Further SAR studies on natural template based neuroprotective molecules for the treatment of Alzheimer's disease.

In our earlier paper, we described ferulic acid (FA) template based novel series of multifunctional cholinesterase (ChE) inhibitors for the management of AD. This report has further extended the structure-activity relationship (SAR) studies of this series of molecules in a calibrated manner to improve upon the ChEs inhibition and antioxidant property to identify the novel potent multifunctional molecules. To investigate the effect of replacement of phenylpiperazine ring with benzylpiperazine, increase in the linker length between FA and substituted phenyl ring, and replacement of indole moiety with tryptamine on this molecular template, three series of novel molecules were developed. All synthesized compounds were tested for their acetyl and butyryl cholinestrases (AChE and BChE) inhibitory properties. Enzyme inhibition and PAS binding studies identified compound 13b as a lead molecule with potent inhibitor property towards AChE/BChE (AChE IC50 = 0.96 ± 0.14 µM, BChE IC50 = 1.23 ± 0.23 µM) compared to earlier identified lead molecule EJMC-G (AChE IC50 = 5.74 ± 0.13 µM, BChE IC50 = 14.05 ± 0.10 µM, respectively). Molecular docking and dynamics studies revealed that 13b fits well into the active sites of AChE and BChE, forming stable and strong interactions with key residues Trp86, Ser125, Glu202, Trp 286, Phe295, Tyr 337 in AChE, and with Trp 82, Gly115, Tyr128, and Ser287 in BChE. The compound, 13b was found to be three times more potent antioxidant in a DPPH assay (IC50 = 20.25 ± 0.26 µM) over the earlier identified EJMC-B (IC50 = 61.98 ± 0.30 µM) and it also was able to chelate iron. Co-treatment of 13b with H2O2, significantly attenuated and reversed H2O2-induced toxicity in the SH-SY5Y cells. The parallel artificial membrane permeability assay-blood brain barrier (PAMPA-BBB) revealed that 13b could cross BBB efficiently. Finally, the in-vivo efficacy of 13b at dose of 10 mg/kg in scopolamine AD model has been demonstrated. The present study strongly suggests that the naturally inspired multifunctional molecule 13b may behave as a potential novel therapeutic agent for AD management.

Molecular docking, binding mode analysis, molecular dynamics, and prediction of ADMET/toxicity properties of selective potential antiviral agents against SARS-CoV-2 main protease: an effort toward drug repurposing to combat COVID-19.

The importance of the main protease (Mpro) enzyme of SARS-CoV-2 in the digestion of viral polyproteins introduces Mpro as an attractive drug target for antiviral drug design. This study aims to carry out the molecular docking, molecular dynamics studies, and prediction of ADMET properties of selected potential antiviral molecules. The study provides an insight into biomolecular interactions to understand the inhibitory mechanism and the spatial orientation of the tested ligands and further, identification of key amino acid residues within the substrate-binding pocket that can be applied for structure-based drug design. In this regard, we carried out molecular docking studies of chloroquine (CQ), hydroxychloroquine (HCQ), remdesivir (RDV), GS441524, arbidol (ARB), and natural product glycyrrhizin (GA) using AutoDock 4.2 tool. To study the drug-receptor complex's stability, selected docking possesses were further subjected to molecular dynamics studies with Schrodinger software. The prediction of ADMET/toxicity properties was carried out on ADMET Prediction™. The docking studies suggested a potential role played by CYS145, HIS163, and GLU166 in the interaction of molecules within the active site of COVID-19 Mpro. In the docking studies, RDV and GA exhibited superiority in binding with the crystal structure of Mpro over the other selected molecules in this study. Spatial orientations of the molecules at the active site of Mpro exposed the significance of S1-S4 subsites and surrounding amino acid residues. Among GA and RDV, RDV showed better and stable interactions with the protein, which is the reason for the lesser RMSD values for RDV. Overall, the present in silico study indicated the direction to combat COVID-19 using FDA-approved drugs as promising agents, which do not need much toxicity studies and could also serve as starting points for lead optimization in drug discovery.

Reciprocal Associations Between Maternal Smoking Cessation and Breastfeeding.

Background: Pregnancy is a motivating factor to quit smoking, but many women relapse postpartum. The underlying mechanisms and the necessary duration of breastfeeding that provide long-term protection against postpartum smoking relapse are unknown. Aims: We aimed to examine (1) associations of smoking cessation with breastfeeding initiation and duration; (2) necessary breastfeeding duration to reduce or prevent risk of postpartum smoking relapse. Methods: In this cohort study, we recruited 55 mothers, either smoking or have quit smoking, who recently delivered their baby from the Greater Buffalo area, NY, USA. Results: Quitters had a higher breastfeeding initiation rate (73.7% versus 30.8%; p = 0.029) and breastfed longer (p < 0.024) than nonquitters. Mothers who never breastfed relapsed quicker than mothers who did (p = 0.039). There was a 28% reduction in smoking relapse at 12 months postpartum for every month longer of breastfeeding duration (confounder-adjusted hazard ratio, 0.72 [95% confidence interval, 0.55-0.94]; p = 0.014). The estimated smoking relapse risk was 60.0% for nonbreastfeeding, 22.4% for 3 months of breastfeeding, 8.4% for 6 months of breastfeeding, and 1.2% for 12 months of breastfeeding. Conclusion: Smoking cessation was associated with increased breastfeeding initiation and duration. Smoking relapse risk decreased with longer breastfeeding duration, and 12 months of breastfeeding may help to prevent smoking relapse. An integrated intervention of maternal smoking cessation and breastfeeding promotion is promising to enhance both behaviors.

Genome-wide Association Study for Yield and Yield-Related Traits in Diverse Blackgram Panel (Vigna mungo L. Hepper) Reveals Novel Putative Alleles for Future Breeding Programs.

Blackgram (Vigna mungo L. Hepper) is an important tropical and sub-tropical short-duration legume that is rich in dietary protein and micronutrients. Producing high-yielding blackgram varieties is hampered by insufficient genetic variability, absence of suitable ideotypes, low harvest index and susceptibility to biotic-abiotic stresses. Seed yield, a complex trait resulting from the expression and interaction of multiple genes, necessitates the evaluation of diverse germplasm for the identification of novel yield contributing traits. Henceforth, a panel of 100 blackgram genotypes was evaluated at two locations (Ludhiana and Gurdaspur) across two seasons (Spring 2019 and Spring 2020) for 14 different yield related traits. A wide range of variability, high broad-sense heritability and a high correlation of grain yield were observed for 12 out of 14 traits studied among all environments. Investigation of population structure in the panel using a set of 4,623 filtered SNPs led to identification of four sub-populations based on ad-hoc delta K and Cross entropy value. Using Farm CPU model and Mixed Linear Model algorithms, a total of 49 significant SNP associations representing 42 QTLs were identified. Allelic effects were found to be statistically significant at 37 out of 42 QTLs and 50 known candidate genes were identified in 24 of QTLs.

Semiautomated Small-Scale Purification Method for High-Throughput Expression Analysis of Recombinant Proteins.

The expression analysis of recombinant proteins is a challenging step in any high-throughput protein production pipeline. Often multiple expression systems and a variety of expression construct designs are considered for the production of a protein of interest. There is a strong need to triage constructs rapidly and systematically. This chapter describes a semiautomated method for the simultaneous purification and characterization of proteins expressed from multiple samples of expression cultures from the E. coli, baculovirus expression vector system, and mammalian transient expression systems. This method assists in the selection of the most promising expression construct(s) or the most favorable expression condition(s) to move forward into large-scale protein production.

Implementation of an Automated High-Throughput Plasmid DNA Production Pipeline.

Biologics sample management facilities are often responsible for a diversity of large-molecule reagent types, such as DNA, RNAi, and protein libraries. Historically, the management of large molecules was dispersed into multiple laboratories. As methodologies to support pathway discovery, antibody discovery, and protein production have become high throughput, the implementation of automation and centralized inventory management tools has become important. To this end, to improve sample tracking, throughput, and accuracy, we have implemented a module-based automation system integrated into inventory management software using multiple platforms (Hamilton, Hudson, Dynamic Devices, and Brooks). Here we describe the implementation of these systems with a focus on high-throughput plasmid DNA production management.