Screening Of Library Research Articles

CovalentInDB 2.0: an updated comprehensive database for structure-based and ligand-based covalent inhibitor design and screening.

The rational design of targeted covalent inhibitors (TCIs) has emerged as a powerful strategy in drug discovery, known for its ability to achieve strong binding affinity and prolonged target engagement. However, the development of covalent drugs is often challenged by the need to optimize both covalent warhead and non-covalent interactions, alongside the limitations of existing compound libraries. To address these challenges, we present CovalentInDB 2.0, an updated online database designed to support covalent drug discovery. This updated version includes 8303 inhibitors and 368 targets, supplemented by 3445 newly added cocrystal structures, providing detailed analyses of non-covalent interactions. Furthermore, we have employed an AI-based model to profile the ligandability of 144 864 cysteines across the human proteome. CovalentInDB 2.0 also features the largest covalent virtual screening library with 2 030 192 commercially available compounds and a natural product library with 105 901 molecules, crucial for covalent drug screening and discovery. To enhance the utility of these compounds, we performed structural similarity analysis and drug-likeness predictions. Additionally, a new user data upload feature enables efficient data contribution and continuous updates. CovalentInDB 2.0 is freely accessible at http://cadd.zju.edu.cn/cidb/.

Selective targeting of oncogenic hotspot mutations of the HER2 extracellular domain.

Oncogenic mutations in the extracellular domain (ECD) of cell-surface receptors could serve as tumor-specific antigens that are accessible to antibody therapeutics. Such mutations have been identified in receptor tyrosine kinases including HER2. However, it is challenging to selectively target a point mutant, while sparing the wild-type protein. Here we developed antibodies selective to HER2 S310F and S310Y, the two most common oncogenic mutations in the HER2 ECD, via combinatorial library screening and structure-guided design. Cryogenic-electron microscopy structures of the HER2 S310F homodimer and an antibody bound to HER2 S310F revealed that these antibodies recognize the mutations in a manner that mimics the dimerization arm of HER2 and thus inhibit HER2 dimerization. These antibodies as T cell engagers selectively killed a HER2 S310F-driven cancer cell line in vitro, and in vivo as a xenograft. These results validate HER2 ECD mutations as actionable therapeutic targets and offer promising candidates toward clinical development.

CRISPR-GRIT: Guide RNAs with Integrated Repair Templates Enable Precise Multiplexed Genome Editing in the Diploid Fungal Pathogen Candida albicans.

Candida albicans, an opportunistic fungal pathogen, causes severe infections in immunocompromised individuals. Limited classes and overuse of current antifungals have led to the rapid emergence of antifungal resistance. Thus, there is an urgent need to understand fungal pathogen genetics to develop new antifungal strategies. Genetic manipulation of C. albicans is encumbered by its diploid chromosomes requiring editing both alleles to elucidate gene function. Although the recent development of CRISPR-Cas systems has facilitated genome editing in C. albicans, large-scale and multiplexed functional genomic studies are still hindered by the necessity of cotransforming repair templates for homozygous knockouts. Here, we present CRISPR-GRIT (Guide RNAs with Integrated Repair Templates), a repair template-integrated guide RNA design for expedited gene knockouts and multiplexed gene editing in C. albicans. We envision that this method can be used for high-throughput library screens and identification of synthetic lethal pairs in both C. albicans and other diploid organisms with strong homologous recombination machinery.

WDR20 prevents hepatocellular carcinoma senescence by orchestrating the simultaneous USP12/46-mediated deubiquitination of c-Myc

The dysfunction of the ubiquitin-proteasome system (UPS) facilitates the malignant progression of hepatocellular carcinoma (HCC). While targeting the UPS for HCC therapy has been proposed, identifying effective targets has been challenging. In this study, we conducted a focused screen of siRNA libraries targeting UPS-related WD40 repeat (WDR) proteins and found that silencing WDR20, a deubiquitinating enzyme activating factor, selectively inhibited the proliferation of HCC cells without affecting normal hepatocytes. Moreover, the downregulation of WDR20 expression induced HCC cellular senescence and suppressed tumor progression in xenograft, sleeping beauty transposon/transposase, and hydrodynamic tail vein injection-induced HCC models, and Alb-Cre+/MYC+ HCC transgenic mouse models. Mechanistically, we found that WDR20 silencing disturbed the protein stability of c-Myc, orchestrating the simultaneous USP12/46-mediated deubiquitination of c-Myc, thereby promoting the transcriptional activation of CDKN1A. Further investigation revealed a positive coexpression of WDR20 and c-Myc in a tissue microarray with 88 HCC clinical samples. By employing three patient-derived organoids from individuals with HCC, we have validated the decrease in c-Myc expression and the significant induction of senescence and growth inhibition following silencing of WDR20. This study not only uncovers the biological function of WDR20 and elucidates the molecular mechanism underlying its negative regulation of HCC cellular senescence but also highlight the potential of WDR20 as a promising target for HCC therapy.

Angelic acid triggers ferroptosis in colorectal cancer cells via targeting and impairing NRF2 protein stability.

Ferroptosis is a unique programmed cell death driven by iron-dependent phospholipid peroxidation. Tumor cells that escape from the conventional therapies appear more sensitive to ferroptosis. Therefore, it is extremely urgent to find safe and efficient active ingredients that induce ferroptosis in tumor cells. Herein, we identified that angelic acid, as a potent anti-tumor active ingredient in Angelica sinensis, profoundly sensitizes CRC cells to ferroptosis via a natural compound library screen. We revealed that angelic acid treatment is sufficient to predispose CRC cells to ferroptosis phenotype, evidenced by malondialdehyde (MDA) accumulation, lipid peroxidation, and upregulation of ferroptosis-associated markers CHAC1 and PTGS2, which is abolished by ferroptosis inhibitor Fer-1. Moreover, the results of network pharmacology showed that NRF2 is critical for angelic acid-mediated CRC cell ferroptosis. Mechanistically, angelic acid exerted its ferroptosis induction via directly binding and facilitating the degradation of NRF2. In addition, the syngeneic mouse models revealed that angelic acid boosts CRC cell sensitivity to ferroptosis inducer sulfasalazine with essentially no toxicity in vivo. Collectively, our findings highlighted a previously unrecognized anti-tumor mechanism of angelic acid and represented an appealing therapeutic strategy for CRC treatment.

Design and investigation of novel iridoid-based peptide conjugates for targeting EGFR and its mutants L858R and T790M/L858R/C797S: an in silico study.

In this work, we designed novel peptide conjugates with plant-based iridoid and lichen-derived depside derivatives to target the wild-type EGFR (WT) and its mutants, L858R and T790M/L858R/C797S triple mutant. These mutations are often expressed in multiple cancers, particularly lung cancer. Specifically, the iridoids included 7-deoxyloganetic acid (7-DGA) and loganic acid (LG), while the depside derivative was sekikaic acid (SK). These compounds are known for their innate anticancer properties and were conjugated with two separate peptide sequences KLPGWSG (K) and YSIPKSS (Y). These sequences have been shown to target EGFR in previous phage display library screening, although the mechanism is unknown. Thus, we created the di-conjugates for dual targeting and investigated their interactions of the di-conjugates and that of the neat peptides with the kinase domain of EGFR (WT) and the two mutants using molecular docking, molecular dynamics (MD) simulations, and MM-GBSA analysis. Docking studies revealed that the (7-DGA)2-K showed the highest binding affinity at - 9.3kcal/mol with the L858R mutant, while (LG)2-Y displayed the highest binding affinity at - 9.0kcal/mol for the triple mutant receptor. Our results indicated that several of the conjugates interacted with crucial residues of the kinase domain, including ASP855 and THR854 (activation loop), MET793 and PRO794 (hinge region), ARG841 (catalytic loop), and LYS728 and LEU718 of the glycine-rich P-loop. Interestingly, strong hydrophobic interactions were also observed with the C-terminal tail residues, such as PHE997 and ALA1000 as well as with ARG999 for the YSIPKSS peptide and most of the conjugates. The hydroxyl group of the cyclopentane ring and the oxygen of the pyran ring of the (7-DGA)2-peptide conjugates contributed to binding particularly in the hinge region, while the peptide components formed an extended structure that bound well into the C-lobe. The (SK)2-Y di-conjugate and KLPGWSG peptide formed hydrogen bonds with the SER797 residue of the triple mutant. Overall, our results show that the (7-DGA)2-K, di-conjugate, the (7-DGA)2-Y di-conjugate, and the neat YSIPKSS demonstrated strong and stable binding with the L858R mutant and the highly resistant triple mutant EGFR, respectively. The novel designed conjugates demonstrate potential for further optimization for laboratory studies aimed at developing new therapeutics for targeting specific EGFR mutant expressing cells.

High-resolution acoustic ejection mass spectrometry for high-throughput library screening

An approach is described for high-throughput quality assessment of drug candidate libraries using high-resolution acoustic ejection mass spectrometry (AEMS). Sample introduction from 1536-well plates is demonstrated for this application using 2.5 nL acoustically dispensed sample droplets into an Open Port Interface (OPI) with pneumatically assisted electrospray ionization at a rate of one second per sample. Both positive and negative ionization are shown to be essential to extend the compound coverage of this protease inhibitor-focused library. Specialized software for efficiently interpreting this data in 1536-well format is presented. A new high-throughput method for quantifying the concentration of the components (HTQuant) is proposed that neither requires adding an internal standard to each well nor further encumbers the high-throughput workflow. This approach for quantitation requires highly reproducible peak areas, which is shown to be consistent within 4.4 % CV for a 1536-well plate analysis. An approach for troubleshooting the workflow based on the background ion current signal is also presented. The AEMS data is compared to the industry standard LC/PDA/ELSD/MS approach and shows similar coverage but at 180-fold greater throughput. Despite the same ionization process, both methods confirmed the presence of a small percentage of compounds in wells that the other did not. The data for this relatively small, focused library is compared to a larger, more chemically diverse library to indicate that this approach can be more generally applied beyond this single case study. This capability is particularly timely considering the growing implementation of artificial intelligence strategies that require the input of large amounts of high-quality data to formulate predictions relevant to the drug discovery process. The molecular structures of the 872-compound library analyzed here are included to begin the process of correlating molecular structures with ionization efficiency and other parameters as an initial step in this direction.

Lymphoma and Leukemia Cell Vulnerabilities and Resistance Identified by Compound Library Screens.

Response to anticancer agents is often restricted to subsets of patients. Recognition of factors underlying this heterogeneity and identification of biomarkers associated with response to drugs would greatly improve the efficacy of drug treatment. Platforms that can comprehensively map cellular response to compounds in high-throughput provide a unique tool to identify associated biomarkers and provide hypotheses for mechanisms underlying variable response. Such screens can be performed on cell lines and short-term cultures of primary cells to take advantage of the respective models' strength, which include, e.g., the ability to silence genes or introduce somatic mutations to cell lines. Cohorts of patient samples represent the natural diversity of cancers, including rarer mutations and combinatorial patterns of mutations that are often absent from existing cell lines. We here summarize a simple and scalable method for the measurement of viability after drug exposure based on ATP measurements as a surrogate for viability, which we use to measure and understand drug response in cell lines and primary cells.

MATE transporter OsMATE2 mediates root growth, grain size and weight by interacting with Mn-SOD and PABP in rice

Multidrug and toxic compound extrusion proteins (MATE) can transport small organic molecules in and out of cells and participate in detoxification, nutrient absorption, disease resistance and plant development processes. These compounds are widely distributed in plants. However, the mechanism by which MATE affects grain development remains elusive. In this study, we studied a MATE transporter, OsMATE2, which localized on the membrane. The CRISPR-Cas9 (CR) knockout line of OsMATE2 presented obvious decreases in grain weight. In addition, root development was also affected. Two proteins that interact with OsMATE2, namely, manganese-superoxide dismutase (Mn-SOD) and poly(A)-binding protein (PABP), were identified from a screening of yeast library. The results were validated through yeast two-hybrid and bimolecular fluorescence complementation experiments. The CRISPR-Cas9 (CR) knockout lines of Mn-SOD and PABP presented increased grain size and weight. Our findings demonstrated that OsMATE2 interacts with Mn-SOD and PABP to regulate grain development in rice.

Enhancing Cellular Homeostasis: Targeted Botanical Compounds Boost Cellular Health Functions in Normal and Premature Aging Fibroblasts.

The human skin, the body's largest organ, undergoes continuous renewal but is significantly impacted by aging, which impairs its function and leads to visible changes. This study aimed to identify botanical compounds that mimic the anti-aging effects of baricitinib, a known JAK1/2 inhibitor. Through in silico screening of a botanical compound library, 14 potential candidates were identified, and 7 were further analyzed for their effects on cellular aging. The compounds were tested on both normal aged fibroblasts and premature aging fibroblasts derived from patients with Hutchinson-Gilford Progeria Syndrome (HGPS). Results showed that these botanical compounds effectively inhibited the JAK/STAT pathway, reduced the levels of phosphorylated STAT1 and STAT3, and ameliorated phenotypic changes associated with cellular aging. Treatments improved cell proliferation, reduced senescence markers, and enhanced autophagy without inducing cytotoxicity. Compounds, such as Resveratrol, Bisdemethoxycurcumin, Pinosylvin, Methyl P-Hydroxycinnamate, cis-Pterostilbene, and (+)-Gallocatechin, demonstrated significant improvements in both control and HGPS fibroblasts. These findings suggest that these botanical compounds have the potential to mitigate age-related cellular alterations, offering promising strategies for anti-aging therapies, particularly for skin health. Further in vivo studies are warranted to validate these results and explore their therapeutic applications.

Identification of Novel PPARγ Partial Agonists Based on Virtual Screening Strategy: In Silico and In Vitro Experimental Validation.

Thiazolidinediones (TZDs) including rosiglitazone and pioglitazone function as peroxisome proliferator-activated receptor gamma (PPARγ) full agonists, which have been known as a class to be among the most effective drugs for the treatment of type 2 diabetes mellitus (T2DM). However, side effects of TZDs such as fluid retention and weight gain are associated with their full agonistic activities toward PPARγ induced by the AF-2 helix-involved "locked" mechanism. Thereby, this study aimed to obtain novel PPARγ partial agonists without direct interaction with the AF-2 helix. Through performing virtual screening of the Targetmol L6000 Natural Product Library and utilizing molecular dynamics (MD) simulation, as well as molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) analysis, four compounds including tubuloside b, podophyllotoxone, endomorphin 1 and paliperidone were identified as potential PPARγ partial agonists. An in vitro TR-FRET competitive binding assay showed podophyllotoxone displayed the optimal binding affinity toward PPARγ among the screened compounds, exhibiting IC50 and ki values of 27.43 µM and 9.86 µM, respectively. Further cell-based transcription assays were conducted and demonstrated podophyllotoxone's weak agonistic activity against PPARγ compared to that of the PPARγ full agonist rosiglitazone. These results collectively demonstrated that podophyllotoxone could serve as a PPARγ partial agonist and might provide a novel candidate for the treatment of various diseases such as T2DM.

Exploring Natural Compounds Targeting the Bacterial SHV Protein to Combat Antibiotic Resistance: A Biocomputational Study

Background: Antibiotic-resistant (AR) bacteria are rapidly spreading worldwide, posing a serious threat to antibiotic efficacy. Bacterial infections have emerged as a persistent threat following decades of antibiotic use. Sulfhydryl variable (SHV) is a well-known bacterial enzyme linked to AR. SHV has a high degree of genetic diversity, resulting in the existence of numerous distinct variants. Methods: The PyRx AutoDock VINA was used to conduct in-silico screening of a natural compound library to assess their interaction with the SHV-1 protein. SwissADME web tools were used to predict the physicochemical, drug-likeness, and ADMET properties of the selected compounds.Result: The compounds PSCdb00708, PSCdb00149, PSCdb00698, and PSCdb00175 bind strongly to the SHV-1 protein and interact strongly with the SHV-1 active site residues, as well as having several amino acid residue interactions in common with avibactam. These compounds exhibited higher binding affinity values than avibactam. Furthermore, these compounds demonstrated no violation of drug-likeness.Conclusion: The compounds PSCdb00708, PSCdb00149, PSCdb00698, and PSCdb00175 can be employed as SHV-1 inhibitors in the management of AR. However, experimental validation is required to optimize them as SHV-1 inhibitors.Keywords: Antibiotic-resistant; Antibiotic; Virtual screening; AutoDock; SHV-1 protein

Metagenomic analysis during capecitabine therapy reveals microbial chemoprotective mechanisms and predicts drug toxicity in colorectal cancer patients.

Unpredictable chemotherapy side effects are a major barrier to successful treatment. Cell culture and mouse experiments indicate that the gut microbiota is influenced by and influences anti-cancer drugs. However, metagenomic data from patients paired to careful side effect monitoring remains limited. Herein, we focus on the oral fluoropyrimidine capecitabine (CAP). We investigate CAP-microbiome interactions through metagenomic sequencing of longitudinal stool sampling from a cohort of advanced colorectal cancer (CRC) patients. We established a prospective cohort study including 56 patients with advanced CRC treated with CAP monotherapy across 4 centers in the Netherlands. Stool samples and clinical questionnaires were collected at baseline, during cycle 3, and post-treatment. Metagenomic sequencing to assess microbial community structure and gene abundance was paired with transposon mutagenesis, targeted gene deletion, and media supplementation experiments. An independent US cohort was used for model validation. CAP treatment significantly altered gut microbial composition and pathway abundance, enriching for menaquinol (vitamin K2) biosynthesis genes. Transposon library screens, targeted gene deletions, and media supplementation confirmed that menaquinol biosynthesis protects Escherichia coli from drug toxicity. Microbial menaquinol biosynthesis genes were associated with decreased peripheral sensory neuropathy. Machine learning models trained in this cohort predicted hand-foot syndrome and dose reductions in an independent cohort. These results suggest treatment-associated increases in microbial vitamin biosynthesis serve a chemoprotective role for bacterial and host cells, with implications for toxicities outside the gastrointestinal tract. We provide a proof-of-concept for the use of microbiome profiling and machine learning to predict drug toxicities across independent cohorts. These observations provide a foundation for future human intervention studies, more in-depth mechanistic dissection in preclinical models, and extension to other cancer treatments.

How Biologics Have Changed the Drug Discovery Landscape.

Advances in molecular biology and molecular genetics as well as major scientific breakthroughs in immunology and oncology have led to the rapid growth of biologic therapeutics. Their success has resulted in significant changes to virtually every step in the drug discovery and development process. Biologics are produced by living organisms, and screening libraries are generated by immunization or phage display. Lead optimization utilizes sophisticated protein engineering to improve drug-like properties and targeting specificity. The manufacturing process for biologics is complex and requires highly specialized facilities. Determination of pharmacology and safety must overcome the complications associated with species specificity. Initial clinical testing must proceed more slowly and carefully due to the limited predictive utility of preclinical data. In summary, the drug discovery and development process has been dramatically altered by biologic therapeutics and will continue to evolve with the introduction of messenger RNA-based therapeutics and the application of artificial intelligence.

Microscopic Phage Adsorption Assay: High-throughput quantification of virus particle attachment to host bacterial cells.

Phages, viruses of bacteria, play a pivotal role in Earth's biosphere and hold great promise as therapeutic and diagnostic tools in combating infectious diseases. Attachment of phages to bacterial cells is a crucial initial step of the interaction. The classic assay to quantify the dynamics of phage attachment involves co-culturing and enumeration of bacteria and phages, which is laborious, lengthy, hence low-throughput, and only provides ensemble estimates of model-based adsorption rate constants. Here, we utilized fluorescence microscopy and particle tracking to obtain trajectories of individual virus particles interacting with cells. The trajectory durations quantified the heterogeneity in dwell time, the time that each phage spends interacting with a bacterium. The average dwell time strongly correlated with the classically-measured adsorption rate constant. We successfully applied this technique to quantify host-attachment dynamics of several phages including those targeting key bacterial pathogens. This approach should benefit the field of phage biology by providing highly quantitative, model-free readouts at single-virus resolution, helping to uncover single-virus phenomena missed by traditional measurements. Owing to significant reduction in manual effort, our method should enable rapid, high-throughput screening of a phage library against a target bacterial strain for applications such as therapy or diagnosis.

TML1 AND TML2 SYNERGISTICALLY REGULATE NODULATION AND AFFECT ARBUSCULAR MYCORRHIZA IN MEDICAGO TRUNCATULA.

Two symbiotic processes, nodulation and arbuscular mycorrhiza, are primarily controlled by the plant's need for nitrogen (N) and phosphorus (P), respectively. Autoregulation of Nodulation (AON) and Autoregulation of Mycorrhization (AOM) both negatively regulate their respective processes and share multiple components - plants that make too many nodules usually have higher AM fungal root colonization. The protein TML (TOO MUCH LOVE) was shown to function in roots to maintain susceptibly to rhizobial infection under low N conditions and control nodule number through AON in Lotus japonicus . M. truncatula has two sequence homologs: Mt TML1 and Mt TML2. We report the generation of stable single and double mutants harboring multiple allelic variations in MtTML1 and MtTML2 using CRISPR-Cas9 targeted mutagenesis and screening of a transposon mutagenesis library. Plants containing single mutations in Mt TML1 or Mt TML2 produced 2-3 times the nodules of wild-type plants whereas plants containing mutations in both genes displayed a synergistic effect, forming 20x more nodules compared to wild type plants. Examination of expression and heterozygote effects suggest genetic compensation may play a role in the observed synergy. Plants with mutations in both TMLs only showed mild increases in AM fungal root colonization at later timepoints in our experiments, suggesting these genes may also play a minor role in AM symbiosis regulation. The mutants created will be useful tools to dissect the mechanism of synergistic action of Mt TML1 and Mt TML2 in M. truncatula symbiosis with beneficial microbes.

Unbiased high-throughput screening of drug-repurposing libraries identifies small-molecule inhibitors of clot retraction

AbstractPlatelet clot retraction, the ultimate phase of platelet thrombus formation, is critical for clot stabilization. It requires functional αIIbβ3 receptors, fibrin, and the integrated actions of the actin-myosin contractile and cytoskeletal systems. Disturbances in clot retraction have been associated with both bleeding and thrombosis. We recently demonstrated that platelets treated with the αIIbβ3 antagonist peptide RGDW, which eliminates fibrinogen-mediated platelet aggregation, are still able to retract clots. We have exploited this observation to develop an unbiased, functional high-throughput assay to identify small-molecule inhibitors of fibrin-mediated clot retraction adapted for a 384-well plate format. We tested 9710 compounds from drug-repurposing libraries (DRLs). These libraries contain compounds that are either US Food and Drug Administration approved or have undergone preclinical/clinical development. We identified 27 compounds from the Library of Pharmacologically Active Compounds library as inhibitors of clot retraction, of which 14 are known inhibitors of platelet function. From the DRLs, we identified 135 compounds (1.6% hit rate). After extensive curation, these compounds were categorized based on the activity of their reported target. Multiple kinase and phosphodiesterase inhibitors with known antiplatelet effects were identified, along with multiple deubiquitination and receptor inhibitors, as well as compounds that have not previously been reported to have antiplatelet activity. Studies of 1 of the deubiquitination inhibitors (degrasyn) suggest that its effects are downstream of thrombin-induced platelet-fibrinogen interactions and thus may permit the separation of platelet thrombin-induced aggregation-mediated events from clot retraction. Additional studies of the identified compounds may lead to novel mechanisms of inhibiting thrombosis.

Identification of novel and potent inhibitors of SARS-CoV-2 main protease from DNA-encoded chemical libraries.

In vitro screening of large compound libraries with automated high-throughput screening is expensive and time-consuming and requires dedicated infrastructures. Conversely, the selection of DNA-encoded chemical libraries (DECLs) can be rapidly performed with routine equipment available in most laboratories. In this study, we identified novel inhibitors of SARS-CoV-2 main protease (Mpro) through the affinity-based selection of the DELopen library (open access for academics), containing 4.2 billion compounds. The identified inhibitors were peptide-like compounds containing an N-terminal electrophilic group able to form a covalent bond with the nucleophilic Cys145 of Mpro, as confirmed by x-ray crystallography. This DECL selection campaign enabled the discovery of the unoptimized compound SLL11 (IC50 = 30 nM), proving that the rapid exploration of large chemical spaces enabled by DECL technology allows for the direct identification of potent inhibitors avoiding several rounds of iterative medicinal chemistry. As demonstrated further by x-ray crystallography, SLL11 was found to adopt a highly unique U-shaped binding conformation, which allows the N-terminal electrophilic group to loop back to the S1' subsite while the C-terminal amino acid sits in the S1 subsite. MP1, a close analog of SLL11, showed antiviral activity against SARS-CoV-2 in the low micromolar range when tested in Caco-2 and Calu-3 (EC50 = 2.3 µM) cell lines. As peptide-like compounds can suffer from low cell permeability and metabolic stability, the cyclization of the compounds will be explored in the future to improve their antiviral activity.

An adaptable, fit-for-purpose screening approach with high-throughput capability to determine speed of action and stage specificity of anti-malarial compounds.

A revamped in vitro compound identification and activity profiling approach is required to meet the large unmet need for new anti-malarial drugs to combat parasite drug resistance. Although compound hit identification utilizing high-throughput screening of large compound libraries is well established, the ability to rapidly prioritize such large numbers for further development is limited. Determining the speed of action of anti-malarial drug candidates is a vital component of malaria drug discovery, which currently occurs predominantly in lead optimization and development. This is due in part to the capacity of current methods which have low throughput due to the complexity and labor intensity of the approaches. Here, we provide an adaptable screening paradigm utilizing automated high content imaging, including the development of an automated schizont maturation assay, which collectively can identify anti-malarial compounds, classify activity into fast and slow acting, and provide an indication of the parasite stage specificity, with high-throughput capability. By frontloading these critical biological parameters much earlier in the drug discovery pipeline, it has the potential to reduce lead compound attrition rates later in the development process. The capability of the approach in its alternative formats is demonstrated using three Medicines for Malaria Venture open access compound "boxes," namely Pathogen Box (malaria set-125 compounds), Global Health Priority Box [Malaria Box 2 (80 compounds) and zoonotic neglected diseases (80 compounds)], and the Pandemic Response Box (400 compounds). From a total of 685 compounds tested, 79 were identified as having fast ring-stage-specific activity comparable to that of artemisinin and therefore of high priority for further consideration and development.

Strategic lead compound design and development utilizing computer-aided drug discovery (CADD) to address herbicide-resistant Phalaris minor in wheat fields.

Wheat (Triticum aestivum) is a vital cereal crop and a staple food source worldwide. However, wheat grain productivity has significantly declined as a consequence of infestations by Phalaris minor. Traditional weed control methods have proven inadequate owing to the physiological similarities between P. minor and wheat during early growth stages. Consequently, farmers have turned to herbicides, targeting acetyl-CoA carboxylase (ACCase), acetolactate synthase (ALS) and photosystem II (PSII). Isoproturon targeting PSII was introduced in mid-1970s, to manage P. minor infestations. Despite their effectiveness, the repetitive use of these herbicides has led to the development of herbicide-resistant P. minor biotypes, posing a significant challenge to wheat productivity. To address this issue, there is a pressing need for innovative weed management strategies and the discovery of novel herbicide molecules. The integration of computer-aided drug discovery (CADD) techniques has emerged as a promising approach in herbicide research, that facilitates the identification of herbicide targets and enables the screening of large chemical libraries for potential herbicide-like molecules. By employing techniques such as homology modelling, molecular docking, molecular dynamics simulation and pharmacophore modelling, CADD has become a rapid and cost-effective medium to accelerate the herbicide discovery process significantly. This approach not only reduces the dependency on traditional experimental methods, but also enhances the precision and efficacy of herbicide development. This article underscores the critical role of bioinformatics and CADD in developing next-generation herbicides, offering new hope for sustainable weed management and improved wheat cultivation practices. © 2024 Society of Chemical Industry.