Recent pandemic situation of COVID-19 is caused due to SARS-CoV2 and almost all the countries of the world has been affected by this highly contagious virus. Main protease (M pro ) of this virus is a highly attractive drug target among various other enzymes due to its ability to process poly-protein that is the translated product of the SARS-CoV2 RNA. The aim of the present study demonstrates molecular docking study of Glycyrrhiza glabra (Gg) active compounds such as Glycyrrhizic acid (GA), Liquiritigenin (L) and Glabridin (G) against the M pro . Docking studies shows that these active compounds bind strongly with some of the amino acid residues in the active site of M pro and inhibits the enzyme strongly. GA, L, and G are proposed to be strong inhibitors of the enzyme and the amino acids: His 41 , Gly 143 , Gln 189 , Glu 166 , Cys 145 , Thr 25 , Asn 142 , Met 49 , Cys 44 , Thr 45 and pro 168 present in the active site of M pro were shown to make non-covalent interaction with these compounds. In silico ADMET properties prediction also shows that Gg active compounds had good solubility, absorption, permeation, non-toxic, and non- carcinogenic characteristics. Our finding concludes that all of the three active compounds of Gg could have the potential to be strong inhibitors for M pro of SARS-CoV2 but glycyrrhizic acid have a high binding affinity of -8.0 Kcal/mol and glycyrrhizic acid have good ADMET properties than the other two.

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Pullulan production from Aureobasidium pullulans was explored to increase yield. Non-linear hybrid mathematical tools for optimization of process variables as well as the pullulan yield were analyzed. The one variable at a time (OVAT) approach was used to optimize the maximum pullulan yield of 35.16 ± 0.29 g/L. The tools predicted maximum pullulan yields of 39.4918 g/L (genetic algorithm coupled with artificial neural network (GA–ANN)) and 36.0788 g/L (GA coupled with adaptive network based fuzzy inference system (GA–ANFIS)). The best regression value (0.94799) of the Levenberg–Marquardt (LM) algorithm for ANN and the epoch error (6.1055 × 10−5) for GA–ANFIS point towards prediction precision and potentiality of data training models. The process parameters provided by both the tools corresponding to their predicted yield were revalidated by experiments. Among the two of them GA–ANFIS results were replicated with 98.82% accuracy. Thus GA–ANFIS predicted an optimum pullulan yield of 36.0788 g/L with a substrate concentration of 49.94 g/L, incubation period of 182.39 h, temperature of 27.41 °C, pH of 6.99, and agitation speed of 190.08 rpm.

The presence of antineoplastic compounds in aquatic ecosystem is an emerging challenge for the society. Antineoplastic compounds released into the aquatic environment exhibit a potential threat to normal aquatic life. Particularly, antineoplastic compounds are responsible for direct or indirect interference with the cellular DNA of an organism and cause toxicity to cells. The present study focused on the assessment of in vitro toxic effect of cyclophosphamide, etoposide and paclitaxel on Raw 264.7 cell line (mouse monocyte macrophage cells). The inhibitory concentration of cyclophosphamide, etoposide, and paclitaxel was determined. The IC 50 values of these compounds were 145.44, 5.40, and 69.76 lg ml -1 respectively. This is the first report on toxicity analysis of cyclophosphamide, paclitaxel and etoposide on Raw 264.7 cell line by reducing cell viability and indicating the cell cytotoxicity i.e., 69.58% for cyclophosphamide, 92.01% for etoposide and 88.85% for paclitaxel on concentration 250 lg ml -1 . The results of their cytotoxicity assessment highlight the need of improvement in sewage treatment technology for the efficient removal of these compounds from aquatic environment.