Drug Discovery Strategies Research Articles

Discovery of FLT3-targeting PROTACs with potent antiproliferative activity against acute myeloid leukemia cells harboring FLT3 mutations

Acute myeloid leukemia (AML) patients harboring Fms-like tyrosine kinase 3 (FLT3) mutations often suffer from poor prognosis and relapse. Targeted protein degradation utilizing proteolysis targeting chimeras (PROTACs) is considered as a novel therapeutic strategy in drug discovery and may be a promising modality to target FLT3 mutations for the development of potent anti-AML drugs. Herein, a kind of FLT3-targeting PROTACs was rationally developed based on a FLT3 inhibitor previously reported by us. The representative compound 35 showed potent and selective antiproliferative activities against AML cells harboring FLT3 mutations. Western blot assay demonstrated that compound 35 effectively induced the degradation of FLT3-ITD and decreased the phosphorylation levels of FLT3-ITD, AKT, STAT5 and ERK in MV4-11 cells in a dose-dependent manner. Flow cytometry analysis illustrated that compound 35 strongly induced apoptosis and cell cycle arrest in MV4-11 cells in a dose-dependent manner. Moreover, compound 35 displayed favorable metabolic stability in in-vitro liver microsomes studies. Comparative molecular dynamic (MD) simulation studies further elucidated the underlying mechanism of compound 35 to stabilize the dynamic ensemble of the FLT3—compound 35—cereblon (CRBN) ternary complex. Taken together, compound 35 could serve as a lead molecule for developing FLT3 degraders against AML.

Exploring Tumor-Promoting Qualities of Cancer-Associated Fibroblasts and Innovative Drug Discovery Strategies With Emphasis on Thymoquinone.

Tumor epithelial development and chemoresistance are highly promoted by the tumor microenvironment (TME), which is mostly made up of the cancer stroma. This is due to several causes. Cancer-associated fibroblasts (CAFs) stand out among them as being essential for the promotion of tumors. Understanding the fibroblastic population within a single tumor is made more challenging by the undeniable heterogeneity within it, even though particular stromal alterations are still up for debate. Numerous chemical signals released by tumors improve the connections between heterotypic fibroblasts and CAFs, promoting the spread of cancer. It becomes essential to have a thorough understanding of this complex microenvironment to effectively prevent solid tumor growth. Important new insights into the role of CAFs in the TME have been revealed by recent studies. The objective of this review is to carefully investigate the relationship between CAFs in tumors and plant secondary metabolites, with a focus on thymoquinone (TQ). The literature published between 2010 and 2023 was searched in PubMed and Google Scholar with keywords such as TQ, TME, cancer-associated fibroblasts, mechanism of action, and flavonoids. The results showed a wealth of data substantiating the activity of plant secondary metabolites, particularly TQ's involvement in blocking CAF operations. Scrutinized research also clarified the wider effect of flavonoids on pathways related to cancer. The present study highlights the complex dynamics of the TME and emphasizes the critical role of CAFs. It also examines the possible interventions provided by secondary metabolites found in plants, with TQ playing a vital role in regulating CAF function based on recent literature.

BacPROTACs targeting Clp protease: a promising strategy for anti-mycobacterial drug discovery.

Tuberculosis (TB) has claimed more lives over the course of two millennia than any other infectious disease worldwide. In 2021, the World Health Organization (WHO) estimated that 10.6 million people were diagnosed with TB, resulting in the deaths of 1.4 million HIV-negative individuals. The emergence of multidrug-resistant TB (MDR-TB), defined as resistance to at least rifampicin (RIF) and isoniazid (INH), and extensively drug-resistant TB (XDR-TB), poses the primary challenge to overcome in the coming years. We have recently conducted an extensive analysis of investments and research endeavours in the field, with the overarching objective of achieving the established milestone of TB eradication by the year 2030. Over the past several years, there has been notable progress in advancing a multitude of promising compounds, each possessing distinct mechanisms of action, into clinical phases of development. However, it is worth noting that strains of mycobacteria resistant to current antitubercular drugs have already emerged for some of these compounds The exploration of the innovative Proteolytic Target Chimeras (PROTACs) protein degradation approach has emerged as a viable avenue for the discovery of novel antimicrobials. While the ubiquitin system is exclusive to eukaryotic cells, certain bacteria use a similar degradation system that relies on the recognition of phosphorylated arginine residues (pArg) by the ClpC:ClpP (ClpCP) protease, thereby leading to protein degradation. In this opinion article, we have described and analized the advances in the use of PROTACs that leverage bacterial proteolytic machinery (BacPROTACs) to design new antitubercular agents. Scope Statement. The development of novel pharmaceuticals for tuberculosis treatment is deemed urgently necessary due to the emergence of resistant strains. In this context, the introduction of new technologies capable of alleviating the disease and attaining the objectives outlined by the World Health Organization is imperative. Among the innovative strategies, the degradation of proteins that are crucial for the survival of the bacillus holds promise for generating new medications, particularly those that are effective at treating latent (non-replicating) Mycobacterium tuberculosis. Within this perspective, we present the advancements and obstacles encountered in the exploration of new BacPROTAC compounds, with the intention of encouraging research and illuminating challenges associated with the implementation of BacPROTACs to address to the global tuberculosis crisis.

In silico and structural investigation of sulfonamides targeting VraSR two component system in methicillin-resistant Staphylococcus aureus

Drug-resistant Staphylococcus aureus strains are global health concerns. Several studies have shown that these strains can develop defences against cell wall antibiotics such as β-lactams, glycopeptides and daptomycin which target cell wall biosynthesis. The coordination of these responses have been associated with two component system (TCS) regulated by histidine kinase protein (VraS) and its cognate regulator VraR which influences the target DNA upon signal recognition. Computer-based screening methods, predictions and simulations have emerged as more efficient and quick ways to identify promising new compound leads from large databases against emerging drug targets thus allowing prediction of small select set of molecules for further validations. These combined approaches conserve valuable time and resources. Due to methicillin resistance, sulfonamide-derivative medications have been found to be effective treatment strategy to treat S. aureus infections. The current study used ligand-based virtual screening (LBVS) to identify powerful sulfonamide derivative inhibitors from an antibacterial compound library against VraSR signaling components, VraS and VraR. We identified promising sulfonamide derivative [compound 5: (4-[(1-{[(3,5-Dimethoxyphenyl)Carbamoyl]Methyl}-2,4-Dioxo-1,2,3,4-Tetrahydroquinazolin-3-Yl)Methyl]-N-[(Furan-2-Yl)Methyl]Benzamide)] with reasonable binding parameters of −31.38 kJ/mol and ΔGbind score of −294.32 kJ/mol against ATP binding domain of sensor kinase VraS. We further identified four compounds N1 (PCID83276726), N3 (PCID83276757), N9 (PCID3672584), and N10 (PCID20900589) against VraR DNA binding domain (VraRC) with ΔGbind energies of −190.27, −237.54, −165.21, and −190.88 kJ/mol, respectively. Structural and simulation analyses further suggest their stable interactions with DNA interacting residues and potential to disrupt DNA binding domain dimerization; therefore, it is prudent to further investigate and characterize them as VraR dimer disruptors and inhibit other promoter binding site. Interestingly, the discovery of drugs that target VraS and VraR may open new therapeutic avenues for drug-resistant S. aureus. These predictions based on screening, simulations and binding affinities against VraSR components hold promise for opening novel therapeutic avenues against drug-resistant S. aureus and present opportunities for repositioning efforts. These efforts aim to create analogs with enhanced potency and selectivity against two-component signaling systems that significantly contribute to virulence in MRSA or VRSA. These analyses contribute valuable insights into potential avenues for combating antibiotic-resistant S. aureus through computationally driven drug discovery strategies. Communicated by Ramaswamy H. Sarma

Genomics and Drug Discovery Strategies: The Role of Natural Compounds and Its Receptor in Alzheimer's Disease.

Alzheimer's Disease (AD) is a special class of neurodegenerative diseases demarcated as a progressive disorder affecting especially older adults globally. The AD-infected brain shows declination in cognitive functions, memory loss, and other exhausting symptoms. In this study, we focused on using advanced bioinformatics and next-generation sequencing to explore essential clusters of genes from various diversified Alzheimer's, Parkinson and Frontotemporal Dementia diseased cases. The significant differential expression analysis of genes (p-value ≤ 0.05, log fold change ≤ 0.05) was carried out, followed by meta-analysis, which resulted in the identification of 20 conserved genes across variable case studies. Out of 20 conserved genes, CASP8 and PTPN11 were observed to show essential regulatory mechanisms in AD metabolic pathways and proceeded further for docking analysis. Moreover, the natural compounds were screened for ligand library preparation based on extensive scientific literature and (ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity)) property check. Molecular docking was carried out with screened ligands and target receptors, resulting in the identification of Rosmarinic acid (RA) with CASP8 having docked score (∆G = -8.0 kcal/mol); Donepezil (FDA drug) dock score (∆G = -7.3 kcal/mol) (control). PTPN11 receptor with Carnosol ligand resulted in docking score (∆G = -9.1 kcal/mol) w.r.t Tacrine (FDA drug) docked score (∆G = -8.0 kcal/mol) followed by MD simulation. This research will aid in the identification of potential natural compounds that future researchers can use for further validation as a potential candidate drug in combating various neurodegenerative diseases highlighting AD.

Fused Enzyme Glucose-6-Phosphate Dehydrogenase::6-Phosphogluconolactonase (G6PD::6PGL) as a Potential Drug Target in Giardia lamblia, Trichomonas vaginalis, and Plasmodium falciparum.

Several microaerophilic parasites such as Giardia lamblia, Trichomonas vaginalis, and Plasmodium falciparum are major disease-causing organisms and are responsible for spreading infections worldwide. Despite significant progress made in understanding the metabolism and molecular biology of microaerophilic parasites, chemotherapeutic treatment to control it has seen limited progress. A current proposed strategy for drug discovery against parasitic diseases is the identification of essential key enzymes of metabolic pathways associated with the parasite's survival. In these organisms, glucose-6-phosphate dehydrogenase::6-phosphogluconolactonase (G6PD:: 6PGL), the first enzyme of the pentose phosphate pathway (PPP), is essential for its metabolism. Since G6PD:: 6PGL provides substrates for nucleotides synthesis and NADPH as a source of reducing equivalents, it could be considered an anti-parasite drug target. This review analyzes the anaerobic energy metabolism of G. lamblia, T. vaginalis, and P. falciparum, with a focus on glucose metabolism through the pentose phosphate pathway and the significance of the fused G6PD:: 6PGL enzyme as a therapeutic target in the search for new drugs.

Natural Products Revolutionizing and Innovative Drug Discovery and Development Strategies: Healthcare Challenges and Future Perspectives

Natural Products Revolutionizing and Innovative Drug Discovery and Development Strategies: Healthcare Challenges and Future Perspectives

Fragment Merging, Growing, and Linking Identify New Trypanothione Reductase Inhibitors for Leishmaniasis.

Trypanothione reductase (TR) is a suitable target for drug discovery approaches against leishmaniasis, although the identification of potent inhibitors is still challenging. Herein, we harnessed a fragment-based drug discovery (FBDD) strategy to develop new TR inhibitors. Previous crystallographic screening identified fragments 1-3, which provided ideal starting points for a medicinal chemistry campaign. In silico investigations revealed critical hotspots in the TR binding site, guiding our structure- and ligand-based structure-actvity relationship (SAR) exploration that yielded fragment-derived compounds 4-14. A trend of improvement in Leishmania infantum TR inhibition was detected along the optimization and confirmed by the crystal structures of 9, 10, and 14 in complex with Trypanosoma brucei TR. Compound 10 showed the best TR inhibitory profile (Ki = 0.2 μM), whereas 9 was the best one in terms of in vitro and ex vivo activity. Although further fine-tuning is needed to improve selectivity, we demonstrated the potentiality of FBDD on a classic but difficult target for leishmaniasis.

High-throughput modular click chemistry synthesis of catechol derivatives as covalent inhibitors of SARS-CoV-2 3CLpro

The 3C-like protease (3CLpro) is a crucial target in anti-Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) drug design. Herein, we performed high-throughput synthesis of catechol derivatives from the bioactive catechol-terminal alkyne scaffold A4, by using modular click chemistry. Subsequently, we conducted two rounds of SARS-CoV-2 3CLpro inhibition screening and selected seven compounds for synthesis and further efficacy validation. Compound P1-E11 had potent inhibitory effects toward SARS-CoV-2 3CLpro (IC50 = 2.54 ± 0.46 μM); exhibited good selectivity toward the human cysteine proteases cathepsins B and L; and demonstrated superior anti-SARS-CoV-2 potency (EC50 = 4.66 ± 0.58 μM) with low cytotoxicity (CC50 > 100 μM) in A549-hACE2-TMPRSS2 cells. The irreversible covalent mechanism of P1-E11 was confirmed through time-dependent experiments, enzyme kinetic studies, and dilution and dialysis assays. The binding affinity between P1-E11 and SARS-CoV-2 3CLpro with a KD value of 0.57 μM was validated through surface plasmon resonance (SPR) experiments. Molecular docking provided insights into the binding mode of P1-E11 to the target protein. This study demonstrated the feasibility and efficacy of modular click reactions in natural-product-based structural modifications and presents a novel approach for leveraging this strategy in antiviral drug discovery.

Discovery of Novel PDEδ Autophagic Degraders: A Case Study of Autophagy-Tethering Compound (ATTEC).

The autophagy-tethering compound (ATTEC) technology has emerged as a promising strategy for targeted protein degradation (TPD). Here, we report the discovery of the first generation of PDEδ autophagic degraders using an ATTEC approach. The most promising compound 12c exhibited potent PDEδ binding affinity and efficiently induced PDEδ degradation in a concentration-dependent manner. Mechanistic studies confirmed that compound 12c reduced the PDEδ protein level through lysosome-mediated autophagy without affecting the PDEδ mRNA expression. Importantly, compound 12c was much more effective in suppressing the growth in KRAS mutant pancreatic cancer cells than the corresponding PDEδ inhibitor. Taken together, this study expands the application scope of the ATTEC approach and highlights the effectiveness of the PDEδ autophagic degradation strategy in antitumor drug discovery.

Based on virtual screening methods and biological activity assessment, AK-968/13030056 has been identified as a potential mTOR inhibitor

The dysregulation of the PI3K/Akt/mTOR signaling pathway is one of the crucial pathways, leading to cancer development. mTOR (Rapamycin/mammalian target of rapamycin) participates in various intracellular signaling processes, regulating cellular metabolism, proliferation, and apoptosis. Numerous mTOR inhibitors have entered clinical research but are not yet on the market. There is an urgent need to develop a drug discovery strategy to accelerate the process. This study applied a virtual screening strategy to identify an mTOR inhibitor with potential inhibitory activity against mTOR. Firstly, we employed the Vina software to dock active and inactive datasets with two proteins (4L23 and 4JT6). The sensitive protein which is based on the docking results and ROC curve analysis is selected. Then, using the KNIME molecular screening program, virtual screening, cluster analysis, and binding model analysis, the 14 hit compounds are identified. Thirdly, through kinase assay and anti-proliferative activity evaluation, the hit compound AK-968/13030056 was ultimately confirmed. Finally, we conducted molecular docking studies and anti-tumor activity research on this compound. The inhibition rate of this compound on mTOR kinase was 70.62 %, exhibiting the strongest inhibitory activity against MCF-7 cells with an IC50 of 7.49 ± 0.87 μM. Subsequently, the biocompatibility of this compound was confirmed through hemolysis testing. Pharmacological experiments including AO staining, JC-1 assays, cell migration, and quantitative real-time PCR analysis also validated its anti-tumor activity. This study has developed a precise and rapid drug discovery strategy, successfully identifying a novel compound with inhibitory activity against the mTOR protein.

Molecular characterization of chronic cutaneous wounds reveals subregion- and wound type-specific differential gene expression.

A limited understanding of the pathology underlying chronic wounds has hindered the development of effective diagnostic markers and pharmaceutical interventions. This study aimed to elucidate the molecular composition of various common chronic ulcer types to facilitate drug discovery strategies. We conducted a comprehensive analysis of leg ulcers (LUs), encompassing venous and arterial ulcers, foot ulcers (FUs), pressure ulcers (PUs), and compared them with surgical wound healing complications (WHCs). To explore the pathophysiological mechanisms and identify similarities or differences within wounds, we dissected wounds into distinct subregions, including the wound bed, border, and peri-wound areas, and compared them against intact skin. By correlating histopathology, RNA sequencing (RNA-Seq), and immunohistochemistry (IHC), we identified unique genes, pathways, and cell type abundance patterns in each wound type and subregion. These correlations aim to aid clinicians in selecting targeted treatment options and informing the design of future preclinical and clinical studies in wound healing. Notably, specific genes, such as PITX1 and UPP1, exhibited exclusive upregulation in LUs and FUs, potentially offering significant benefits to specialists in limb preservation and clinical treatment decisions. In contrast, comparisons between different wound subregions, regardless of wound type, revealed distinct expression profiles. The pleiotropic chemokine-like ligand GPR15L (C10orf99) and transmembrane serine proteases TMPRSS11A/D were significantly upregulated in wound border subregions. Interestingly, WHCs exhibited a nearly identical transcriptome to PUs, indicating clinical relevance. Histological examination revealed blood vessel occlusions with impaired angiogenesis in chronic wounds, alongside elevated expression of genes and immunoreactive markers related to blood vessel and lymphatic epithelial cells in wound bed subregions. Additionally, inflammatory and epithelial markers indicated heightened inflammatory responses in wound bed and border subregions and reduced wound bed epithelialization. In summary, chronic wounds from diverse anatomical sites share common aspects of wound pathophysiology but also exhibit distinct molecular differences. These unique molecular characteristics present promising opportunities for drug discovery and treatment, particularly for patients suffering from chronic wounds. The identified diagnostic markers hold the potential to enhance preclinical and clinical trials in the field of wound healing.

Repurposing FDA-Approved Anastrozole-based Drugs for Breast Cancer through Drug-Drug Transcriptomic Similarity and Cavity Detection Guided Blind Docking

Breast cancer remains a significant global health concern, necessitating innovative strategies for drug discovery and development. Repurposing existing drugs offers a promising avenue, leveraging the wealth of information available on food and drug administration (FDA) approved compounds. This study investigates the repurposing potential of anastrozole-based drugs, already established for their efficacy in certain conditions, for breast cancer treatment. This research presents a multifaceted investigation into the identification, structural refinement, and virtual screening of potential therapeutics targeting the aromatase CYP19A enzyme, a crucial player in hormone-related conditions such as breast cancer. The study commences with the identification of anastrozole-based drugs exhibiting transcriptomic profiles closely resembling known breast cancer therapeutics. Through a comprehensive analysis, a subset of compounds demonstrates high transcriptomic similarity, suggesting shared molecular pathways and target interactions. Notably, anastrozole, a well-known aromatase inhibitor, emerges as a top candidate, highlighting its potential in breast cancer treatment. The crystallographic structure of aromatase CYP19A is subjected to meticulous preprocessing using the PDB-REDO server, resulting in significant improvements in various validation metrics. Structural changes, including alterations in rotamers, removal of water molecules, and peptide flips, indicate the success of the refinement process in enhancing the accuracy of the protein model. The refined structure serves as a reliable foundation for subsequent studies. Further, structure-based cavity detection unveils potential binding sites on the aromatase enzyme. Docking studies employing the cb-dock server elucidate the interaction patterns and binding affinities of selected compounds within these cavities. Anastrozole, along with other candidates like dolasetron and stiripentol, exhibits promising binding scores and interacts with specific residues crucial for enzyme activity. This integrative approach, combining transcriptomic similarity analysis, structural refinement, and virtual screening, provides valuable insights into potential lead compounds for the inhibition of aromatase in breast cancer therapy. The identified compounds offer a starting point for further experimental validation and drug development. The most promising compound that can be repurposed for as an aromatase inhibitor is dolasetron. Overall, this research contributes to the ongoing efforts to leverage computational methodologies for the rational design of targeted therapeutics against hormone-related disorders.

Eriodictyol Flavanones Based Virtual Screening of Bioactive Compounds from ChEMBL 2D Database with Classic 3-point Pharmacophore Screening Method for HER2 Inhibitors for Breast Cancer

Understanding binding interactions between flavanones and human epidermal growth factor receptor 2 (HER2) is an important step in developing effective treatments for breast cancer, and this study applies computational methods to do just that. This research presents a comprehensive computational methodology for identifying potential HER2 inhibitors with a focus on breast cancer treatment. The study leverages a combination of structural and pharmacophore-based approaches, starting with bioactive compound selection from the ChEMBL 2D database. The PDB-REDO refined crystal structure of Kinase domain of Human HER2 (erbB2) was used to conduct molecular docking simulations with the identified drugs. The Kleywegt-like plot analysis demonstrates the improved structural quality of the HER2 kinase domain after refinement, showing enhanced agreement with experimental data. Molecular docking simulations, conducted using the AutoDock tool, reveal the binding affinity and interaction patterns of selected compounds with the HER2 receptor. Virtual screening results highlight compounds with high binding affinity, favorable interaction patterns, and structural compatibility as potential lead candidates. To ensure safety and efficacy, ADMETox filtering was employed, providing insights into the compound’s toxicity profile and pharmacokinetic attributes. The selected compound, Eriodictyol (C20H20O6), exhibits a generally favorable safety profile, with predicted inactivity across multiple toxicity classifications and endpoints. While immunotoxicity is predicted, the overall low probabilities suggest a relatively low risk. Physicochemical and pharmacokinetic assessments indicate Eriodictyol’s potential for drug development. With a molecular weight of 356.37 g/mol, balanced lipophilicity, and high gastrointestinal absorption, the compound aligns with drug-likeness criteria. However, careful consideration is warranted due to its inhibitory effects on certain enzymes and alerts for catechol_A and isolated_alkene. In conclusion, this integrated computational approach streamlines the identification of potential HER2 inhibitors, offering a systematic strategy for drug discovery. Eriodictyol emerges as a promising candidate, demonstrating a favorable safety profile and pharmacokinetic attributes, paving the way for further in-depth studies and development as a potential therapeutic agent for breast cancer.

Dephosphorylation Switch DNAzyme-RCA Circuit: A Robust Strategy for the Homogeneous and Reliable Detection of FTO Demethylase.

Fat mass and obesity-associated protein (FTO) plays a crucial role in regulating the dynamic modification of N6-methyladenosine (m6A) in eukaryotic mRNA. Sensitive detection of the FTO level and efficient evaluation of the FTO demethylase activity are of great importance to early cancer diagnosis and anticancer drug discovery, which are currently challenged by limited sensitivity/precision and low throughput. Herein, a robust strategy based on the dephosphorylation switch DNAzyme-rolling circle amplification (RCA) circuit, termed DSD-RCA, is developed for highly sensitive detection of FTO and inhibitor screening. Initially, the catalytic activity of DNAzyme is silenced by engineering with an m6A modification in its catalytic core. Only in the presence of target FTO can the methyl group on DNAzyme be eliminated, resulting in the activation of the catalytic activity of DNAzyme and thus cleaving the hairpin substrate to release numerous primers. Different from the conventional methods that use the downstream cleavage primer with the original 3'-hydroxyl end directly as the RCA primer with the problem of high background signal, which should be compensated by additional separation and wash steps in heterogeneous format, our DSD-RCA assay uses the upstream cleavage primer with a 2',3'-cyclic phosphate terminus at the 3'-end serving as an intrinsically blocked 3' end. Only after a dephosphorylation reaction mediated by T4 polynucleotide kinase can the upstream cleavage primers with a resultant 3'-hydroxyl end be extended by RCA. With the high signal-to-noise ratio and homogeneous property, the proposed platform can sensitively detect FTO with a limit of detection of 31.4 pM, and the relative standard deviations (RSDs %) ranging from 0.8 to 2.0% were much lower than the heterogeneous methods. The DSD-RCA method was applied for analyzing FTO in cytoplasmic lysates from different cell lines and tissues of breast cancer patients and further used for screening FTO inhibitors without the need for separation or cleaning, providing an opportunity for achieving high throughput and demonstrating the potential applications of this strategy in disease diagnostics, drug discovery, and biological applications.

Exploring the antibiotic potential of cultured ‘unculturable’ bacteria

In response to the severe global antibiotic resistance crisis, this forum delves into ‘unculturable’ bacteria, believed to be a promising source of novel antibiotics. We propose remarkable drug discovery strategies that leverage these bacteria’s diversity, aspiring to transform resistance management. The urgent call for new antibiotics accentuates the essentiality of further research.

Design and Characterization of a Novel eEF2K Degrader with Potent Therapeutic Efficacy Against Triple-Negative Breast Cancer.

Dysregulated eEF2K expression is implicated in the pathogenesis of many human cancers, including triple-negative breast cancer (TNBC), making it a plausible therapeutic target. However, specific eEF2K inhibitors with potent anti-cancer activity have not been available so far. Targeted protein degradation has emerged as a new strategy for drug discovery. In this study, a novel small molecule chemical is designed and synthesized, named as compound C1, which shows potent activity in degrading eEF2K. C1 selectively binds to F8, L10, R144, C146, E229, and Y236 of the eEF2K protein and promotes its proteasomal degradation by increasing the interaction between eEF2K and the ubiquitin E3 ligase βTRCP in the form of molecular glue. C1 significantly inhibits the proliferation and metastasis of TNBC cells both in vitro and in vivo and in TNBC patient-derived organoids, and these antitumor effects are attributed to the degradation of eEF2K by C1. Additionally, combination treatment of C1 with paclitaxel, a commonly used chemotherapeutic drug, exhibits synergistic anti-tumor effects against TNBC. This study not only generates a powerful research tool to investigate the therapeutic potential of targeting eEF2K, but also provides a promising lead compound for developing novel drugs for the treatment of TNBC and other cancers.

Enhancing Opioid Bioactivity Predictions through Integration of Ligand-Based and Structure-Based Drug Discovery Strategies with Transfer and Deep Learning Techniques.

The opioid epidemic has cast a shadow over public health, necessitating immediate action to address its devastating consequences. To effectively combat this crisis, it is crucial to discover better opioid drugs with reduced addiction potential. Artificial intelligence-based and other machine learning tools, particularly deep learning models, have garnered significant attention in recent years for their potential to advance drug discovery. However, using these tools poses challenges, especially when training samples are insufficient to achieve adequate prediction performance. In this study, we investigate the effectiveness of transfer learning in building robust deep learning models to enhance ligand bioactivity prediction for each individual opioid receptor (OR) subtype. This is achieved by leveraging knowledge obtained from pretraining a model using supervised learning on a larger data set of bioactivity data combined with ligand-based and structure-based molecular descriptors related to the entire OR subfamily. Our studies hold the potential to advance opioid research by enabling the rapid identification of novel chemical probes with specific bioactivities, which can aid in the study of receptor function and contribute to the future development of improved opioid therapeutics.

Discovery of JN122, a Spiroindoline-Containing Molecule that Inhibits MDM2/p53 Protein-Protein Interaction and Exerts Robust In Vivo Antitumor Efficacy.

MDM2 and MDM4 cooperatively and negatively regulate p53, while this pathway is often hijacked by cancer cells in favor of their survival. Blocking MDM2/p53 interaction with small-molecule inhibitors liberates p53 from MDM2 mediated degradation, which is an attractive strategy for drug discovery. We reported herein structure-based discovery of highly potent spiroindoline-containing MDM2 inhibitor (-)60 (JN122), which also exhibited moderate activities against MDM4/p53 interactions. In a panel of cancer cell lines harboring wild type p53, (-)60 efficiently promoted activation of p53 and its target genes, inhibited cell cycle progression, and induced cell apoptosis. Interestingly, (-)60 also promoted degradation of MDM4. More importantly, (-)60 exhibited good PK properties and exerted robust antitumor efficacies in a systemic mouse xenograft model of MOLM-13. Taken together, our study showcases a class of potent MDM2 inhibitors featuring a novel spiro-indoline scaffold, which is promising for future development targeting cancer cells with wild-type p53.

An Uncertainty-Guided Deep Learning Method Facilitates Rapid Screening of CYP3A4 Inhibitors.

Cytochrome P450 3A4 (CYP3A4), a prominent member of the P450 enzyme superfamily, plays a crucial role in metabolizing various xenobiotics, including over 50% of clinically significant drugs. Evaluating CYP3A4 inhibition before drug approval is essential to avoiding potentially harmful pharmacokinetic drug-drug interactions (DDIs) and adverse drug reactions (ADRs). Despite the development of several CYP inhibitor prediction models, the primary approach for screening CYP inhibitors still relies on experimental methods. This might stem from the limitations of existing models, which only provide deterministic classification outcomes instead of precise inhibition intensity (e.g., IC50) and often suffer from inadequate prediction reliability. To address this challenge, we propose an uncertainty-guided regression model to accurately predict the IC50 values of anti-CYP3A4 activities. First, a comprehensive data set of CYP3A4 inhibitors was compiled, consisting of 27,045 compounds with classification labels, including 4395 compounds with explicit IC50 values. Second, by integrating the predictions of the classification model trained on a larger data set and introducing an evidential uncertainty method to rank prediction confidence, we obtained a high-precision and reliable regression model. Finally, we use the evidential uncertainty values as a trustworthy indicator to perform a virtual screening of an in-house compound set. The in vitro experiment results revealed that this new indicator significantly improved the hit ratio and reduced false positives among the top-ranked compounds. Specifically, among the top 20 compounds ranked with uncertainty, 15 compounds were identified as novel CYP3A4 inhibitors, and three of them exhibited activities less than 1 μM. In summary, our findings highlight the effectiveness of incorporating uncertainty in compound screening, providing a promising strategy for drug discovery and development.