Drug Targets Research Articles

Development of LAT1-Selective Nuclear Medicine Therapeutics Using Astatine-211

We investigated nuclear medicine therapeutics targeting the L-type amino acid transporter 1 (LAT1). We previously reported that a nuclear medicine therapeutic drug using astatine 211 (211At), an alpha-emitting nuclide that can be produced in an accelerator and targets LAT1 as a molecular target, is effective. The seed compound was 3-[211At] Astato-α-methyl-L-tyrosine (211At-AAMT-OH-L). We used a unique labeling method. By changing the OH group of phenol to a methyl group, retention was successfully increased. It was also found that the amount of the L-isomer taken up by the D-isomer and L-isomer was clearly higher, and the L-isomer was superior as a therapeutic drug. Compounds in which the methyl group was replaced with an ethyl or propyl group were also examined, but their retention did not increase significantly. In fact, we observed increased non-specific accumulation and dynamics, suggesting that labeling may be off. In addition, 211At-AAMT-O-Me-L, which has a simple structure, was clearly superior in terms of uptake speed for several candidate compounds. As a result, we were able to develop a compound that can be easily labeled, has high specific radioactivity, is stable, and has a strong therapeutic effect.

Abstract B006: Role of the BAF complex in pancreatic cancer-associated fibroblast function

Abstract Fibroblasts comprise the majority cell type within connective tissue and play an important role in the support and repair of every organ. This homeostatic support occurs via the activation of fibroblasts (e.g. myofibroblasts) that then secrete growth factors, cytokines, and components of the extracellular matrix (ECM) that can further modulate residential cells. It has been demonstrated that cell-derived ECMs (CDMs) alone, generated in vitro, are sufficient to activate or maintain naive fibroblasts depending on the activation status of the fibroblasts that generated the CDM. Using this CDM system, we published that Netrin G1 is a regulator of pancreatic cancer-associated fibroblast (CAF) function that is pathologically expressed, and that its expression is dependent on the ECM. The mechanistic details behind how the ECM regulates fibroblasts’ gene expression to alter its function and activation status, however, is currently unknown. We previously showed that loss of the β5 integrin subunit negatively impacts the ability of pancreatic CAFs to maintain a constitutively activated state and dampens their pro- tumorigenic functions. RNA sequencing of these β5-deficient CAFs showed altered expression of Netrin G1, as well as members of the BAF (BRG/BRM-associated factor) family of chromatin remodelers. The goal of this project is to elucidate the role of the BAF complex in mediating the outside-in signaling from the ECM. To determine the role of the BAF complex on fibroblast activation and function, knockdown (KD) cell lines for the ATP-subunits Brg1 and Brm1 were generated in patient-derived pancreatic CAFs. Akin to β5 KD CAFs, loss of both Brg1 and Brm1 decreased the expression of published TGFβ-dependent markers of pancreatic CAF activation. However, unlike β5 KD CAFs that are unable to generate substantial, aligned CDMs, Brg1 and Brm1 KD CAFs had no effect on matrix deposition or alignment; like Netrin G1 KD CAFs that have decreased pro-tumor functions. Indeed, loss of Brm1 appears to decrease Netrin G1 akin to β5 KD CAFs. Expression levels of Netrin G1 were not restored in β5 nor Brm1 KD CAFs treated with recombinant TGFβ-1 during CDM production, whereas the TGFβ-dependent activation markers were. Collectively, these data begin to suggest that pro-tumorigenic ECM- mediated signaling may alter fibroblast gene expression via the BAF complex in a TGFβ dependent manner, opening the door to epigenetic drug targets as a new therapeutic access point to normalize the tumor-enabling microenvironment in pancreatic cancer patients. Citation Format: Jaye C. Gardiner, Khoa A. Tran, Janusz Franco-Barraza, Edna Cukierman. Role of the BAF complex in pancreatic cancer-associated fibroblast function [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr B006.

Advanced single-cell and spatial analysis with high-multiplex characterization of circulating tumor cells and tumor tissue in prostate cancer: Unveiling resistance mechanisms with the CoDuCo in situ assay.

Metastatic prostate cancer is a highly heterogeneous and dynamic disease and practicable tools for patient stratification and resistance monitoring are urgently needed. Liquid biopsy analysis of circulating tumor cells (CTCs) and circulating tumor DNA are promising, however, comprehensive testing is essential due to diverse mechanisms of resistance. Previously, we demonstrated the utility of mRNA-based in situ padlock probe hybridization for characterizing CTCs. We have developed a novel combinatorial dual-color (CoDuCo) assay for in situ mRNA detection, with enhanced multiplexing capacity, enabling the simultaneous analysis of up to 15 distinct markers. This approach was applied to CTCs, corresponding tumor tissue, cancer cell lines, and peripheral blood mononuclear cells for single-cell and spatial gene expression analysis. Using supervised machine learning, we trained a random forest classifier to identify CTCs. Image analysis and visualization of results was performed using open-source Python libraries, CellProfiler, and TissUUmaps. Our study presents data from multiple prostate cancer patients, demonstrating the CoDuCo assay's ability to visualize diverse resistance mechanisms, such as neuroendocrine differentiation markers (SYP, CHGA, NCAM1) and AR-V7 expression. In addition, druggable targets and predictive markers (PSMA, DLL3, SLFN11) were detected in CTCs and formalin-fixed, paraffin-embedded tissue. The machine learning-based CTC classification achieved high performance, with a recall of 0.76 and a specificity of 0.99. The combination of high multiplex capacity and microscopy-based single-cell analysis is a unique and powerful feature of the CoDuCo in situ assay. This synergy enables the simultaneous identification and characterization of CTCs with epithelial, epithelial-mesenchymal, and neuroendocrine phenotypes, the detection of CTC clusters, the visualization of CTC heterogeneity, as well as the spatial investigation of tumor tissue. This assay holds significant potential as a tool for monitoring dynamic molecular changes associated with drug response and resistance in prostate cancer.

Parallel Analyses by Mass Spectrometry (MS) and Reverse Phase Protein Array (RPPA) Reveal Complementary Proteomic Profiles in Triple-Negative Breast Cancer (TNBC) Patient Tissues and Cell Cultures.

High-plex proteomic technologies have made substantial contributions to mechanism studies and biomarker discovery in complex diseases, particularly cancer. Despite technological advancements, inherent limitations in individual proteomic approaches persist, impeding the achievement of comprehensive quantitative insights into the proteome. In this study, we employed two widely used proteomic technologies, mass spectrometry (MS) and reverse phase protein array (RPPA) to analyze identical samples, aiming to systematically assess the outcomes and performance of the different technologies. Additionally, we sought to establish an integrated workflow by combining these two proteomic approaches to augment the coverage of protein targets for discovery purposes. We used 14 fresh frozen tissue samples from triple-negative breast cancer (TNBC: seven tumors versus seven adjacent non-cancerous tissues) and cell line samples to evaluate both technologies and implement this dual-proteomic strategy. Using a single-step protein denaturation and extraction protocol, protein samples were subjected to reverse-phase liquid chromatography (LC) followed by electrospray ionization (ESI)-mediated MS/MS for proteomic profiling. Concurrently, identical sample aliquots were analyzed by RPPA for profiling of over 300 proteins and phosphoproteins that are in key signaling pathways or druggable targets in cancer. Both proteomic methods demonstrated the expected ability to differentiate samples by groups, revealing distinct proteomic patterns under various experimental conditions, albeit with minimal overlap in identified targets. Mechanism-based analysis uncovered divergent biological processes identified with the two proteomic technologies, capitalizing on their complementary exploratory potential.

Exploring the Antiviral Potential of Artemisia annua Through JAK-STAT Pathway Targeting: A Network Pharmacology Approach

Background: Artemisia annua, a plant with antiviral potential, has shown promise against various viral infections, yet its mechanisms of action are not fully understood. This study explores A. annua’s antiviral effects using network pharmacology and molecular docking, focusing on key active compounds and their interactions with viral protein targets, particularly within the JAK-STAT signaling pathway—a critical mediator of immune responses to viral infections. Methods: From the TCMSP database, we identified eight active compounds and 335 drug targets for A. annua, with 19 intersecting targets between A. annua compounds and viral proteins. A protein–protein interaction (PPI) network highlighted 10 key hub genes, analyzed further through Gene Ontology (GO) and KEGG pathways to understand their immune and antiviral roles. ADMET properties of the active compound Patuletin (MOL004112) were assessed, followed by 200 ns molecular dynamics simulations to examine its stability in complex with JAK2. Results: PPI analysis identified JAK2, MAPK3, MAPK1, JAK1, PTPN1, HSPA8, TYK2, RAF1, MAPT, and HMOX1 as key hub genes, with JAK2 emerging as a critical regulator of immune and antiviral pathways. ADMET analysis confirmed Patuletin’s favorable pharmacokinetic properties, and molecular dynamics simulations showed a stable Patuletin-JAK2 complex, with FEL analysis indicating minimal disruption to JAK2’s intrinsic flexibility. Conclusions: These findings highlight JAK2 as a promising target in the antiviral activity of A. annua compounds, particularly Patuletin, supporting its potential as an antiviral agent and providing a foundation for further research on A. annua’s therapeutic applications.

A non-canonical mechanism of GPCR activation.

The goal of designing safer, more effective drugs has led to tremendous interest in molecular mechanisms through which ligands can precisely manipulate the signaling of G-protein-coupled receptors (GPCRs), the largest class of drug targets. Decades of research have led to the widely accepted view that all agonists-ligands that trigger GPCR activation-function by causing rearrangement of the GPCR's transmembrane helices, opening an intracellular pocket for binding of transducer proteins. Here we demonstrate that certain agonists instead trigger activation of free fatty acid receptor 1 by directly rearranging an intracellular loop that interacts with transducers. We validate the predictions of our atomic-level simulations by targeted mutagenesis; specific mutations that disrupt interactions with the intracellular loop convert these agonists into inverse agonists. Further analysis suggests that allosteric ligands could regulate the signaling of many other GPCRs via a similar mechanism, offering rich possibilities for precise control of pharmaceutically important targets.

Generating and validating renewable affimer protein binding reagents targeting SH2 domains.

Despite SH2 domains, being pivotal in protein interactions linked to various diseases like cancer, we lack specific research tools for intracellular assays. Understanding SH2-mediated interactions and creating effective inhibitors requires tools which target individual protein domains. Affimer reagents exhibit promise, yet their potential against the extensive SH2 domain family remains largely unexplored. Our study aimed to bridge this gap by identifying Affimer reagents that selectively bind to 22 out of 41 SH2 domains. These reagents enabled a medium-throughput screening approach resembling siRNA studies, shedding light on their functionality. Notably, select Affimers demonstrated the ability to curtail the nuclear translocation of pERK, with Grb2 being a prominent target. Further analyses revealed that these Grb2-specific Affimer reagents displayed competitive inhibition with impressive metrics: IC50s ranging from 270.9 nM to 1.22 µM, together with low nanomolar binding affinities. Moreover, they exhibited the ability to pull down endogenous Grb2 from cell lysates, illustrating their efficacy in binding the Grb2 SH2 domain. This comprehensive assessment underscores the potential of Affimer reagents as domain-specific inhibitors. Their viability for medium/high-throughput phenotypic screening presents a promising avenue via which to identify and characterize potential drug targets within the SH2 domain family.

Genetic variation perspective reveals potential drug targets for subtypes of endometrial cancer.

The study aims to identify potential drug targets for endometrial cancer (EC) subtypes through a Mendelian randomization (MR) approach, assessing their clinical relevance. We utilized genetic instruments for 4,907 plasma proteins from the deCODE Genetics study dataset, and data with EC (n = 12,906) from a genome-wide study (GWAS) meta-analysis in European populations for MR analyses. Complementary analyses included protein-protein interactions (PPI) network analysis, therapeutic efficacy evaluation, differential gene expression assessment, and prognosis evaluation. The expression levels of key drug targets were quantitatively measured at both the transcriptional and translational stages utilizing reverse transcription quantitative PCR (RT-qPCR) and immunohistochemistry (IHC). Additionally, we analyzed various clinicopathological features. Five drug targets for EC (CBR3, GSTO1, HHIP, IGF2R, and MMP10), seven for endometrioid subtypes (ACAP2, CBR3, GSTO1, HHIP, IGF2R, MMP10, and TLR2), and seven for non-endometrioid subtypes (CST3, DNAJB14, FSTL5, GMPR2, IFI16, MAPK9, and NEO1) were identified. Among these, IGF2R (OR = 1.165; 95% CI 1.067-1.272; p = 1.046 × 10- 2) and CST3 (OR = 0.523; 95% CI 0.339-0.804; p = 7.010 × 10- 3) were highlighted as key drug targets with causal evidence both at transcriptional and translational levels. This study preliminarily confirms that IGF2R and CST3 may serve as novel targets for the treatment of EC, providing a foundational reference for innovative clinical approaches to this disease.

Artificial intelligence, medications, pharmacogenomics, and ethics.

Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing various scientific and clinical disciplines including pharmacogenomics (PGx) by enabling the analysis of complex datasets and the development of predictive models. The integration of AI and ML with PGx has the potential to provide more precise, data-driven insights into new drug targets, drug efficacy, drug selection, and risk of adverse events. While significant effort to develop and validate these tools remain, ongoing advancements in AI technologies, coupled with improvements in data quality and depth is anticipated to drive the transition of these tools into clinical practice and delivery of individualized treatments and improved patient outcomes. The successful development and integration of AI-assisted PGx tools will require careful consideration of ethical, legal, and social issues (ELSI) in research and clinical practice. This paper explores the intersection of PGx with AI, highlighting current research and potential clinical applications, and ELSI including privacy, oversight, patient and provider knowledge and acceptance, and the impact on patient-provider relationship and new roles.

Repurposing of drug candidates against Epstein-Barr virus: Virtual screening, docking computations, molecular dynamics, and quantum mechanical study.

Epstein-Barr virus (EBV) was the first tumor virus identified in humans, and it is mostly linked to lymphomas and cancers of epithelial cells. Nevertheless, there is no FDA-licensed drug feasible for this ubiquitous EBV viral contagion. EBNA1 (Epstein-Barr nuclear antigen 1) plays several roles in the replication and transcriptional of latent gene expression of the EBV, making it an attractive druggable target for the treatment of EBV-related malignancies. The present study targets EBV viral reactivation and upkeep by inhibiting EBNA1 utilizing a drug-repurposing strategy. To hunt novel EBNA1 inhibitors, a SuperDRUG2 database (> 4,600 pharmaceutical ingredients) was virtually screened utilizing docking computations. In accordance with the estimated docking scores, the most promising drug candidates then underwent MDS (molecular dynamics simulations). Besides, the MM-GBSA approach was applied to estimate the binding affinities between the identified drug candidates and EBNA1. On the basis of MM-GBSA//200 ns MDS, bezitramide (SD000308), glyburide (SD001170), glisentide (SD001159), and glimepiride (SD001156) unveiled greater binding affinities towards EBNA1 compared to KWG, a reference inhibitor, with ΔGbinding values of -44.3, -44.0, -41.7, -40.2, and -32.4 kcal/mol, respectively. Per-residue decomposition analysis demonstrated that LYS477, ASN519, and LYS586 significantly interacted with the identified drug candidates within the EBNA1 binding pocket. Post-dynamic analyses also demonstrated high constancy of the identified drug candidates in complex with EBNA1 throughout 200 ns MDS. Ultimately, electrostatic potential and frontier molecular orbitals analyses were performed to estimate the chemical reactivity of the identified EBNA1 inhibitors. Considering the current outcomes, this study would be an adequate linchpin for forthcoming research associated with the inhibition of EBNA1; however, experimental assays are required to inspect the efficiency of these candidates.

Associations Between Gene Variants of Lipid-Lowering Drug Targets and Adverse Outcomes After Ischemic Stroke.

The association of lipid-lowering drug targets and their gene variants with cardiovascular diseases has been previously clarified. However, the relationship between gene variants of lipid-lowering drug targets and the adverse prognosis of ischemic stroke patients remains unclear. Multiple single-nucleotide polymorphisms associated with 6 lipid-lowering drug targets were genotyped for patients with ischemic stroke. The primary outcome was death or major disability within 2 years after ischemic stroke. Genetic risk scorewas constructed from significant single-nucleotide polymorphismsidentified via additive models, which was calculated by multiplying the number of risk alleles at each locus by the corresponding beta coefficient and then summing the products. The rs2006760-C of the HMGCR, rs11206510-T of PCSK9, and rs1864163-G and rs9929488-G of CETP were associated with increased odds of adverse outcomes within 2 years after ischemic stroke. Each additional risk allele was associated with higher odds of adverse outcomes. Genetic risk scorewas positively associated with the odds of primary outcome (odds ratio [OR], 1.48 [95% CI, 1.15-1.90]; Ptrend = 0.001), major disability (OR, 1.56[95% CI, 1.16-2.08]; Ptrend = 0.002), death (hazard ratio [HR], 1.58[95% CI, 1.12-2.25]; Ptrend = 0.011), and the composite outcome of death or cardiovascular events (HR, 1.41[95% CI, 1.08-1.85]; Ptrend = 0.010) when 2 extreme quartiles were compared. rs2006760-C of HMGCR, rs11206510-T of PCSK9, and rs1864163-G and rs9929488-G of CETP were associated with increased odds of adverse outcomes within 2 years after ischemic stroke. Furthermore, higher GRS was positively related to the odds of poor outcomes in patients with ischemic stroke. Registration: URL: https://www.clinicaltrials.gov; Identifier: NCT01840072.

Discovery of 1-(Phenylsulfonyl)-1,2,3,4-tetrahydroquinoline Derivative as Orally Bioavailable and Safe RORγt Inverse Agonists for Potential Treatment of Rheumatoid Arthritis.

The retinoic acid receptor-related orphan receptor γt (RORγt) is a key regulator of Th17 cells, associated with autoimmune diseases, making it a significant drug target. Herein, we designed and synthesized 1-(phenylsulfonyl)-1,2,3,4-tetrahydroquinoline derivatives, improving upon GSK2981278 to enhance bioavailability. Of which, D4 exhibited superior bioavailability (F = 48.1 and 32.9% in mice and rats, respectively) compared to GSK2981278 (F = 6.2 and 4.1%, respectively), and effectively treated psoriasis in mice at lower doses. Moreover, for the first time, we report the efficacies of a RORγt inverse agonist in mouse models of rheumatoid arthritis. (R)-D4, the eutomer of D4, matched or exceeded GSK2981278's therapeutic effects at lower doses, with no adverse effects observed after 2 weeks of administration. These results position (R)-D4 as a promising and orally bioavailable candidate for Th17-mediated autoimmune disease treatment.

Discovery and binding mode of small molecule inhibitors of the apo form of human TDO2.

Tryptophan-2,3-dioxygenase (TDO2) and indoleamine-2,3-dioxygenase (IDO1) are structurally distinct heme enzymes that catalyze the conversion of L-tryptophan to N-formyl-kynurenine, and play important roles in metabolism, inflammation, and tumor immune surveillance. The enzymes can adopt an inactive, heme-free (apo) state or an active, heme-containing (holo) state, with the balance between them varying dynamically according to biological conditions. Inhibitors of holo-TDO2 are known but, despite several advantages of the heme-free state as a drug target, no inhibitors of apo-TDO2 have been reported. We describe the discovery of the first apo-TDO2 binding inhibitors, to our knowledge, and their inhibition of cellular TDO2 activity at low nanomolar concentrations. The crystal structure of a potent, small molecule inhibitor bound to apo-TDO2 reveals its detailed binding interactions within the large, hydrophobic heme binding pocket of the active site.

Precision oncology platforms: practical strategies for genomic database utilization in cancer treatment.

In recent years, the expansion of molecularly targeted cancer therapies has significantly advanced precision oncology. Parallel developments in next-generation sequencing (NGS) technologies have also improved precision oncology applications, making genomic analysis of tumors more affordable and accessible. Targeted NGS panels now enable the rapid identification of diverse actionable mutations, requiring clinicians to efficiently assess the predictive value of cancer biomarkers for specific treatments. The urgency for timely and accurate decision-making in oncology emphasizes the importance of reliable precision oncology software. Online clinical decision-making tools and associated cancer databases have been designed by consolidating genomic data into standardized, accessible formats. These new platforms are highly integrated and crucial for identifying actionable somatic genomic biomarkers essential for tumor survival, determining corresponding drug targets, and selecting appropriate treatments based on the mutational profile of each patient's tumor. To help oncologists and translational cancer researchers unfamiliar with these tools, we review the utility, accuracy, and comprehensiveness of several commonly used precision medicine software options currently available. Our analysis categorized selected genomic databases based on their primary content, utility, and how well they provide practical guidance for interpreting somatic biomarker data. We identified several comprehensive, mostly open-access platforms that are easy to use for genetic biomarker searches, each with unique features and limitations. Among the precision oncology tools we evaluated, we found MyCancerGenome and OncoKB to be the first choice, offering comprehensive, accurate up-to-date information on the clinical significance of somatic mutations. To illustrate the application of these precision oncology tools in clinical settings, we evaluated three case studies to see how use of the platforms could have influenced treatment planning. Most of the precision oncology software evaluated could be easily streamlined into clinical workflows to provide updated information on approved drugs and clinical trials related the actionable mutations detected. Some platforms were very intuitive and easy to use, while others, often developed in smaller academic settings, were more difficult to navigate and may not be updated consistently. Future enhancements, incorporating artificial intelligence algorithms, are likely to improve integration of the platforms with diverse big data sources, enabling more accurate predictions of potential therapeutic responses.

Global Profiling Lysine Reactivity and Ligandability with Oxidant‐Triggered Bioconjugation Chemistry

Due to the high abundance and diverse functions of lysine residues, both in the interior and on the surface of proteins, the development of new methods to characterize their reactivity and ligandability could significantly expand the pool of druggable targets. To date, only a limited number of aminophilic electrophiles have been assessed for interactions with the lysine proteome, resulting in a substantial fraction remaining inaccessible to current probes. Here, to the best of our knowledge, we report the first oxidant‐triggered bioconjugation platform for in‐depth profiling of lysines. We quantified over 7000 covalently modifiable lysine residues, which significantly expands the coverage of ligandable lysines in the whole proteome. Chemical proteomics enabled the mapping of more than 100 endogenous kinases, thus providing a comprehensive landscape of ligandable catalytic lysines within the kinome. Moreover, we identified a suite of new ligandable lysines such as K60 of ENO1 and K31 of PPIA, offering insights for exploring new functional and targetable residues. These findings could provide valuable clues for the development of novel targeted covalent inhibitors (TCIs).

Decoding Acute Myeloid Leukemia: A Clinician’s Guide to Functional Profiling

Acute myeloid leukemia (AML) is a complex clonal disorder characterized by clinical, genetic, metabolomic, and epigenetic heterogeneity resulting in the uncontrolled proliferation of aberrant blood-forming precursor cells. Despite advancements in the understanding of the genetic, metabolic, and epigenetic landscape of AML, it remains a significant therapeutic challenge. Functional profiling techniques, such as BH3 profiling (BP), gene expression profiling (GEP), proteomics, metabolomics, drug sensitivity/resistance testing (DSRT), CRISPR/Cas9, and RNAi screens offer valuable insights into the functional behavior of leukemia cells. BP evaluates the mitochondrial response to pro-apoptotic BH3 peptides, determining a cell’s apoptotic threshold and its reliance on specific anti-apoptotic proteins. This knowledge can pinpoint vulnerabilities in the mitochondria-mediated apoptotic pathway in leukemia cells, potentially informing treatment strategies and predicting therapeutic responses. GEP, particularly RNA sequencing, evaluates the transcriptomic landscape and identifies gene expression alterations specific to AML subtypes. Proteomics and metabolomics, utilizing mass spectrometry and nuclear magnetic resonance (NMR), provide a detailed view of the active proteins and metabolic pathways in leukemia cells. DSRT involves exposing leukemia cells to a panel of chemotherapeutic and targeted agents to assess their sensitivity or resistance profiles and potentially guide personalized treatment strategies. CRISPR/Cas9 and RNAi screens enable systematic disruption of genes to ascertain their roles in leukemia cell survival and proliferation. These techniques facilitate precise disease subtyping, uncover novel biomarkers and therapeutic targets, and provide a deeper understanding of drug-resistance mechanisms. Recent studies utilizing functional profiling have identified specific mutations and gene signatures associated with aggressive AML subtypes, aberrant signaling pathways, and potential opportunities for drug repurposing. The integration of multi-omics approaches, advances in single-cell sequencing, and artificial intelligence is expected to refine the precision of functional profiling and ultimately improve patient outcomes in AML. This review highlights the diverse landscape of functional profiling methods and emphasizes their respective advantages and limitations. It highlights select successes in how these methods have further advanced our understanding of AML biology, identifies druggable targets that have improved outcomes, delineates challenges associated with these techniques, and provides a prospective view of the future where these techniques are likely to be increasingly incorporated into the routine care of patients with AML.

Global Profiling Lysine Reactivity and Ligandability with Oxidant-Triggered Bioconjugation Chemistry.

Due to the high abundance and diverse functions of lysine residues, both in the interior and on the surface of proteins, the development of new methods to characterize their reactivity and ligandability could significantly expand the pool of druggable targets. To date, only a limited number of aminophilic electrophiles have been assessed for interactions with the lysine proteome, resulting in a substantial fraction remaining inaccessible to current probes. Here, to the best of our knowledge, we report the first oxidant-triggered bioconjugation platform for in-depth profiling of lysines. We quantified over 7000 covalently modifiable lysine residues, which significantly expands the coverage of ligandable lysines in the whole proteome. Chemical proteomics enabled the mapping of more than 100 endogenous kinases, thus providing a comprehensive landscape of ligandable catalytic lysines within the kinome. Moreover, we identified a suite of new ligandable lysines such as K60 of ENO1 and K31 of PPIA, offering insights for exploring new functional and targetable residues. These findings could provide valuable clues for the development of novel targeted covalent inhibitors (TCIs).

Identification of Potential Inhibitors of TGFβR1 for the Treatment of Cancer through Structure-Based Virtual Screening and Molecular Dynamics Simulations.

Globally, cancer is one of the leading causes of death. Resistance to conventional medications, such as chemotherapy and radiation, continues to be a significant challenge in the treatment of cancer despite the availability of numerous medicines. Therefore, the highest priority is to hunt for new therapeutic agents. Transforming growth factor-beta is a pivotal regulatory cytokine that exerts significant influence over cellular processes, particularly emphasizing its role in facilitating and modulating cell proliferation. TGF-β receptor 1, identified as the most promising active site of the TGF-β signaling, is a potent drug target site that has garnered wide attention for developing new anticancer agents. The present investigation investigates the potential natural products as TGFβR1 inhibitors. The SB431542 complexed TGFβR1 protein model was used to screen the natural product database to obtain a compound with high binding potential. NPC247629 has emerged as the best-scored compound among all the screened compounds, demonstrating the highest affinity towards the TGFβR1 regarding docking score -17.54 kcal/mol. The all-atoms MD simulation study indicated that all proposed hits are retained inside the receptor in dynamic states. Additionally, principal component and free energy landscape analysis were performed to explore the binding mechanism of top-hit natural products. The best-screened hits, NPC247629 and NPC60735, have excellent binding affinity and hold a massive potential for TGFβR1 inhibition, paving the way for promising future investigations in cancer treatment.

Weighted Gene Co-Expression Network Based on Transcriptomics: Unravelling the Differentiation Dynamics of 3T3-L1 Preadipocytes and the Regulatory Mechanism of Protopanaxatriol

The intricate regulatory mechanisms governing adipocyte differentiation are pivotal in elucidating the complex pathophysiology underlying obesity. This study aims to explore the dynamic changes in gene expression during the differentiation of 3T3-L1 adipocytes using transcriptomics methods. Protopanaxatriol (PPT) significantly inhibited adipocyte differentiation. To uncover the molecular mechanisms, we conducted an extensive transcriptomic analysis of adipocytes throughout various differentiation stages, comparing gene expression profiles before and after PPT treatment. The construction of 16 co-expression modules was achieved using weighted gene co-expression network analysis (WGCNA). The 838 differentially expressed genes in the blue module were highly correlated with PPT treatment. Further analysis revealed that PIKfyve, STAT3, JAK1, CTTN, TYK2, JAK3, STAT2, STAT5b, SOCS3, and IRF9 were core genes closely associated with adipocyte differentiation. This discovery underscores the potential pivotal function of these ten genes in regulating adipocyte differentiation. This study elucidated that PPT, an active ingredient in ginseng, could reduce lipid accumulation by inhibiting the differentiation of adipocyte precursors through the negative regulation of genes such as PIKfyve, STAT3, and JAK1. Finally, molecular docking identified potential binding sites for PPT on PIKfyve and JAK1. This study provides potential drug targets for preventing obesity and related metabolic diseases.

Helicobacter pylori Efflux Pumps: A Double-Edged Sword in Antibiotic Resistance and Biofilm Formation

Helicobacter pylori is a major pathogen associated with various gastric diseases. Despite decades of research, the treatment of H. pylori remains challenging. One of the primary mechanisms contributing to failures of therapies targeting this bacterium is genetic mutations in drug target sites, although the growing body of scientific data highlights that efflux pumps may also take part in this process. Efflux pumps are proteinaceous transporters actively expelling antimicrobial agents from the interior of the targeted cells and reducing the intracellular concentration of these compounds. Considering that efflux pumps contribute to both antimicrobial resistance and biofilm formation, an in-depth understanding of their properties may constitute a cornerstone in the development of novel therapeutics against H. pylori. In line with this, the aim of the current review is to describe the multitude of efflux pumps produced by H. pylori and present the data describing the involvement of these proteins in tolerance and/or resistance to various classes of antimicrobial substances.