Current Medicinal Chemistry - Online First

Lung cancer (LC) is the second most lethal cancer and efficient treatments are missing. Our understanding of the underlying pathogenic mechanisms remains limited. Oridonin is a compound extracted from the Chinese herb Rabdosia rubescens with anticancer properties. Nevertheless, its effects on LC and the underlying mechanisms remain unknown.

In the current research, A549 and Hcc1833 cells were treated with different doses of oridonin, and cell proliferation and migration were detected using CCK8, EdU, Transwell, and wound healing assays. A subcutaneous tumor and caudal vein metastasis model was generated to verify the inhibitory effects of oridonin on Hcc1833 tumor growth and metastasis in vivo. Proteomics analyses then were performed to examine the regulatory mechanism. LiP-SMap combined with microscale thermophoresis and molecular docking analyses were used to validate the relationship between oridonin and S100A11.

Data showed that oridonin suppressed cell proliferation and migration depending on dose and suppressed tumor growth and invasion. LiP-SMap and molecular docking analyses confirmed that oridonin interacted with the Asn-53 residue of S100A11, which inhibited the activation of oridonin. S100A11 overexpression reversed the inhibitory effects of oridonin on cell proliferation and migration.

In conclusion, the data indicate that oridonin suppresses LC malignant progression by targeting S100A11.

Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder, but no drugs can cure this disease. Chalcones possess good antioxidant activity, anti-neuroinflammatory activity, neuroprotective effects, inhibitory effects on Aβ aggregation, and Aβ disaggregation ability. Therefore, chalcones are ideal lead compounds, and the discovery of novel anti-AD agent-based chalcones is necessary.

Hydroxy groups and aryl benzyl ether groups were introduced into chalcone scaffolds to obtain a series of 2-hydroxyl-4-benzyloxy chalcone derivatives. These derivatives were further synthesized, biologically evaluated, and docked.

Most target derivatives exhibited good anti-AD activities. In particular, compound 11d had excellent inhibitory effects on self-induced Aβ1-42 aggregation (90.8% inhibition rate at 25 μM) and Cu²⁺ induced Aβ1-42 aggregation (93.4% inhibition rate at 25 μM). In addition, it also exhibited good Aβ1-42 fibril disaggregation ability (64.7% at 25 μM), significant antioxidative activity (ORAC = 2.03 Trolox equivalent), moderate MAO-B inhibition (IC50 = 4.81 μM), selective metal chelation, appropriate BBB permeation, and dramatic anti-neuroinflammatory ability. In addition, compound 11d relieved AD symptoms and protected hippocampal neurons in vivo.

Compound 11d is a promising multifunctional anti-Aβ agent.

A series of benzylidene derivatives of fenobam and its thio analogues (1-22) have been evaluated for their cytotoxicity against breast cancer (MCF-7, MDA-MB-231), ovarian cancer (A2780, SKOV-3) and cervical cancer (HELA) cell lines.

These compounds (1-22) exhibited 72-83% inhibition of Erk activity against the ovarian cancer cell line (A2780). Compounds 3 and 20 showed the highest DNA damage effect in Comet Assay against the A2780 cancer cell line as compared to the other tested analogues (4, 8, 11, 12, and 13) by using % Tail DNA and OTM. Compounds 3, 4, and 11 showed significant activities and selectivity towards COX-2 with 78%, 97%, and 89% inhibition, as compared to 17%, 57%, and 26% inhibition against COX-1 isoenzyme, respectively.

Interestingly, molecular docking scores were also in very good agreement with the experimental results regarding discriminating the selectivity index of the tested compounds against COX-1 & COX-2 enzymes. Further molecular dynamics (MD) simulation study revealed that the most selective compound, 13, binds with the COX-2 enzyme in a similar fashion to that of Rofecoxib, which was further supported by their MD-based free binding energies (MM-GBSA) of -49.76 ± 4.27 kcal/mol, and -44.84 ±3.78 kcal/mol, respectively.

Moreover, in silico ADMET predictions showed adequate properties for these compounds, making them promising leads worthy of further optimization.

Globally, one of the main causes of cancer-related mortality is Colon Adenocarcinoma (COAD). In this study, a new special Immune Cell Functions (ICF) risk model was constructed using single-cell and bulk RNA sequencing data to develop a new understanding and clinical applications for COAD.

The immune function gene sets were downloaded from a literature reference, and the COAD single-cell dataset GSE146771 was downloaded from the Tumour Immune Single Cell Hub database. Using Lasso analysis, a multiple gene signature was made from the enrichment scores of immune function gene sets that were enriched in different ways. Robust validation of the signature was then performed in multiple independent cohorts. After that, we built the model using a 10-fold cross-test and evaluated its independence for clinical usage using a nomogram. We also investigated the connection between signature and immune function, genetic variation, immunotherapy, and the cancer immunological microenvironment. Lastly, we used qPCR and immunohistochemistry to examine the expression of the unreported model genes. To find the regulatory functions of unreported model genes, an EdU assay was employed.

First, 20 differentially enriched immune function gene sets were identified. Ten genes can be used as a risk profile to assess the prognosis of colon cancer, according to Lasso regression analysis. Signature performance was stable in both the training cohort and two independent GEO external cohorts, and risk scores were confirmed as independent prognostic factors. At the same time, our risk model continued to be highly predictive across various clinical clusters and clinical characteristics, such as immune checkpoints, tumour genome mutations, and chemotherapeutic drug resistance. Patients in the low-risk group have exhibited a higher chance of benefiting from immunotherapy, according to immunotherapy response research. qPCR and immunohistochemistry analysis have revealed SIRP5 expression as high in COAD tissues, while CMC1 and ASAH1 expression has been found to be low. According to the findings of the functional experiment, SIRP5, CMC1, and ASAH1 may control the ability of CRC cells to proliferate.

In this study, using scRNA-seq and bulk RNA-seq data, we created a risk model to predict the prognosis and effectiveness of immunotherapy in patients with COAD. In addition, we have discovered three model genes (SIRP5, CMC1, and ASAH1) that have not been reported before. These genes have the potential to be novel therapeutic targets in Colorectal Cancer (CRC). These findings suggest that this model could be used to evaluate the prognostic risk and identify potential targets for COAD patient treatment.

The disability and mortality related to Parkinson's disease (PD), a neurodegenerative disease, are increasing globally at a faster rate than other neurological disorders. With no permanent cure for PD, there is an urgent need to develop novel and effective anti-PD drugs.

Targeting monoamine oxidases (MAO), which catalyze the breakdown of neurotransmitters, is one way to treat neurodegenerative diseases. In this context, an initial molecular docking of twenty designed sulfonyl derivatives of benzimidazole against monoamine oxidase B (MAO-B) associated with PD was conducted using AutoDock Vina.

The results were compared with those of the conventional inhibitors, selegiline and rasagiline. Based on the docking score, the in-silico pharmacokinetic properties (ADME), drug-likeness, and toxicity profiles of the newly synthesized molecules were examined using SwissADME, PreADMET, ProTox-3.0, vNN, and ADMETlab web tools. Then, twelve potential derivatives were synthesized and characterized by IR, ¹H-NMR, ¹³C-NMR, ¹⁹F-NMR (for some compounds), and mass spectrometry. Derivatives 2cj and 1bj were the two molecules having the best binding affinity of -11.9 and -11.8 kcal/mol, respectively, against MAO-B, exhibiting a higher binding affinity compared to that of some commercially available drugs. A 50 ns MD simulation run was performed to observe the stability of the top two docked complexes, MAO-B-2cj and MAO-B-1bj, in order to further validate the efficacy of those two substances. Moreover, the MM-PBSA method was used to calculate the final, binding free energy of the simulated (MAO-B-2cj) complex.

This study indicates that the binding affinity of most of the hits was superior to that of known MAO inhibitors; therefore, these newly synthesized benzimidazole derivatives may be developed into essential drug candidates for the treatment of PD.