Current Discovery Progress of Some Emerging Anti-infective Chalcones: Highlights from 2016 to 2017.

The anti-infective potentials of the natural products are very well known for centuries and are a part of traditional healing. The foremost therapeutic classes include flavones, isoflavones, flavonols, flavanones, flavanols, proanthocyanidins, anthocyanidins, chalcones, and aurones. The chalcone or 1,3-diphenyl-2E-propene-1-one represents the class of natural products which are comprised of benzylideneacetophenone function; i.e. two aromatic moieties linked together by an α, ß-unsaturated carbonyl bridge comprising three-carbons. At present, chalcone is one of the privileged scaffolds that can be synthesized in the laboratory to derive different pharmacologically active compounds. This article is the continued form of the previously published work on anti-infective perspectives of chalcones (highlighted till 2015). The current work emphasizes on the discovery process of the chalcone in the period of 2016 to 2017 on malaria, trypanosomiasis, leishmaniasis, filaria, tuberculosis, netamodes, Human Immunodeficiency Virus (HIV), Tobacco Mosaic Virus (TMV), Severe Acute Respiratory Syndrome (SARS), and miscellaneous conditions. This review comprehensively focuses on the latest progress related with the anti-infective chalcones. The content includes the crucial structural features of chalcone scaffold including structure-activity relationship(s) along with their plausible mechanism of action(s) from the duration Jan 2016 to Dec 2017. This literature will be of prime interest to medicinal chemists in getting ideas and concepts for better rational development of potential anti-infective inhibitors.

Monte Carlo based modelling approach for designing and predicting cytotoxicity of 2-phenylindole derivatives against breast cancer cell line MCF7.

Breast cancer is one of the leading causes of cancers among the variety of cancers in woman all over the world. Compounds with phenylindole scaffold were found to execute promising cytotoxicity against breast cancer cell line MCF7. In the present study, a Monte Carlo based QSAR analysis was performed on a dataset containing 102 phenylindoles in order to accelerate the efforts to find out better cytotoxic phenylindoles against MCF7 cell line. The statistical qualities of the generated models were found to be quite good as far as the internal and external validation were concerned. The best models from each split (Split 1: R2 = 0.6944, Q2 = 0.6495; Split 2: R2 = 0.8202, Q2 = 0.7998; Split 3: R2 = 0.8603, Q2 = 0.8357) for the test set were selected and Y-scrambling test and applicability domain analysis were also performed to ensure the robustness of these models. Among these models, model from split 3 obtained by using hybrid descriptors (combination of SMILES and HSG with 0ECk connectivity) was used to identify and classify the structural attributes as promoters as well as hinderers of cytotoxicity for these 2-phenylindole derivatives. Results from the analysis were further used to design and predict some probable new 2-phenylindole derivatives having promising cytotoxicity (IC50 < 55 nM) against MCF7.