κB, COX-2, and HFFO exhibited acceptable drug-likeness and ADMET profiles in general.

Conclusion

Collectively, this study's findings suggest HFFO as a potent neuroprotectant, potentially valuable for the prevention of memory impairment caused by cholinergic deficiency and neuroinflammation.

An efficient curriculum learning-based strategy for molecular graph learning

Computational methods have been widely applied to resolve various core issues in drug discovery, such as molecular property prediction. In recent years, a data-driven computational method-deep learning had achieved a number of impressive successes in various domains. In drug discovery, graph neural networks (GNNs) take molecular graph data as input and learn graph-level representations in non-Euclidean space. An enormous amount of well-performed GNNs have been proposed for molecular graph learning. Meanwhile, efficient use of molecular data during training process, however, has not been paid enough attention. Curriculum learning (CL) is proposed as a training strategy by rearranging training queue based on calculated samples' difficulties, yet the effectiveness of CL method has not been determined in molecular graph learning. In this study, inspired by chemical domain knowledge and task prior information, we proposed a novel CL-based training strategy to improve the training efficiency of molecular graph learning, called CurrMG. Consisting of a difficulty measurer and a training scheduler, CurrMG is designed as a plug-and-play module, which is model-independent and easy-to-use on molecular data. Extensive experiments demonstrated that molecular graph learning models could benefit from CurrMG and gain noticeable improvement on five GNN models and eight molecular property prediction tasks (overall improvement is 4.08%). We further observed CurrMG’s encouraging potential in resource-constrained molecular property prediction. These results indicate that CurrMG can be used as a reliable and efficient training strategy for molecular graph learning.

Availability: The source code is available in https://github.com/gu-yaowen/CurrMG.

Photoredox Deaminative Alkylation in DNA-Encoded Library Synthesis

Herein, we report an on-DNA photoredox-mediated deaminative alkylation method for diversifying DNA-tagged acrylamide substrate with amine-derived radicals. The radicals can be conveniently generated from sterically hindered primary amines, and the deaminative alkylation can tolerate a broad array of radical precursors. Furthermore, the methodology is applicable to Boc-protected diamines, free amino acids, and aryl halides, which bear functional groups enabling additional rounds of diversification. The method is believed to offer a high potential for constructing DNA-encoded libraries, as was demonstrated by the production of a mock library in a 2 × 3 matrix format and confirmation of DNA stability by UPLC-MS and qPCR experiments.

Discovery of novel microtubule stabilizers targeting taxane binding site by applying molecular docking, molecular dynamics simulation, and anticancer activity testing

Disruption of the dynamic equilibrium of microtubules can induce cell cycle arrest in G2/M phase and apoptosis. Hence, discovery of novel tubulin polymerization inhibitors is very necessary and an important task in drug research and development for treatment of various tumors. In this investigation, 50 compounds were screened as microtubule stabilizers targeting the taxane site by combination of molecular docking methods. Among these hits, hits 19 and 38 with novel scaffolds exhibited the highest anti-proliferative activity with IC₅₀ ranging from 9.50 to 13.81 μM in four cancer cell lines. The molecular dynamics simulations confirmed that tubulin and two hits could form stable systems. Meanwhile, the mechanism of the interactions between tubulin and two hits at simulated physiological conditions were probed. The in vitro tubulin polymerization assay revealed hits 19 and 38 were able to promote tubulin polymerization in a dose-dependent manner. Further, the immunofluorescence assay suggested that hits 19 and 38 could accelerate microtubule assembly in A549 and HeLa cells. Finally, studies on antitumor activity indicated that hits 19 and 38 induced G2/M phase cell cycle arrest and apoptosis, and inhibited cancer cell motility and migration in A549 and HeLa cells. Importantly, hit38 exhibited better anti-tubulin and anti-cancer activity than hit19 in A549 and HeLa cells. Therefore, these results suggest that hit38 represents a promising microtubule stabilizer for treating cancer and deserves further investigation.

Marine fungal metabolite butyrolactone I prevents cognitive deficits by relieving inflammation and intestinal microbiota imbalance on aluminum trichloride-injured zebrafish

Background

Mounting evidences indicate that oxidative stress, neuroinflammation, and dysregulation of gut microbiota are related to neurodegenerative disorders (NDs). Butyrolactone I (BTL-I), a marine fungal metabolite, was previously reported as an in vitro neuroprotectant and inflammation inhibitor. However, little is known regarding its in vivo effects, whereas zebrafish (Danio rerio) could be used as a convenient in vivo model of toxicology and central nervous system (CNS) diseases.

Methods

Here, we employed in vivo and in silico methods to investigate the anti-NDs potential of BTL-I. Specifically, we established a cognitive deficit model in zebrafish by intraperitoneal (i.p.) injection of aluminum trichloride (AlCl₃) (21 μg) and assessed their behaviors in the T-maze test. The proinflammatory cytokines interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α) as well as acetylcholinesterase (AChE) activity or glutathione (GSH) levels were assayed 24 h after AlCl₃ injection. The intestinal flora variation of the zebrafish was investigated by 16S rDNA high-throughput analysis. The marine fungal metabolite, butyrolactone I (BTL-I), was used to modulate zebrafish cognitive deficits evoked by AlCl₃ and evaluated about its effects on the above inflammatory, cholinergic, oxidative stress, and gut floral indicators. Furthermore, the absorption, distribution, metabolism, excretion, and toxicity (ADMET) and drug-likeness properties of BTL-I were studied by the in silico tool ADMETlab.

Results

BTL-I dose-dependently ameliorated AlCl₃-induced cognitive deficits in zebrafish. While AlCl₃ treatment elevated the levels of central and peripheral proinflammatory cytokines, increased AChE activity, and lowered GSH in the brains of zebrafish, these effects, except GSH reduction, were reversed by 25–100 mg/kg BTL-I administration. Besides, 16S rDNA high-throughput sequencing of the intestinal flora of zebrafish showed that AlCl₃ decreased Gram-positive bacteria and increased proinflammatory Gram-negative bacteria, while BTL-I contributed to maintaining the predominance of beneficial Gram-positive bacteria. Moreover, the in silico analysis indicated that BTL-I exhibits acceptable drug-likeness and ADMET profiles.

Conclusions

The present findings suggest that BTL-I is a potential therapeutic agent for preventing CNS deficits caused by inflammation, neurotoxicity, and gut flora imbalance.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12974-022-02403-3.

Synthesis of pyrimidine-containing alkaloids

This review deals with the synthesis of naturally occurring alkaloids containing partially or completely saturated pyrimidine nuclei. The interest in these compounds is associated with their structural diversity, high biological activity and toxicity. The review is divided into four parts, each of which describes a number of synthetic methodologies toward structurally different naturally occurring alkaloids containing saturated cyclic six-membered amidine, guanidine, aminal and urea (thiourea) moieties, respectively. The development of various synthetic strategies for the preparation of these compounds has remarkably increased during the past few decades. This is primarily due to the fact that some of these compounds are isolated only in limited quantities, which makes it practically impossible to study their full structural characteristics and biological activity.

ADMETlab 2.0: an integrated online platform for accurate and comprehensive predictions of ADMET properties

Because undesirable pharmacokinetics and toxicity of candidate compounds are the main reasons for the failure of drug development, it has been widely recognized that absorption, distribution, metabolism, excretion and toxicity (ADMET) should be evaluated as early as possible. In silico ADMET evaluation models have been developed as an additional tool to assist medicinal chemists in the design and optimization of leads. Here, we announced the release of ADMETlab 2.0, a completely redesigned version of the widely used AMDETlab web server for the predictions of pharmacokinetics and toxicity properties of chemicals, of which the supported ADMET-related endpoints are approximately twice the number of the endpoints in the previous version, including 17 physicochemical properties, 13 medicinal chemistry properties, 23 ADME properties, 27 toxicity endpoints and 8 toxicophore rules (751 substructures). A multi-task graph attention framework was employed to develop the robust and accurate models in ADMETlab 2.0. The batch computation module was provided in response to numerous requests from users, and the representation of the results was further optimized. The ADMETlab 2.0 server is freely available, without registration, at https://admetmesh.scbdd.com/.

Target-Based Evaluation of "Drug-Like" Properties and Ligand Efficiencies

Physicochemical descriptors commonly used to define "drug-likeness" and ligand efficiency measures are assessed for their ability to differentiate marketed drugs from compounds reported to bind to their efficacious target or targets. Using ChEMBL version 26, a data set of 643 drugs acting on 271 targets was assembled, comprising 1104 drug-target pairs having ≥100 published compounds per target. Taking into account changes in their physicochemical properties over time, drugs are analyzed according to their target class, therapy area, and route of administration. Recent drugs, approved in 2010-2020, display no overall differences in molecular weight, lipophilicity, hydrogen bonding, or polar surface area from their target comparator compounds. Drugs are differentiated from target comparators by higher potency, ligand efficiency (LE), lipophilic ligand efficiency (LLE), and lower carboaromaticity. Overall, 96% of drugs have LE or LLE values, or both, greater than the median values of their target comparator compounds.

What's in a Name? Drug Nomenclature and Medicinal Chemistry Trends using INN Publications

The World Health Organization assigns international nonproprietary names (INN), also known as common names, to compounds upon request from drug developers. Structures of INNs are publicly available and represent a source, albeit underused, to understand trends in drug research and development. Here, we explain how a common drug name is composed and analyze chemical entities from 2000 to 2021. In the analysis, we describe some changes that intertwine chemical structure, newer therapeutic targets (e.g., kinases), including a significant increase in the use of fluorine and of heterocycles, and some other evolutionary modifications, such as the progressive increase in molecular weight. Alongside these, small signs of change can be spotted, such as the rise in spirocyclic scaffolds and small rings and the emergence of unconventional structural moieties that might forecast the future to come.

DrugSpaceX: a large screenable and synthetically tractable database extending drug space

One of the most prominent topics in drug discovery is efficient exploration of the vast drug-like chemical space to find synthesizable and novel chemical structures with desired biological properties. To address this challenge, we created the DrugSpaceX (https://drugspacex.simm.ac.cn/) database based on expert-defined transformations of approved drug molecules. The current version of DrugSpaceX contains >100 million transformed chemical products for virtual screening, with outstanding characteristics in terms of structural novelty, diversity and large three-dimensional chemical space coverage. To illustrate its practical application in drug discovery, we used a case study of discoidin domain receptor 1 (DDR1), a kinase target implicated in fibrosis and other diseases, to show DrugSpaceX performing a quick search of initial hit compounds. Additionally, for ligand identification and optimization purposes, DrugSpaceX also provides several subsets for download, including a 10% diversity subset, an extended drug-like subset, a drug-like subset, a lead-like subset, and a fragment-like subset. In addition to chemical properties and transformation instructions, DrugSpaceX can locate the position of transformation, which will enable medicinal chemists to easily integrate strategy planning and protection design.

The application of isatin-based multicomponent-reactions in the quest for new bioactive and druglike molecules

Oxindole derivatives are known for their great interest in the field of Medicinal Chemistry, as they display vast biological activities. Recent efforts concerning the preparation of oxindole derivatives using isatin-based multicomponent reactions (MCRs) constitute a great advance in generating druglike libraries fast and with wide scaffold diversity. In this review, we address those recent developments, exploring the synthetic pathways and biological activities described for these compounds, namely antitumor, antibacterial, antifungal, antiparasitic, antiviral, antioxidant, anti-inflammatory and central nervous system (CNS) pathologies. To add new depth to this work, we used a well-established web-based free tool (SwissADME) to evaluate the most promising scaffolds in what concerns their druglike properties, namely by evaluating their compliance with some of the most valuable rules applied by medicinal chemists in both academia and industrial settings (Lipinski, Ghose, Veber, Egan, Muegge). The aim of this review is to endorse isatin-based MCRs as a valuable synthetic approach to attain new hit compounds bearing the oxindole privileged structure, while critically exploring these scaffolds' druglike properties.

Fsp3: A new parameter for drug-likeness

The drug-likeness of a compound is a key factor during the initial phases of drug discovery. It can be defined as the similarity between compounds and drugs. Here, we collate research related to the fraction of sp³ carbon atoms (Fsp³), including related high-throughput screening (HTS) cases, structural modifications based on Fsp³, and strategies to improve it. We also introduce new synthetic methods for spirocyclic scaffolds. It is likely that the reasonable rigidity of spirocyclic scaffolds will provide a new generation of drug candidates.

F10, a new camptothecin derivative, was identified as a new orally-bioavailable, potent antitumor agent

Topoisomerases are interesting targets for drug discovery. In the present study, we attached saturated carbon atoms to the 10-position of camptothecin and synthesized 10 new camptothecin derivatives from 10-HCPT or SN-38. The activities of new compounds were evaluated both in vitro and in vivo. The most promising compound F10, 7-ethyl-10-(2-oxo-2-(piperidin-1-yl)ethoxy)camptothecin, inhibited cancer cells growth with the IC₅₀ of 0.002, 0.003, 0.011 and 0.081 μM on Raji, HCT116, A549 and Lovo cells, respectively. Meanwhile, oral administration of F10 remarkably suppressed the HCT116-xenograft tumor growth in the nude-mice model at the dosage of 0.5, 2.0 and 8.0 mg/kg in vivo. Intraperitoneal administration of F10 can completely inhibit Raji-xenograft tumor growth in established NPG mouse model at 2.0 and 4.0 mg/kg. In addition, the minimum lethal doses of F10 and SN-38 in mice by intravenous administration were 80 and 40 mg/kg (or 0.155, 0.102 mmol/kg), respectively. The solubility of F10 reached 9.86 μg/mL in a buffer solution of pH 4.5. The oral bioavailability of F10 achieved 22.4% in mice. The molecular docking model revealed that F10 can interact with topoisomerase I-DNA complex. Our findings indicate that F10 is a new orally-oavailable antitumor agent with potent anticancer effect. Furthermore, attaching a ring hydrophobic moiety to the 10-position of camptothecin provides a favorable approach in the optimization of camptothecin.

A Practical Method for Continuous Production of sp3-Rich Compounds from (Hetero)Aryl Halides and Redox-Active Esters

A practically useful coupling reaction between aromatic halides and redox-active esters was realized by nickel catalysis through the use of a packed zinc bed column in continuous flow. Multiple reuse of the column showed a negligible decrease in efficiency, affording high space/time yields. A wide range of substrates, including a number of heteroaryl halides and polyfunctional materials were coupled in generally good yields. Longer-time and larger-scale experiments further demonstrates the robustness of the system.