Exploring the 1,3-benzoxazine chemotype for cannabinoid receptor 2 as a promising anti-cancer therapeutic

MzDOCK: A free ready-to-use GUI-based pipeline for molecular docking simulations

Molecular docking is by far the most preferred approach in structure-based drug design for its effectiveness to predict the scoring and posing of a given bioactive small molecule into the binding site of its pharmacological target. Herein, we present MzDOCK, a new GUI-based pipeline for Windows operating system, designed with the intent of making molecular docking easier to use and higher reproducible even for inexperienced people. By harmonic integration of python and batch scripts, which employs various open source packages such as Smina (docking engine), OpenBabel (file conversion) and PLIP (analysis), MzDOCK includes many practical options such as: binding site configuration based on co-crystallized ligands; generation of enantiomers from SMILES input; application of different force fields (MMFF94, MMFF94s, UFF, GAFF, Ghemical) for energy minimization; retention of selectable ions and cofactors; sidechain flexibility of selectable binding site residues; multiple input file format (SMILES, PDB, SDF, Mol2, Mol); generation of reports and of pictures for interactive visualization. Users can download for free MzDOCK at the following link: https://github.com/Muzatheking12/MzDOCK.

New substituted benzoxazine derivatives as potent inducers of membrane permeability and cell death

The search for new agents targeting different forms of cell death is an important research focus for developing new and potent antitumor therapies. As a contribution to this endeavor, we have designed and synthesized a series of new substituted 3,4-dihydro-2H-1,4-benzoxazine derivatives. These compounds have been evaluated for their efficacy against MCF-7 breast cancer and HCT-116 colon cancer cell lines. Overall, substituting this heterocycle led to improved antiproliferative activity compared to the unsubstituted derivative 1. The most active compounds, 2b and 4b, showed IC50 values of 2.27 and 3.26 μM against MCF-7 cells and 4.44 and 7.63 μM against HCT-116 cells, respectively. To investigate the mechanism of action of the target compounds, the inhibition profile of 8 kinases involved in cell signaling was studied highlighting residual activity on HER2 and JNK1 kinases. 2b and 4b showed a consistent binding mode to both receptor kinases, establishing significant interactions with known and catalytically important domains and residues. Compounds 2b and 4b exhibit potent cytotoxic activity by disrupting cell membrane permeability, likely triggering both inflammatory and non-inflammatory cell death mechanisms. This dual capability increases their versatility in the treatment of different stages or types of tumors, providing greater flexibility in clinical applications.

Cannabinoids and triple-negative breast cancer treatment

Triple-negative breast cancer (TNBC) accounts for about 10-20% of all breast cancer cases and is associated with an unfavorable prognosis. Until recently, treatment options for TNBC were limited to chemotherapy. A new successful systemic treatment is immunotherapy with immune checkpoint inhibitors, but new tumor-specific biomarkers are needed to improve patient outcomes. Cannabinoids show antitumor activity in most preclinical studies in TNBC models and do not appear to have adverse effects on chemotherapy. Clinical data are needed to evaluate efficacy and safety in humans. Importantly, the endocannabinoid system is linked to the immune system and immunosuppression. Therefore, cannabinoid receptors could be a potential biomarker for immune checkpoint inhibitor therapy or a novel mechanism to reverse resistance to immunotherapy. In this article, we provide an overview of the currently available information on how cannabinoids may influence standard therapy in TNBC.

Recent Advances in the Discovery of Novel Drugs on Natural Molecules

Natural products (NPs) are always a promising source of novel drugs for tackling unsolved diseases [...].

Small Molecules for the Treatment of Long-COVID-Related Vascular Damage and Abnormal Blood Clotting: A Patent-Based Appraisal

People affected by COVID-19 are exposed to, among others, abnormal clotting and endothelial dysfunction, which may result in deep vein thrombosis, cerebrovascular disorders, and ischemic and non-ischemic heart diseases, to mention a few. Treatments for COVID-19 include antiplatelet (e.g., aspirin, clopidogrel) and anticoagulant agents, but their impact on morbidity and mortality has not been proven. In addition, due to viremia-associated interconnected prothrombotic and proinflammatory events, anti-inflammatory drugs have also been investigated for their ability to mitigate against immune dysregulation due to the cytokine storm. By retrieving patent literature published in the last two years, small molecules patented for long-COVID-related blood clotting and hematological complications are herein examined, along with supporting evidence from preclinical and clinical studies. An overview of the main features and therapeutic potentials of small molecules is provided for the thromboxane receptor antagonist ramatroban, the pan-caspase inhibitor emricasan, and the sodium-hydrogen antiporter 1 (NHE-1) inhibitor rimeporide, as well as natural polyphenolic compounds.

Synthesis of Benzoxazines by Heterogeneous Multicomponent Biochemo Multienzymes Cascade Reaction

This work describes the possibility to combine multicomponent chemistry and multienzymes cascade transformations in a unique reactive framework to yield highly functionalized 1,4-benzoxazines under favorable heterogeneous conditions. The synthetic scheme involved the generation in situ of electrophilic reactive quinone intermediates of tyrosol esters catalyzed by lipase M and tyrosinase followed by nucleophilic 1,6-Michael addition of selected α-amino acid methyl esters, and successive intramolecular lactonization and aromatization processes. The immobilization of the multienzymes cascade on electroactive lignin nanoparticles improved the sustainability and recyclability of the overall system.

CIRCE: Web-Based Platform for the Prediction of Cannabinoid Receptor Ligands Using Explainable Machine Learning

The endocannabinoid system, which includes cannabinoid receptor 1 and 2 subtypes (CB1R and CB2R, respectively), is responsible for the onset of various pathologies including neurodegeneration, cancer, neuropathic and inflammatory pain, obesity, and inflammatory bowel disease. Given the high similarity of CB1R and CB2R, generating subtype-selective ligands is still an open challenge. In this work, the Cannabinoid Iterative Revaluation for Classification and Explanation (CIRCE) compound prediction platform has been generated based on explainable machine learning to support the design of selective CB1R and CB2R ligands. Multilayer classifiers were combined with Shapley value analysis to facilitate explainable predictions. In test calculations, CIRCE predictions reached ∼80% accuracy and structural features determining ligand predictions were rationalized. CIRCE was designed as a web-based prediction platform that is made freely available as a part of our study.