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1.
Phytomedicine ; 85: 153523, 2021 May.
Article in English | MEDLINE | ID: mdl-33662771

ABSTRACT

BACKGROUND: Extensive research over the past several decades, explored that the natural compounds contain different plant secondary metabolites and have the potential to inhibit breast cancer resistance protein (BCRP). PURPOSE: To identify crucial molecular fingerprints of some natural products for the inhibition of breast cancer resistance protein and also to screen out some potent natural BCRP inhibitors. STUDY DESIGN: Multiple modelling strategies were applied with three main mottos: (a) Generation of robust classification models to identify the linear and non-linear relationships among the natural compounds and the inhibition of BCRP, (b) Identification of important structural fingerprints that modulate BCRP inhibition and screening of natural database to find the probable hit molecules, (c) Comprehensive ligand-receptor interactions analysis of those against the putative breast cancer resistant protein through molecular docking analysis. METHODS: Monte Carlo optimization and SPCI analysis was used to identify important structural fingerprints. QSARCo. and swissADME analysis were used for screening and prediction of hits. Finally, docking analysis was performed for interaction study. RESULTS: In this study, some important structural fingerprints of BCRP inhibitors were identified. Additionally, eleven natural anti-cancer compounds were predicted to be active against the BCRP and also satisfy the different drug-likeliness properties. Among them, apigenin was found to have better binding affinities against the putative target as obtained from molecular docking analysis. CONCLUSION: This study is an attempt to understand about the molecular fingerprints of natural compounds for the inhibition of BCRP and also to dig out some novel natural inhibitors against BCRP.


Subject(s)
ATP Binding Cassette Transporter, Subfamily G, Member 2/antagonists & inhibitors , Biological Products/pharmacology , Neoplasm Proteins/antagonists & inhibitors , Antineoplastic Agents/pharmacology , Drug Discovery , Drug Resistance, Neoplasm , Humans , Molecular Docking Simulation , Neoplasms , Protein Binding , Protein Structure, Tertiary , Quantitative Structure-Activity Relationship
2.
Bioorg Med Chem ; 29: 115860, 2021 01 01.
Article in English | MEDLINE | ID: mdl-33191083

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) brutally perils physical and mental health worldwide. Unavailability of effective anti-viral drug rendering global threat of COVID-19 caused by SARS-CoV-2. In this scenario, viral protease enzymes are crucial targets for drug discovery. This extensive study meticulously focused on two viral proteases such as main protease (Mpro) and papain-like protease (PLpro), those are essential for viral replication. This review provides a detail overview of the targets (Mpro and PLpro) from a structural and medicinal chemistry point of view, together with recently reported protease inhibitors. An insight into the challenges in the development of effective as well as drug like protease inhibitors is discussed. Peptidomimetic and/or covalent coronavirus protease inhibitors possessed potent and selective active site inhibition but compromised in pharmacokinetic parameters to be a drug/drug like molecule. Lead optimization of non-peptidomimetic and/or low molecular weight compounds may be a better option for oral delivery. A masterly combination of adequate pharmacokinetic properties with coronavirus protease activity as well as selectivity will provide potential drug candidates in future. This study is a part of our endeavors which surely dictates medicinal chemistry efforts to discover effective anti-viral agent for this devastating disease.


Subject(s)
Antiviral Agents/metabolism , Coronavirus 3C Proteases/metabolism , Cysteine Proteinase Inhibitors/metabolism , Drug Discovery , Antiviral Agents/chemistry , Catalytic Domain , Coronavirus 3C Proteases/chemistry , Cysteine Proteinase Inhibitors/chemistry , Drug Evaluation, Preclinical , Molecular Docking Simulation , Molecular Structure , Protein Binding , Quantitative Structure-Activity Relationship , SARS-CoV-2/enzymology
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