Plant flavonoid inhibition of SARS-CoV-2 main protease and viral replication.

Plant-based flavonoids have been evaluated as inhibitors of ß-coronavirus replication and as therapies for COVID-19 on the basis of their safety profile and widespread availability. The SARS-CoV-2 main protease (Mpro) has been implicated as a target for flavonoids in silico. Yet no comprehensive in vitro testing of flavonoid activity against SARS-CoV-2 Mpro has heretofore been performed. We screened 1,019 diverse flavonoids for their ability to inhibit SARS-CoV-2 Mpro. Multiple structure-activity relationships were identified among active compounds such as enrichment of galloylated flavonoids and biflavones, including multiple biflavone analogs of apigenin. In a cell-based SARS-CoV-2 replication assay, the most potent inhibitors were apigenin and the galloylated pinocembrin analog, pinocembrin 7-O-(3''-galloyl-4'',6''-(S)-hexahydroxydiphenoyl)-beta-D-glucose (PGHG). Molecular dynamic simulations predicted that PGHG occludes the S1 binding site via a galloyl group and induces a conformational change in Mpro. These studies will advance the development of plant-based flavonoids-including widely available natural products-to target ß-coronaviruses.

Inhibition of Amyloid ß Aggregation and Cytotoxicity by Berbamine Hydrochloride.

Alzheimer's disease (AD) continues to be a major global health challenge, and the recent approval of Aduhelm and Leqembi has opened new avenues for its treatment. Small-molecule inhibitors targeting Aß aggregation hold promise as an alternative to monoclonal antibodies. In this study, we evaluated the ability of berbamine hydrochloride (BBMH), a member of the bisbenzylisoquinoline alkaloids, to reduce Aß aggregation and cytotoxicity. Thioflavin T kinetics, circular dichroism spectroscopy, and atomic force microscopy results indicated that BBMH effectively inhibited Aß aggregation. Surface plasmon resonance and molecular docking results further revealed that BBMH could bind to Aß fibrils, thereby hindering the aggregation process. This physical picture has been confirmed in a quantitative way by chemical kinetics analysis, which showed BBMH tends to bind with the fibril ends and thus prevents the transition from protofibrils to mature fibrils as well as the elongation process. Additionally, our MTT results showed that BBMH was able to reduce the cytotoxicity of Aß40 on N2a cells. Our results demonstrate, for the first time, the potential of BBMH to inhibit Aß aggregation and cytotoxicity, offering a promising direction for further research and drug development efforts in the fight against Alzheimer's disease.

Normalization of Tumor Vessels by Lenvatinib-Based Metallo-Nanodrugs Alleviates Hypoxia and Enhances Calreticulin-Mediated Immune Responses in Orthotopic HCC and Organoids.

Immunocheckpoint inhibitors combined with Lenvatinib is the first line treatment for hepatocellular carcinoma (HCC), but their potency is hampered by the low response rate and adverse events. Herein, a targeted therapeutic strategy through the coassembly of Lenvatinib, Adriamycin, Fe3+ ion, and a natural polyphenol (metallo-nanodrugs) is presented by coordination effect for potentiating tumor vascular normalization and systematic chemo-immunotherapy to effectively inhibit the progression of HCC in both orthotopic model and patients-derived organoids. In mice with orthotopic HCC, the obtained metallo-nanodrugs efficiently increase the drug accumulation in orthotopic tumors and can respond to acidic tumor environment. The promotion of tumor vascular normalization by metallo-nanodrugs is observed, which enhances the infiltrating T lymphocytes in tumor, and reinforces the calreticulin-mediated antitumor immunity through alleviating hypoxia, reducing regulatory T cells, and down-regulating PDL1 expression of tumors. The excellent therapeutic efficiency with complete remission of orthotopic tumors (3/6) and long-term survival of mice (4/6, 42 days) are also achieved. Furthermore, the excellent therapeutic effect of metallo-nanodrugs is also validated in 5 patient-derived organoids, and hence can provide a marvelous systemic chemo-immunotherapy strategy for enhancing HCC treatment.

Photosensitizers Dispersed on Nanosized Triterpenoid Matrix with Deaggregation-Enhanced Singlet Oxygen Production.

Aggregation-caused quenching (ACQ) effects of photosensitizers severely cut down the generation of quantum yield of singlet oxygen (1O2) for effective photodynamic therapy (PDT). Herein, we accomplish a deaggregation-enhanced 1O2 production strategy by the noncovalent coordination of a clinically applied triterpenoid oleanolic acid (OA) and hematoporphyrin (Hp) via one-step self-assembly, forming a nanosensitizer OH, in which Hp is interspersed on the surface of the OA matrix in a face-to-face manner. The scattered arrangement of Hp held by the OA matrix decreases the π-π aggregation in Hp, leading to a 3.7-fold boost in the intracellular 1O2 yield and high phototoxicity in vitro and in vivo. Moreover, the biologically active OA enables OH to display excellent cellular uptake efficiency (increase by 36-fold), deep tumor penetration, and synergistic antitumor outcome at a low dose. Thus, this simple strategy paves the way for the green development of efficient photosensitizers.

Similarities and differences between embryonic implantation and CTC invasion: Exploring the roles of abortifacients in cancer metastasis chemoprevention.

Mifepristone (RU486) is a chemical contraceptive marketed in more than 55 countries and used by hundreds of millions of women worldwide. Current studies reported its uses by both genders for a safe and long-term psychotic depression and particularly for traditional cancer chemotherapy. Here, we investigated the multidisciplinary data from recent large epidemiological chemoprevention studies for long-term use of oral contraceptives to reduce cancer risk, and from the unsuccessful clinical trials of mifepristone used as a post-metastatic anticancer drug, and elucidated the similarities and differences in cellular and molecular processes between embryonic implantation to endometrium and adhesion/invasion of circulating tumor cells (CTCs) to vascular endothelium. The deep analyses provide a stronger scientific basis for repurposing abortifacients for safe and effective cancer metastatic chemoprevention. Initiation of such cancer drug development strategy represents a paradigm shift from traditional post-metastasis treatments to novel pre-metastasis chemoprevention.

Synergistic Silencing of Skp2 by siRNA Self-Assembled Nanoparticles as a Therapeutic Strategy for Advanced Prostate Cancer.

Advanced prostate cancer, harboring multiple mutations of tumor suppressor genes, is refractory to conventional therapies. Knockout of the Skp2 gene blocks pRb/p53 doubly deficient prostate cancer in mice, which inspired the authors to develop an approach for delivering siRNA that would efficiently silence Skp2 (siSkp2) in vivo. Here, a facile strategy is reported to directly assemble siSkp2 with the natural compound quercetin (Que) into supramolecular nanoparticles (NPs). This carrier-free siSkp2 delivery system could effectively protect siSkp2 from degradation in serum and enhance its cellular internalization. Furthermore, the siSkp2/Que NPs exhibit synergistic effects in Skp2 silencing, because they can degrade the mRNA and protein of Skp2 simultaneously. Indeed, siSkp2/Que NPs remarkably diminish the Skp2 abundance and further inhibit the proliferation and migration of TMU cells (RB1/TP53/KRAS triple mutations) in vitro. The in vivo results further show that i.v. administration of siSkp2/Que NPs efficiently accumulates in tumor sites and strongly inhibits the growth of TMU tumors in nude mice. Importantly, the siSkp2/Que NPs do not induce any abnormality in the treated mice, which suggests satisfactory biocompatibility. Collectively, this study describes a tractable siRNA self-assembled strategy for Skp2 silencing, which might be a promising nanodrug to cure multitherapy-resistant advanced prostate cancer.

Convenient Tuning of the Elasticity of Self-Assembled Nano-Sized Triterpenoids to Regulate Their Biological Activities.

The impact of the mechanical properties of nanomedicines on their biological functions remains elusive due to the difficulty in tuning the elasticity of the vehicles without changing chemistry. Herein, we report the fabrication of elasticity-tunable self-assembled oleanolic acid (OA) nanoconstructs in an antiparallel zigzag manner and develop rigid nanoparticles (OA-NP) and flexible nanogels (OA-NG) as model systems to decipher the elasticity-biofunction relationship. OA-NG demonstrate less endocytosis and enhanced lysosome escape with deformation compared to OA-NP. Further in vitro and in vivo experiments show the active permeation of OA-NG into the interior of tumor with enhanced antitumor efficacy accompanied by decreased collagen production and eight- to tenfold immune cell infiltration. This study not only presents a facile and green strategy to develop flexible OA-NG for effective cancer treatment but also uncovers the crucial role of elasticity in regulating biological activity, which may provide reference for precise design of efficient nanomedicines.

Discovery of novel tubulin inhibitors targeting taxanes site by virtual screening, molecular dynamic simulation, and biological evaluation.

Microtubules play crucial role in process of mitosis and cell proliferation, which have been considered as attractive drug targets for anticancer therapy. The aim of this study was to discover novel and chemically diverse tubulin inhibitors for treatment of cancer. In this investigation, the multilayer virtual screening methods, including common feature pharmacophore model, structure-based pharmacophore model and molecular docking, were developed to screen BioDiversity database with 30,000 compounds. A total of 102 compounds were obtained by the virtual screening, and further filtered by diverse chemical clusters with desired properties and PAINS analysis. Finally, 50 compounds were selected and submitted to the biological evaluation. Among these hits, hits 8 and 30 with novel scaffolds displayed stronger antiproliferative activity on four human tumor cells including Hela, A549, MCF-7, and HepG2. Moreover, the two hits were subsequently submitted to molecular dynamic simulations of 90 ns with the aim of exploring the stability of ligand-protein interactions into the binding pocket, and further probing the mechanism of the interaction between tubulin and hits. The molecular dynamic simulation results revealed there had stronger interactions between tubulin and hits in equilibrium state. Therefore, the hits 8 and 30 have been well characterized as lead compounds for developing new tubulin inhibitors with potential anticancer activity.

Why do we lack a specific magic anti-COVID-19 drug? Analyses and solutions.

The Coronavirus 2019 (COVID-19) pandemic represents the greatest worldwide public health crisis of recent times. The lack of proven effective therapies means that COVID-19 rages relatively unchecked. Current anti-COVID-19 pharmacotherapies are drugs originally designed for other diseases, and administered orally or intravascularly. Thus, they can have various adverse effects. A specific anti-Coronavirus drug should not only target the virus per se, but also treat the related respiratory and cardiovascular symptoms. Here, we examine the advantages and disadvantages of current anti-COVID-19 pharmacotherapies, and analyze the reasons why in the era of big data we have not yet established specific coronavirus therapies and related technical bottlenecks. Finally, we present our design of a novel nebulized S-nitrosocaptopril that is under development for targeting both coronaviruses and their related symptoms.

Author Correction: Achyranthes bidentata polysaccharide can safely prevent NSCLC metastasis via targeting EGFR and EMT.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Developing novel computational prediction models for assessing chemical-induced neurotoxicity using naïve Bayes classifier technique.

Development of reliable and efficient alternative in vivo methods for evaluation of the chemicals with potential neurotoxicity is an urgent need in the early stages of drug design. In this investigation, the computational prediction models for drug-induced neurotoxicity were developed by using the classical naïve Bayes classifier. Eight molecular properties closely relevant to neurotoxicity were selected. Then, 110 classification models were developed with using the eight important molecular descriptors and 10 types of fingerprints with 11 different maximum diameters. Among these 110 prediction models, the prediction model (NB-03) based on eight molecular descriptors combined with ECFP_10 fingerprints showed the best prediction performance, which gave 90.5% overall prediction accuracy for the training set and 82.1% concordance for the external test set. In addition, compared to naïve Bayes classifier, the recursive partitioning classifier displayed worse predictive performance for neurotoxicity. Therefore, the established NB-03 prediction model can be used as a reliable virtual screening tool to predict neurotoxicity in the early stages of drug design. Moreover, some structure alerts for characterizing neurotoxicity were identified in this research, which could give an important guidance for the chemists in structural modification and optimization to reduce the chemicals with potential neurotoxicity.

WDR74 modulates melanoma tumorigenesis and metastasis through the RPL5-MDM2-p53 pathway.

The key molecules and underlying mechanisms of melanoma metastasis remain poorly understood. Using isobaric tag for relative and absolute quantitation (iTRAQ) proteomic screening, probing of patients' samples, functional verification, and mechanistic validation, we identified the important role of the WD repeat-containing protein 74 (WDR74) in melanoma progression and metastasis. Through gain- and loss-of-function approaches, WDR74 was found to promote cell proliferation, apoptosis resistance, and aggressive behavior in vitro. Moreover, WDR74 contributed to melanoma growth and metastasis in vivo. Mechanistically, WDR74 modulates RPL5 protein levels and consequently regulates MDM2 and insulates the ubiquitination degradation of p53 by MDM2. Our study is the first to reveal the oncogenic role of WDR74 in melanoma progression and the regulatory effect of WDR74 on the RPL5-MDM2-p53 pathway. Collectively, WDR74 can serve as a candidate target for the prevention and treatment of melanoma in the clinic.

WDR74 induces nuclear ß-catenin accumulation and activates Wnt-responsive genes to promote lung cancer growth and metastasis.

Lung cancer has been notorious for its lack of advance in clinical therapy, urging for effective therapeutic targets. WD repeat-containing protein 74 (WDR74) has previously been implicated in tumorigenesis, but its mechanistic functions remain not well understood. Herein, WDR74 expression was observed to be increased upon lung cancer progression from healthy normal tissues to the primary cancer and further to the metastatic cancer. Through gain- and loss-of-function approaches, we found that WDR74 regulated lung cancer cell proliferation, cell cycle progression, chemoresistance and cell aggressiveness in vitro. Moreover, a xenograft mouse model disclosed that WDR74 knockout inhibited lung cancer growth and metastasis, whereas WDR74 overexpression reciprocally enhanced these characteristics. Mechanistically, WDR74 promoted nuclear ß-catenin accumulation and drove downstream Wnt-responsive genes, thus revealing that WDR74 activated the Wnt/ß-catenin signaling pathway. Collectively, WDR74 inducing nuclear ß-catenin accumulation and driving the downstream Wnt-responsive genes expression facilitates lung cancer growth and metastasis. WDR74 can serve as a candidate target for the prevention and treatment of lung cancer in clinic.

A novel UPLC/MS/MS method for rapid determination of murrayone in rat plasma and its pharmacokinetics.

Murraya paniculata (L.) is a traditional Chinese medicine (TCM) wildly grown in southeast China, and used for abortion in folk. Murrayone, a coumarin-containing compound extracted from M. paniculata, is the most bioactive substance in this species and is being developed as a novel cancer metastasis chemopreventive agent based on its unique pharmacological properties. In the present study, a novel rapid and sensitive method for quantitative analysis of murrayone in rat plasma and for determining its pharmacokinetics in rats was developed and validated using UPLC/MS/MS. Plasma samples were subjected to protein precipitation and then directly analyzed by UPLC/MS/MS. Both murrayone and coumarin as an internal standard (I.S.) were carried on a C18 column with a gradient mobile phase consisting of acetonitrile and water at a flow rate of 0.3 mL/min. Several gradient elution procedures were evaluated to achieve effective chromatography resolution and a sensitive response to murrayone and the I.S.. Mass spectrometry was carried out using a triple-quadrupole system via positive electrospray ionization and multiple reaction monitoring (MRM). Good linearity (r 2 = 0.9987) was achieved over a linear range of 4.0-1600 ng/mL with a lower limit of quantitation (LLOQ) of 4.0 ng/mL for murrayone. The inter- and intraday accuracy and precision ranged from 90.0 to 99.7% and 1.1 to 12.3% at four quality control concentrations, respectively. The average absolute recoveries of murrayone and the I.S. were determined to be 85.9-92.4% and 86.5-90.7%, respectively, at 10.0, 80.0, and 800 ng/mL. Murrayone was stable under a variety of storage and processing conditions that may be routinely encountered in laboratories based on all the stability tests. This newly developed method was successfully applied to the pharmacokinetic study of murrayone in rats for the first time, and the current assay methodology could provide important insights into potential therapeutics and facilitate further pharmacodynamic explorations of murrayone.

A prediction model of drug-induced ototoxicity developed by an optimal support vector machine (SVM) method.

Drug-induced ototoxicity, as a toxic side effect, is an important issue needed to be considered in drug discovery. Nevertheless, current experimental methods used to evaluate drug-induced ototoxicity are often time-consuming and expensive, indicating that they are not suitable for a large-scale evaluation of drug-induced ototoxicity in the early stage of drug discovery. We thus, in this investigation, established an effective computational prediction model of drug-induced ototoxicity using an optimal support vector machine (SVM) method, GA-CG-SVM. Three GA-CG-SVM models were developed based on three training sets containing agents bearing different risk levels of drug-induced ototoxicity. For comparison, models based on naïve Bayesian (NB) and recursive partitioning (RP) methods were also used on the same training sets. Among all the prediction models, the GA-CG-SVM model II showed the best performance, which offered prediction accuracies of 85.33% and 83.05% for two independent test sets, respectively. Overall, the good performance of the GA-CG-SVM model II indicates that it could be used for the prediction of drug-induced ototoxicity in the early stage of drug discovery.

Identification of novel anaplastic lymphoma kinase (ALK) inhibitors using a common feature pharmacophore model derived from known ligands crystallized with ALK.

In this investigation, a common feature pharmacophore model of anaplastic lymphoma kinase inhibitors was developed based on several known anaplastic lymphoma kinase inhibitors that were co-crystallized with anaplastic lymphoma kinase. The established pharmacophore model Hypo1 was carefully validated and then adopted to screen two in silico chemical databases, Specs (202 408 compounds) and Enamine (1 105 894 compounds), for retrieving novel anaplastic lymphoma kinase inhibitors. The hit compounds were further filtered using a fast bumping-check tool and molecular docking. Finally, 25 compounds were selected and purchased from market. The bioactivity of these compounds was firstly measured at the cellular level against a typical anaplastic lymphoma kinase mutant-driven cancer cell line, Karpas299. And six of them showed a good anti-viability activity. The kinase inhibitory potency against the recombinant human anaplastic lymphoma kinase kinase was tested to the most active compound at the cellular level, T0508-5181 (from Specs), which gave a half maximal inhibitory concentration (IC(50)) of 5.3 µM.

Identification of CK2 inhibitors with new scaffolds by a hybrid virtual screening approach based on Bayesian model; pharmacophore hypothesis and molecular docking.

Protein kinase casein kinase 2 (CK2), a member of the serine/threonine kinase family, has been established as one of the most attractive targets for molecularly targeted cancer therapy. The discovery of CK2 inhibitors has thus attracted much attention in recent years. In this investigation, a hybrid virtual screening approach based on Bayesian classification model, pharmacophore hypothesis and molecular docking was proposed and employed to identify CK2 inhibitors. We first established a naïve Bayes classification model of CK2 inhibitors/non-inhibitors and pharmacophore hypotheses of CK2 inhibitors. The docking parameters and scoring functions were also optimized in advance. The three virtual screening methods were sequentially used to screen two large chemical libraries, Specs and Enamine, for retrieving new CK2 inhibitors. Finally 30 compounds were selected from the final hits for in vitro CK2 kinase inhibitory assays. Five compounds with completely novel scaffolds showed a good inhibitory potency against CK2, which have good potentials for a future hit-to-lead optimization.

Combined SVM-based and docking-based virtual screening for retrieving novel inhibitors of c-Met.

Aberrant c-Met activation has been demonstrated to be implicated in tumorigenesis and anti-cancer drug resistance. Discovery of c-Met inhibitors has attracted much attention in recent years. In this study, a support vector machine (SVM) classification model that discriminates c-Met inhibitors and non-inhibitors was first developed. Evaluation through screening a test set indicates that combined SVM-based and docking-based virtual screening (SB/DB-VS) considerably increases hit rate and enrichment factor compared with the individual methods. Thus the combined SB/DB-VS approach was adopted to screen PubChem, Specs, and Enamine for c-Met inhibitors. 75 compounds were selected for in vitro assays. Eight compounds display a good inhibitory potency against c-Met. Five of them are found to have novel scaffolds, implying a good potential for further chemical modification.

Pharmacophore modeling and hybrid virtual screening for the discovery of novel IκB kinase 2 (IKK2) inhibitors.

IKK2 (IκB kinase 2) inhibitors have been identified as potential drug candidates in the treatment of various immune/inflammatory disorders as well as cancer. So far more than one hundred small molecule inhibitors against IKK2 have been reported publicly. In this investigation, pharmacophore modeling was carried out to clarify the essential structure-activity relationship for the known IKK2 inhibitors. One of the established pharmacophore hypotheses, namely Hypo8, which has the best prediction ability to an external test data set, was suggested as a template for virtual screening. Evaluation of the performances of Hypo8 and a hybrid method (Hypo81docking) in virtual screening indicated that the use of the hybrid virtual screening considerably increased the hit rate and enrichment factor. The hybrid method was therefore adopted for screening several commercially available chemical databases, including Specs, NCI, Maybridge and Chinese Nature Product Database (CNPD), for novel potent IKK2 inhibitors. The hit compounds were subsequently subjected to filtering by Lipinski's rule of five. Finally some of the final hit compounds were selected and suggested for further experimental investigations.