Chalcones are secondary metabolites belonging to the flavonoid (C₆-C₃-C₆ system) family that are ubiquitous in edible and medicinal plants, and they are bioprecursors of plant flavonoids. Chalcones and their natural derivatives are important intermediates of the flavonoid biosynthetic pathway. Plants containing chalcones have been used in traditional medicines since antiquity. Chalcones are basically α,β-unsaturated ketones that exert great diversity in pharmacological activities such as antioxidant, anticancer, antimicrobial, antiviral, antitubercular, antiplasmodial, antileishmanial, immunosuppressive, anti-inflammatory, and so on. This review provides an insight into the chemistry, biosynthesis, and occurrence of chalcones from natural sources, particularly dietary and medicinal plants. Furthermore, the pharmacological, pharmacokinetics, and toxicological aspects of naturally occurring chalcone derivatives are also discussed herein. In view of having tremendous pharmacological potential, chalcone scaffolds/chalcone derivatives and bioflavonoids after subtle chemical modification could serve as a reliable platform for natural products-based drug discovery toward promising drug lead molecules/drug candidates.

Background: Cancer is a global health challenge, it impacts the quality of life and its treatment is associated with several side effects. Resistance of the cancer cells to the existing drugs has led to search for novel anticancer agents. Pyrimidine, a privileged scaffold, is part of living organisms and plays vital role in various biological procedures as well as in cancer pathogenesis. Due to resemblance in structure with the nucleotide base pair of DNA and RNA, it is recognized as valuable compound in the treatment of cancer. Main text: Many novel pyrimidine derivatives have been designed and developed for their anticancer activity in the last few years. The present review aims to focus on the structure activity relationship (SAR) of pyrimidine derivatives as anticancer agent from the last decade. Conclusion: This review intends to assist in the development of more potent and efficacious anticancer drugs with pyrimidine scaffold. Graphical

Background: Cancer is, at present, among the leading causes of morbidity globally. Despite advances in treatment regimens for cancer, patients suffer from poor prognoses. In this context, the availability of vast natural resources seems to alleviate the shortcomings of cancer chemotherapy. The last decade has seen a breakthrough in the investigations related to the anticancer potential of dietary phytoconstituents. Interestingly, a handsome number of bioactive principles, ranging from phenolic acids, phenylpropanoids, flavonoids, stilbenes, and terpenoids to organosulphur compounds have been screened for their anticancer properties. Among the phenylpropanoids currently under clinical studies for anticancer activity, eugenol is a promising candidate. Eugenol is effective against cancers like breast, cervical, lung, prostate, melanomas, leukemias, osteosarcomas, gliomas, etc., as evident from preclinical investigations. Objective: The review aims to focus on cellular and molecular mechanisms of eugenol for cancer prevention and therapy. Methods: Based on predetermined criteria, various scholarly repositories, including PubMed, Scopus, and Science Direct were analyzed for anticancer activities of eugenol. Results: Different biochemical investigations reveal eugenol inducing cytotoxicity, inhibiting phases of the cell cycles, programmed cell death, and auto-phagocytosis in studied cancer lines; thus, portraying eugenol as a promising anticancer molecule. A survey of current literature has unveiled the molecular mechanisms intervened by eugenol in exercising its anticancer role. Conclusion: Based on the critical analysis of the literature, eugenol exhibits vivid signaling pathways to combat cancers of different origins. The reports also depict the advancement of novel nano-drug delivery approaches upgrading the therapeutic profile of eugenol. Therefore, eugenol nanoformulations may have enormous potential for both the treatment and prevention of cancer.

One of the most well-known anti-targets defining medication cardiotoxicity is the voltage-dependent hERG K + channel, which is well-known for its crucial involvement in cardiac action potential repolarization. Torsades de Pointes, QT prolongation, and sudden death are all caused by hERG (the human Ether-à-go-go-Related Gene) inhibition. There is great interest in creating predictive computational (in silico) tools to identify and weed out potential hERG blockers early in the drug discovery process because testing for hERG liability and the traditional experimental screening are complicated, expensive and time-consuming. This study used 2D descriptors of a large curated dataset of 6766 compounds and machine learning approaches to build robust descriptor-based QSAR and predictive classification models for KCNH2 liability. Decision Tree, Random Forest, Logistic Regression, Ada Boosting, kNN, SVM, Naïve Bayes, neural network and stochastic gradient classification classifier algorithms were used to build classification models. If a compound’s IC₅₀ value was between 10 μM and less, it was classified as a blocker (hERG-positive), and if it was more, it was classified as a non-blocker (hERG-negative). Matthew’s correlation coefficient formula and F1score were applied to compare and track the developed models’ performance. Molecular docking and dynamics studies were performed to understand the cardiotoxicity relating to the hERG–gene. The hERG residues interacting after 100 ns are LEU:697, THR:708, PHE:656, HIS:674, HIS:703, TRP:705 and ASN:709 and the hERG–ligand-16 complex trajectory showed stable behaviour with lesser fluctuations in the entire simulation of 200 ns. Communicated by Ramaswamy H. Sarma