Bipiperidinyl Derivatives of Cannabidiol Enhance Its Antiproliferative Effects in Melanoma Cells

Cannabis and its major cannabinoid cannabidiol (CBD) are reported to exhibit anticancer activity against skin tumors. However, the cytotoxic effects of other minor cannabinoids and synthetic CBD derivatives in melanoma are not fully elucidated. Herein, the antiproliferative activity of a panel of phytocannabinoids was screened against murine (B16F10) and human (A375) melanoma cells. CBD was the most cytotoxic natural cannabinoid with respective IC50 of 28.6 and 51.6 μM. Further assessment of the cytotoxicity of synthetic CBD derivatives in B16F10 cells identified two bipiperidinyl group-bearing derivatives (22 and 34) with enhanced cytotoxicity (IC50 = 3.1 and 8.5 μM, respectively). Furthermore, several cell death assays including flow cytometric (for apoptosis and ferroptosis) and lactate dehydrogenase (for pyroptosis) assays were used to characterize the antiproliferative activity of CBD and its bipiperidinyl derivatives. The augmented cytotoxicity of 22 and 34 in B16F10 cells was attributed to their capacity to promote apoptosis (as evidenced by increased apoptotic population). Taken together, this study supports the notion that CBD and its derivatives are promising lead compounds for cannabinoid-based interventions for melanoma management.

Indispensable role of microbes in anticancer drugs and discovery trends

Recent years have seen an increased focus on the advancement of naturally derived products for the treatment of cancer. Since the beginning of recorded history, nature has provided a variety of medicinal agents, and an overwhelming number of drugs that we have today are derived from natural sources. Such natural agents are prominently used to treat several diseases such as diabetes, malaria, Alzheimer's, pulmonary disorders, etc. with cancer being the highlight of this review. Due to the rapid development of resistance to chemotherapeutic drugs, the hunt for effective novel drugs is still a paramount concern in cancer treatment. Moreover, many chemotherapy drugs typically have high toxicity and adverse side effects, which necessitates the need to develop anti-tumor drugs that can be employed to treat deadly tumors with fewer negative effects on health and better efficacy. Isolation of several chemotherapeutic drugs has been conducted from a wide range of natural sources which include plants, microbes, fungi, and marine microorganisms. Considering the trends of previous decades, microbial diversity has grown to play a significant role in the formulation of pharmaceuticals and drugs, especially antibiotics and anti-cancer medications. Microbe-derived antitumor antibiotics such as anthracycline, epothilones, bleomycin, actinomycin, and staurosporine are amongst the widely used cancer chemotherapeutic agents. This review deals majorly with microbe-derived anticancer drugs taking into account their derivatives, mechanism of action, isolation procedures, limitations, and tumors targeted by them. This article also reports the phase of clinical study these drugs are undergoing. Moreover, it intends to portray the indispensable part that these microbes have been playing since time immemorial in the odyssey of chemotherapeutic agents. KEY POINTS: • Microbial diversity contributes heavily towards the formulation of anticancer drugs. • Polypeptides, carbohydrates, and alkaloids are prevalent microbe-based drug classes. • Microbe-derived anticancer agents target various sarcomas, carcinomas, and lymphomas.

Water-Soluble Heliomycin Derivatives to Target i-Motif DNA

Heliomycin (also known as resistomycin) is an antibiotic with a broad spectrum of biological activities. However, low aqueous solubility and poor knowledge of its chemical properties have limited the development of this natural product. Here, we present an original scheme for the introduction of aminoalkylamine residues at positions 3, 5, and 7 of heliomycin and, using this, have prepared a series of novel water-soluble derivatives. The addition of side chains to the heliomycin scaffold significantly improves their interaction with different DNA secondary structures. One derivative, 7-deoxy-7-(2-aminoethyl)amino-10-O-methylheliomycin (8e), demonstrated affinity, stabilization potential, and good selectivity toward i-motif-forming DNA sequences over the duplex and G-quadruplex. Heliomycin derivatives therefore represent promising molecular scaffolds for further development as DNA-i-motif interacting ligands and potential chemotherapeutic agents.

DeltaMS: a tool to track isotopologues in GC- and LC-MS data

INTRODUCTION

Stable isotopic labeling experiments are powerful tools to study metabolic pathways, to follow tracers and fluxes in biotic and abiotic transformations and to elucidate molecules involved in metal complexing.

OBJECTIVE

To introduce a software tool for the identification of isotopologues from mass spectrometry data.

METHODS

DeltaMS relies on XCMS peak detection and X¹³CMS isotopologue grouping and then analyses data for specific isotope ratios and the relative error of these ratios. It provides pipelines for recognition of isotope patterns in three experiment types commonly used in isotopic labeling studies: (1) search for isotope signatures with a specific mass shift and intensity ratio in one sample set, (2) analyze two sample sets for a specific mass shift and, optionally, the isotope ratio, whereby one sample set is isotope-labeled, and one is not, (3) analyze isotope-guided perturbation experiments with a setup described in X¹³CMS.

RESULTS

To illustrate the versatility of DeltaMS, we analyze data sets from case-studies that commonly pose challenges in evaluation of natural isotopes or isotopic signatures in labeling experiment. In these examples, the untargeted detection of sulfur, bromine and artificial metal isotopic patterns is enabled by the automated search for specific isotopes or isotope signatures.

CONCLUSION

DeltaMS provides a platform for the identification of (pre-defined) isotopologues in MS data from single samples or comparative metabolomics data sets.