Structure-based drug design of pre-clinical candidate nanopiperine: a direct target for CYP1A1 protein to mitigate hyperglycaemia and associated microbes.

IF 2.3 3区 环境科学与生态学 Q3 CHEMISTRY, MULTIDISCIPLINARY SAR and QSAR in Environmental Research Pub Date : 2024-12-04 DOI:10.1080/1062936X.2024.2434934
R Dey, S Saha, S H Molla, S Nandi, A Samadder
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Abstract

Diabetes is attributed to an increased vulnerability to bacterial infection linked to unregulated hyperglycaemia. The present study highlights the formulation of nanoparticles with phyto-compound piperine (PIP) encapsulated within non-toxic biodegradable polymer poly-lactide co-glycolide (PLGA) which showed a variety in surface functionality, biocompatibility, and the ability to tailor an optimized release rate from its polymeric enclosure. The observations revealed that nanopiperine (NPIP) pre-treatment in mice inhibited alteration in hepatic tissue architecture and hepato-biochemical parameters in diabetes and its associated bacterial infections. NPIP also decreased the propensity of lipids to undergo an oxidation process and stabilized the membrane lipids in vivo, thereby lowering oxidative stress and preventing enzymatic activation of CYP1A1. This result is corroborated with the in silico molecular docking study where PIP binding with CYP1A1 gave -11.32 Kcal/mol dock score value. The antibacterial activity of PIP was further demonstrated by the in silico PIP and Ef-Tu protein-binding efficacy revealing -6.48 Kcal/mol score value which was coupled with the results of in vitro studies where the zone of inhibition assay with NPIP against Staphylococcus aureus and Escherichia coli. Thus, NPIP could serve as a potential drug candidate in modulating targeted proteins to inhibit the progression of hyperglycaemia and its associated microbes.

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来源期刊
CiteScore
5.20
自引率
20.00%
发文量
78
审稿时长
>24 weeks
期刊介绍: SAR and QSAR in Environmental Research is an international journal welcoming papers on the fundamental and practical aspects of the structure-activity and structure-property relationships in the fields of environmental science, agrochemistry, toxicology, pharmacology and applied chemistry. A unique aspect of the journal is the focus on emerging techniques for the building of SAR and QSAR models in these widely varying fields. The scope of the journal includes, but is not limited to, the topics of topological and physicochemical descriptors, mathematical, statistical and graphical methods for data analysis, computer methods and programs, original applications and comparative studies. In addition to primary scientific papers, the journal contains reviews of books and software and news of conferences. Special issues on topics of current and widespread interest to the SAR and QSAR community will be published from time to time.
期刊最新文献
Enhanced prediction of beta-secretase inhibitory compounds with mol2vec technique and machine learning algorithms. Structure-based drug design of pre-clinical candidate nanopiperine: a direct target for CYP1A1 protein to mitigate hyperglycaemia and associated microbes. Structure-based pharmacophore modelling for ErbB4-kinase inhibition: a systematic computational approach for small molecule drug discovery for breast cancer. A deep learning model based on the BERT pre-trained model to predict the antiproliferative activity of anti-cancer chemical compounds. Discovery of novel pyrrolo[2,3-d]pyrimidine derivatives as anticancer agents: virtual screening and molecular dynamic studies.
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