DrugRepoBank: a comprehensive database and discovery platform for accelerating drug repositioning.

In recent years, drug repositioning has emerged as a promising alternative to the time-consuming, expensive and risky process of developing new drugs for diseases. However, the current database for drug repositioning faces several issues, including insufficient data volume, restricted data types, algorithm inaccuracies resulting from the neglect of multidimensional or heterogeneous data, a lack of systematic organization of literature data associated with drug repositioning, limited analytical capabilities and user-unfriendly webpage interfaces. Hence, we have established the first all-encompassing database called DrugRepoBank, consisting of two main modules: the 'Literature' module and the 'Prediction' module. The 'Literature' module serves as the largest repository of literature-supported drug repositioning data with experimental evidence, encompassing 169 repositioned drugs from 134 articles from 1 January 2000 to 1 July 2023. The 'Prediction' module employs 18 efficient algorithms, including similarity-based, artificial-intelligence-based, signature-based and network-based methods to predict repositioned drug candidates. The DrugRepoBank features an interactive and user-friendly web interface and offers comprehensive functionalities such as bioinformatics analysis of disease signatures. When users provide information about a drug, target or disease of interest, DrugRepoBank offers new indications and targets for the drug, proposes new drugs that bind to the target or suggests potential drugs for the queried disease. Additionally, it provides basic information about drugs, targets or diseases, along with supporting literature. We utilize three case studies to demonstrate the feasibility and effectiveness of predictively repositioned drugs within DrugRepoBank. The establishment of the DrugRepoBank database will significantly accelerate the pace of drug repositioning. Database URL:  https://awi.cuhk.edu.cn/DrugRepoBank.

CapsEnhancer: An Effective Computational Framework for Identifying Enhancers Based on Chaos Game Representation and Capsule Network.

Enhancers are a class of noncoding DNA, serving as crucial regulatory elements in governing gene expression by binding to transcription factors. The identification of enhancers holds paramount importance in the field of biology. However, traditional experimental methods for enhancer identification demand substantial human and material resources. Consequently, there is a growing interest in employing computational methods for enhancer prediction. In this study, we propose a two-stage framework based on deep learning, termed CapsEnhancer, for the identification of enhancers and their strengths. CapsEnhancer utilizes chaos game representation to encode DNA sequences into unique images and employs a capsule network to extract local and global features from sequence "images". Experimental results demonstrate that CapsEnhancer achieves state-of-the-art performance in both stages. In the first and second stages, the accuracy surpasses the previous best methods by 8 and 3.5%, reaching accuracies of 94.5 and 95%, respectively. Notably, this study represents the pioneering application of computer vision methods to enhancer identification tasks. Our work not only contributes novel insights to enhancer identification but also provides a fresh perspective for other biological sequence analysis tasks.

Vascular reconstruction provides short-term and long-term survival benefits for patients with hilar cholangiocarcinoma: A retrospective, multicenter study.

BACKGROUND: In patients with hilar cholangiocarcinoma (HCCA), radical resection can be achieved by resection and reconstruction of the vasculature. However, whether vascular reconstruction (VR) improves long-term and short-term prognosis has not been demonstrated comprehensively. METHODS: This was a retrospective multicenter study of patients who received surgery for HCCA with or without VR. Variables associated with overall survival (OS) and recurrence-free survival (RFS) were identified based on Cox regression. Kaplan-Meier curves were used to explore the impact of VR. Restricted mean survival time (RMST) was used for comparisons of short-term survival between the groups. Patients' intraoperative and postoperative characteristics were compared. RESULTS: Totally 447 patients were enrolled. We divided these patients into 3 groups: VR with radical resections (n = 84); non-VR radical resections (n = 309) and non-radical resection (we pooled VR-nonradical and non-VR nonradical together, n = 54). Cox regression revealed that carbohydrate antigen 242 (CA242), vascular invasion, lymph node metastasis and poor differentiation were independent risk factors for OS and RFS. There was no significant difference of RMST between the VR and non-VR radical groups within 12 months after surgery (10.18 vs. 10.76 mon, P = 0.179), although the 5-year OS (P < 0.001) and RFS (P < 0.001) were worse in the VR radical group. The incidences of most complications were not significantly different, but those of bile leakage (P < 0.001) and postoperative infection (P = 0.009) were higher in the VR radical group than in the non-VR radical group. Additionally, the levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) up to 7 days after surgery tended to decrease in all groups. There was no significant difference in the incidence of postoperative liver failure between the VR and non-VR radical groups. CONCLUSIONS: Radical resection can be achieved with VR to improve the survival rate without worsening short-term survival compared with resection with non-VR. After adequate assessment of the patient's general condition, VR can be considered in the resection.

Residual biliary intraepithelial neoplasia without malignant transformation at resection margin for perihilar cholangiocarcinoma does not require expanded resection: a dual center retrospective study.

BACKGROUND: Additional resection for invasive cancer at perihilar cholangiocarcinoma (pCCA) resection margins has become a consensus. However, controversy still exists regarding whether additional resection is necessary for residual biliary intraepithelial neoplasia (BilIN). METHOD: Consecutive patients with pCCA from two hospitals were enrolled. The incidence and pattern of resection margin BilIN were summarized. Prognosis between patients with negative margins (R0) and BilIN margins were analyzed. Cox regression with a forest plot was used to identify independent risk factors associated with overall survival (OS) and recurrence-free survival (RFS). Subgroup analysis was performed based on BilIN features and tumor characteristics. RESULTS: 306 pCCA patients receiving curative resection were included. 255 had R0 margins and 51 had BilIN margins. There was no significant difference in OS (P = 0.264) or RFS (P = 0.149) between the two group. Specifically, 19 patients with BilIN at distal bile ducts and 32 at proximal bile ducts. 42 patients showed low-grade BilIN, and 9 showed high-grade. Further analysis revealed no significant difference in long-term survival between different locations (P = 0.354), or between different grades (P = 0.772). Portal vein invasion, poor differentiation and lymph node metastasis were considered independent risk factors for OS and RFS, while BilIN was not. Subgroup analysis showed no significant difference in long-term survival between the lymph node metastasis subgroup, or between the portal vein invasion subgroup. CONCLUSION: For pCCA patients underwent curative resection, residual BilIN at resection margin is acceptable. Additional resection is not necessary for such patients to achieve absolute R0 margin.

A Causal Regulation Modeling Algorithm for Temporal Events with Application to Escherichia coli's Aerobic to Anaerobic Transition.

Time-series experiments are crucial for understanding the transient and dynamic nature of biological phenomena. These experiments, leveraging advanced classification and clustering algorithms, allow for a deep dive into the cellular processes. However, while these approaches effectively identify patterns and trends within data, they often need to improve in elucidating the causal mechanisms behind these changes. Building on this foundation, our study introduces a novel algorithm for temporal causal signaling modeling, integrating established knowledge networks with sequential gene expression data to elucidate signal transduction pathways over time. Focusing on Escherichia coli's (E. coli) aerobic to anaerobic transition (AAT), this research marks a significant leap in understanding the organism's metabolic shifts. By applying our algorithm to a comprehensive E. coli regulatory network and a time-series microarray dataset, we constructed the cross-time point core signaling and regulatory processes of E. coli's AAT. Through gene expression analysis, we validated the primary regulatory interactions governing this process. We identified a novel regulatory scheme wherein environmentally responsive genes, soxR and oxyR, activate fur, modulating the nitrogen metabolism regulators fnr and nac. This regulatory cascade controls the stress regulators ompR and lrhA, ultimately affecting the cell motility gene flhD, unveiling a novel regulatory axis that elucidates the complex regulatory dynamics during the AAT process. Our approach, merging empirical data with prior knowledge, represents a significant advance in modeling cellular signaling processes, offering a deeper understanding of microbial physiology and its applications in biotechnology.

A two-stage computational framework for identifying antiviral peptides and their functional types based on contrastive learning and multi-feature fusion strategy.

Antiviral peptides (AVPs) have shown potential in inhibiting viral attachment, preventing viral fusion with host cells and disrupting viral replication due to their unique action mechanisms. They have now become a broad-spectrum, promising antiviral therapy. However, identifying effective AVPs is traditionally slow and costly. This study proposed a new two-stage computational framework for AVP identification. The first stage identifies AVPs from a wide range of peptides, and the second stage recognizes AVPs targeting specific families or viruses. This method integrates contrastive learning and multi-feature fusion strategy, focusing on sequence information and peptide characteristics, significantly enhancing predictive ability and interpretability. The evaluation results of the model show excellent performance, with accuracy of 0.9240 and Matthews correlation coefficient (MCC) score of 0.8482 on the non-AVP independent dataset, and accuracy of 0.9934 and MCC score of 0.9869 on the non-AMP independent dataset. Furthermore, our model can predict antiviral activities of AVPs against six key viral families (Coronaviridae, Retroviridae, Herpesviridae, Paramyxoviridae, Orthomyxoviridae, Flaviviridae) and eight viruses (FIV, HCV, HIV, HPIV3, HSV1, INFVA, RSV, SARS-CoV). Finally, to facilitate user accessibility, we built a user-friendly web interface deployed at https://awi.cuhk.edu.cn/∼dbAMP/AVP/.

AMPActiPred: A three-stage framework for predicting antibacterial peptides and activity levels with deep forest.

The emergence and spread of antibiotic-resistant bacteria pose a significant public health threat, necessitating the exploration of alternative antibacterial strategies. Antibacterial peptide (ABP) is a kind of antimicrobial peptide (AMP) that has the potential ability to fight against bacteria infection, offering a promising avenue for developing novel therapeutic interventions. This study introduces AMPActiPred, a three-stage computational framework designed to identify ABPs, characterize their activity against diverse bacterial species, and predict their activity levels. AMPActiPred employed multiple effective peptide descriptors to effectively capture the compositional features and physicochemical properties of peptides. AMPActiPred utilized deep forest architecture, a cascading architecture similar to deep neural networks, capable of effectively processing and exploring original features to enhance predictive performance. In the first stage, AMPActiPred focuses on ABP identification, achieving an Accuracy of 87.6% and an MCC of 0.742 on an elaborate dataset, demonstrating state-of-the-art performance. In the second stage, AMPActiPred achieved an average GMean at 82.8% in identifying ABPs targeting 10 bacterial species, indicating AMPActiPred can achieve balanced predictions regarding the functional activity of ABP across this set of species. In the third stage, AMPActiPred demonstrates robust predictive capabilities for ABP activity levels with an average PCC of 0.722. Furthermore, AMPActiPred exhibits excellent interpretability, elucidating crucial features associated with antibacterial activity. AMPActiPred is the first computational framework capable of predicting targets and activity levels of ABPs. Finally, to facilitate the utilization of AMPActiPred, we have established a user-friendly web interface deployed at https://awi.cuhk.edu.cn/∼AMPActiPred/.

Knocking down of Xkr8 enhances chemotherapy efficacy through modulating tumor immune microenvironment.

Scramblase Xk-related protein 8 (Xkr8) regulates the externalization of phosphatidylserine (PS) during apoptosis and holds a pivotal role in fostering tumor immunosuppression. Targeting Xkr8 in conjunction with chemotherapy demonstrated a novel avenue for amplifying antitumor immune response and overcoming chemo-immune resistance. Here we further evaluated this strategy by using a clinically relevant orthotopic model and elucidated the mechanism through in-depth single-cell RNA sequencing (scRNA-seq). We found that Xkr8 knockdown exhibited the potential to lead to immunogenic cell death (ICD) by impeding the normal clearance of apoptotic cells. Co-delivery of Xkr8 small interference RNA (siRNA) and a prodrug conjugate of 5-fluorouracil (5-Fu) and oxoplatin (FuOXP) showed remarkable therapeutic efficacy in an orthotopic pancreatic tumor model with increased infiltration of proliferative NK cells and activated macrophages in the tumor microenvironment (TME). Single-cell trajectory analysis further unveiled that tumor infiltrating CD8+ T cells are differentiated favorably to cytotoxic over exhausted phenotype after combination treatment. Our study sheds new light on the impact of Xkr8 knockdown on TME and solidifies the rationale of combining Xkr8 knockdown with chemotherapy to treat various types of cancers.

Design, synthesis and Anti-PVY activity of planar chiral thiourea derivatives incorporated with [2.2]Paracyclophane.

BACKGROUND: Potato virus Y (PVY) is a prominent representative of plant viruses. It can inflict severe damage upon Solanaceae plants, leading to global dissemination and substantial economic losses. To discover new antiviral agents, a class of planar chiral thiourea molecules through the key step of N-heterocyclic carbene-catalyzed nitrile formation reaction was synthesized with excellent optical purities for antiviral evaluations against plant virus PVY. RESULTS: The absolute configurations of the planar chiral compounds exhibited obvious distinctions in the anti-PVY activities. Notability, compound (S)-4u exhibited remarkable curative activities against PVY, with a half maximal effective concentration (EC50) of 349.3 µg mL-1, which was lower than that of the ningnanmycin (NNM) (EC50 = 400.8 µg mL-1). Additionally, The EC50 value for the protective effects of (S)-4u was 146.2 µg mL-1, which was superior to that of NNM (276.4 µg mL-1). Furthermore, the mechanism-of-action of enantiomers of planar chiral compound 4u was investigated through molecular docking, defensive enzyme activity tests and chlorophyll content tests. CONCLUSION: Biological mechanism studies have demonstrated that the configuration of planar chiral target compounds plays a crucial role in the molecular interaction with PVY-CP, enhancing the activity of defense enzymes and affecting chlorophyll content. The current study has provided significant insights into the roles played by planar chiralities in plant protection against viruses. This paves the way for the development of novel green pesticides bearing planar chiralities with excellent optical purities. © 2024 Society of Chemical Industry.

Recent Advances in NHC-Catalyzed Chemoselective Activation of Carbonyl Compounds.

N-Heterocyclic carbenes (NHCs) catalysts have been employed as effective tools in the development of various reactions, which have made notable contributions in developing diverse reaction modes and generating significant functionalized molecules. This review provides an overview of the recent advancements in the chemo- and regioselective activation of different aldehydes using NHCs, categorized into five parts based on the different activation modes. A brief conclusion and outlook is provided to stimulate the development of novel activation modes for accessing functional molecules.

In Situ Formation of Fibronectin-Enriched Protein Corona on Epigenetic Nanocarrier for Enhanced Synthetic Lethal Therapy.

PARP inhibitors (PARPi)-based synthetic lethal therapy demonstrates limited efficacy for most cancer types that are homologous recombination (HR) proficient. To potentiate the PARPi application, a nanocarrier based on 5-azacytidine (AZA)-conjugated polymer (PAZA) for the codelivery of AZA and a PARP inhibitor, BMN673 (BMN) is developed. AZA conjugation significantly decreased the nanoparticle (NP) size and increased BMN loading. Molecular dynamics simulation and experimental validations shed mechanistic insights into the self-assembly of effective NPs. The small PAZA NPs demonstrated higher efficiency of tumor targeting and penetration than larger NPs, which is mediated by a new mechanism of active targeting that involves the recruitment of fibronectin from serum proteins following systemic administration of PAZA NPs. Furthermore, it is found that PAZA carrier sensitize the HR-proficient nonsmall cell lung cancer (NSCLC) to BMN, a combination therapy that is more effective at a lower AZA/BMN dosage. To investigate the underlying mechanism, the tumor immune microenvironment and various gene expressions by RNAseq are explored. Moreover, the BMN/PAZA combination increased the immunogenicity and synergized with PD-1 antibody in improving the overall therapeutic effect in an orthotopic model of lung cancer (LLC).

KinPred-RNA-kinase activity inference and cancer type classification using machine learning on RNA-seq data.

Kinases as important enzymes can transfer phosphate groups from high-energy and phosphate-donating molecules to specific substrates and play essential roles in various cellular processes. Existing algorithms for kinase activity from phosphorylated proteomics data are often costly, requiring valuable samples. Moreover, methods to extract kinase activities from bulk RNA sequencing data remain undeveloped. In this study, we propose a computational framework KinPred-RNA to derive kinase activities from bulk RNA-sequencing data in cancer samples. KinPred-RNA framework, using the extreme gradient boosting (XGBoost) regression model, outperforms random forest regression, multiple linear regression, and support vector machine regression models in predicting kinase activities from cancer-related RNA sequencing data. Efficient gene signatures from the LINCS-L1000 dataset were used as inputs for KinPred-RNA. The results highlight its potential to be related to biological function. In conclusion, KinPred RNA constitutes a significant advance in cancer research by potentially facilitating the identification of cancer.

Discovery of Novel Chiral Indole Derivatives Containing the Oxazoline Moiety as Potential Antiviral Agents for Plants.

Potato virus Y (PVY) is an important plant virus that has spread worldwide, causing significant economic losses. To search for novel structures as potent antiviral agents, a series of chiral indole derivatives containing oxazoline moieties were designed and synthesized and their anti-PVY activities were evaluated. Biological activity tests demonstrated that many chiral compounds exhibited promising anti-PVY activities and that their absolute configurations exhibited obvious distinctions in antiviral bioactivities. Notably, compound (S)-4v displayed excellent curative and protective efficacy against PVY, with EC50 values of 328.6 and 256.1 µg/mL, respectively, which were superior to those of commercial virucide ningnanmycin (NNM, 437.4 and 397.4 µg/mL, respectively). The preliminary antiviral mechanism was investigated to determine the difference in antiviral activity between the two enantiomers of 4v chiral compounds. Molecular docking indicated a stronger binding affinity between the coating proteins of PVY (PVY-CP) and (S)-4v (-6.5 kcal/mol) compared to (R)-4v (-6.2 kcal/mol). Additionally, compound (S)-4v can increase the chlorophyll content and defense-related enzyme activities more effectively than its enantiomer. Therefore, this study provides an important basis for the development of chiral indole derivatives containing oxazoline moieties as novel agricultural chemicals.

Inhibition of iRhom1 by CD44-targeting nanocarrier for improved cancer immunochemotherapy.

The multifaceted chemo-immune resistance is the principal barrier to achieving cure in cancer patients. Identifying a target that is critically involved in chemo-immune-resistance represents an attractive strategy to improve cancer treatment. iRhom1 plays a role in cancer cell proliferation and its expression is negatively correlated with immune cell infiltration. Here we show that iRhom1 decreases chemotherapy sensitivity by regulating the MAPK14-HSP27 axis. In addition, iRhom1 inhibits the cytotoxic T-cell response by reducing the stability of ERAP1 protein and the ERAP1-mediated antigen processing and presentation. To facilitate the therapeutic translation of these findings, we develop a biodegradable nanocarrier that is effective in codelivery of iRhom pre-siRNA (pre-siiRhom) and chemotherapeutic drugs. This nanocarrier is effective in tumor targeting and penetration through both enhanced permeability and retention effect and CD44-mediated transcytosis in tumor endothelial cells as well as tumor cells. Inhibition of iRhom1 further facilitates tumor targeting and uptake through inhibition of CD44 cleavage. Co-delivery of pre-siiRhom and a chemotherapy agent leads to enhanced antitumor efficacy and activated tumor immune microenvironment in multiple cancer models in female mice. Targeting iRhom1 together with chemotherapy could represent a strategy to overcome chemo-immune resistance in cancer treatment.

Adequate cumulative exposure to tacrolimus and low tacrolimus variability decrease the incidence of biliary complications after liver transplantation.

BACKGROUND: Nonearly biliary complications (BCs) after liver transplantation (LT) are highly associated with immunological status. Tacrolimus is the main immunosuppressant. Whether and how tacrolimus bioavailability affects BCs is unclear. METHODS: LT recipients receiving tacrolimus-free immunosuppressants or developing BCs within 3 months after LT were excluded. Tacrolimus-related variables included trough concentration (C0), variability and cumulative exposure to tacrolimus (CET). Receiver operating characteristic (ROC) curves defined cutoff values of CET and variability. The values divided patients into adequate and low CET groups, also high and low-variability groups. Inverse probability of treatment weighting (IPTW) was used to reduce bias. Logistic regression identified risk factors. Kaplan-Meier curves were generated for survival comparison. RESULTS: 409 patients were enrolled, and 39 (9.5 %) suffered from BCs. The mean C0 values were 6.9 and 7.2 ng/mL in the BCs and BCs-free groups, respectively. CET within 3 postoperative months was 550.0 and 608.6 ng.day/mL, while the tacrolimus variability was 0.4 and 0.3, respectively. The cutoff values for CET within 3 months and variability predicting BCs were 660.5 and 0.54, respectively. Multivariable logistic regression revealed that low CET within 3 months (p = 0.005, p = 0.002) and high variability (p < 0.001, p < 0.001) were associated with BCs before and after IPTW. Appropriate CET and low variability were associated with better overall survival (p = 0.009 and 0.029). Subgroup analysis indicated that long cold ischemia time (CIT), high bilirubin and low CET had a higher relative risk and raised the incidence of BCs. CONCLUSIONS: Adequate CET and low variability of tacrolimus ameliorated nonearly BCs incidence and improved survival.

Mechanism of Sophorae Flavescentis Radix (Kushen) in treating NSCLC: Insights from miRNA-mRNA network analysis.

ETHNOPHARMACOLOGICAL RELEVANCE: Sophorae Flavescentis Radix (Kushen) is the primary herb component of Compound Kushen Injection (CKI), an approved clinical treatment for tumors. Despite CKI's widespread use, the underlying mechanisms of Kushen regarding microRNA-target and pathway remain unclear in non-small cell lung cancer (NSCLC). AIM OF THE STUDY: This study aimed to elucidate the crucial miRNAs-targets and pathways responsible for the Kushen's impact on NSCLC. MATERIALS AND METHODS: CCK8, colony formation, and apoptosis assays were performed to assess the effects of Kushen on NSCLC cells. Subsequently, we treated the A549 cell line with varying concentrations of Kushen to obtain mRNA and miRNA expression profiles. A DE (differentially expressed) miRNAs-DEGs network was then constructed to identify the critical miRNA-mRNA interaction influenced by Kushen. Furthermore, we performed clinical significance and prognosis analyses of hub genes to narrow down key genes and their corresponding miRNAs. Finally, the effects of Kushen on critical miRNA-mRNA interaction and related pathway were verified by in vitro and in vivo experiments. RESULTS: In this study, we initially demonstrated that Kushen significantly inhibited cell proliferation, suppressed colony formation, and induced apoptosis in the A549 cells, PC9 cells, and the A549 zebrafish xenograft model. Through expression profile analysis, a DE miRs-DEGs network was constructed with 16 DE miRs and 68 DEGs. Through the network analysis and expression validation, we found Kushen could significantly down-regulate miR-183-5p expression and up-regulate EGR1 expression. Additionally, Kushen affected the PTEN/Akt pathway, increasing PTEN expression and decreasing pAkt expression. Finally, matrine, the essential active compound of Kushen, also inhibited cell growth, induced apoptosis, and regulated miR-183-5p/EGR1 and PTEN/AKT pathway. CONCLUSIONS: Altogether, these findings supported the critical role of miR-183-5p/EGR1 and the PTEN/AKT pathway in the beneficial effects of Kushen on NSCLC, highlighting the therapeutic potential of Kushen in NSCLC treatment.

The Development of Aldehyde Catalytic System.

Aldehyde catalysts have proven to be highly effective in facilitating and accelerating a wide range of challenging transformations in organic chemistry. This article is structured into three main sections, focusing on the utilization of aldehydes as organocatalysts, the aldehydes/transition metals catalytic systems, and photochemical initiators. Finally, we provide a concise summary of the advancements in this fascinating research field, offering our perspectives and insights.

A Robust Drug-Target Interaction Prediction Framework with Capsule Network and Transfer Learning.

Drug-target interactions (DTIs) are considered a crucial component of drug design and drug discovery. To date, many computational methods were developed for drug-target interactions, but they are insufficiently informative for accurately predicting DTIs due to the lack of experimentally verified negative datasets, inaccurate molecular feature representation, and ineffective DTI classifiers. Therefore, we address the limitations of randomly selecting negative DTI data from unknown drug-target pairs by establishing two experimentally validated datasets and propose a capsule network-based framework called CapBM-DTI to capture hierarchical relationships of drugs and targets, which adopts pre-trained bidirectional encoder representations from transformers (BERT) for contextual sequence feature extraction from target proteins through transfer learning and the message-passing neural network (MPNN) for the 2-D graph feature extraction of compounds to accurately and robustly identify drug-target interactions. We compared the performance of CapBM-DTI with state-of-the-art methods using four experimentally validated DTI datasets of different sizes, including human (Homo sapiens) and worm (Caenorhabditis elegans) species datasets, as well as three subsets (new compounds, new proteins, and new pairs). Our results demonstrate that the proposed model achieved robust performance and powerful generalization ability in all experiments. The case study on treating COVID-19 demonstrates the applicability of the model in virtual screening.

Carbene-Catalyzed Atroposelective Annulation for Quick Access to Axially Chiral Thiazine Derivatives.

An N-heterocyclic carbene (NHC)-catalyzed atroposelective annulation reaction is disclosed for quick and efficient access to thiazine derivatives. A series of axially chiral thiazine derivatives bearing various substituents and substitution patterns were produced in moderate to high yields with moderate to excellent optical purities. Preliminary studies revealed that some of our products exhibit promising antibacterial activities against Xanthomonas oryzae pv. oryzae (Xoo) that causes rice bacterial blight.

Quassinoid analogs exert potent antitumor activity via reversible protein biosynthesis inhibition in human colorectal cancer.

Cellular protein synthesis is accelerated in human colorectal cancer (CRC), and high expression of protein synthesis regulators in CRC patients is associated with poor prognosis. Thus, inhibition of protein synthesis may be an effective therapeutic strategy for CRC. We previously demonstrated that the quassinoid bruceantinol (BOL) had antitumor activity against CRC. Herein, potent tumor growth suppression (>80%) and STAT3 inhibition was observed in two different mouse models following BOL administration. Loss of body and spleen weight was observed but was eliminated upon nanoparticle encapsulation while maintaining strong antitumor activity. STAT3 siRNA knockdown exhibited modest suppression of cell proliferation. Surprisingly, STAT3 inhibition using a PROTAC degrader (SD-36) had little effect on cancer cell proliferation suggesting the possibility of additional mechanism(s) of action for quassinoids. BOL-resistant (BR) cell lines, HCT116BR and HCA7BR, were equally sensitive to standard CRC therapeutic agents and known STAT3 inhibitors but resistant to homoharringtonine (HHT), a known protein synthesis inhibitor. The ability of quassinoids to inhibit protein synthesis was dependent on the structure of the C15 sidechain. Of note, BOL did not inhibit protein synthesis in normal human colon epithelial cells whereas HHT and napabucasin remained effective in these normal cells. Novel quassinoids were designed, synthesized, and evaluated in pre-clinical CRC models. Treatment with the most potent analog, 5c, resulted in significant inhibition of cell proliferation and protein synthesis at nanomolar concentrations. These quassinoid analogs may represent a novel class of protein synthesis inhibitors for the treatment of human CRC.