Multi-model in silico characterization of 3-benzamidobenzoic acid derivatives as partial agonists of Farnesoid X receptor in the management of NAFLD

Mitra, Soumya; Halder, Amit Kumar; Ghosh, Nilanjan; Mandal, S. C.; Cordeiro, M. Natália D. S.

doi:10.1016/j.compbiomed.2023.106789

Cited by 3 publications

(1 citation statement)

References 51 publications

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“…The QPHAR models were built after dividing the dataset into a training set (26 compounds) and test set (10 compounds), using the splitData.py tool in QPHAR. The rationale behind the QPHAR-based pharmacophore modeling methodology has been described in detail by Kohlbacher et al [ 42 ], as well as in our previous study [ 43 ]. Specifically, the train.py tool in this software was used for generating the models solely with the training set using the random forest (RF) technique and the following parameters: fuzzy: True; weight type: distance; threshold: 1.5; number of estimators: 10; maximum depth: 3; and metric: R 2 .…”

Section: Methodsmentioning

confidence: 99%

Shaping the Future of Obesity Treatment: In Silico Multi-Modeling of IP6K1 Inhibitors for Obesity and Metabolic Dysfunction

Mondal,

Halder,

Pattanayak

et al. 2024

Pharmaceuticals

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Recent research has uncovered a promising approach to addressing the growing global health concern of obesity and related disorders. The inhibition of inositol hexakisphosphate kinase 1 (IP6K1) has emerged as a potential therapeutic strategy. This study employs multiple ligand-based in silico modeling techniques to investigate the structural requirements for benzisoxazole derivatives as IP6K1 inhibitors. Firstly, we developed linear 2D Quantitative Structure–Activity Relationship (2D-QSAR) models to ensure both their mechanistic interpretability and predictive accuracy. Then, ligand-based pharmacophore modeling was performed to identify the essential features responsible for the compounds’ high activity. To gain insights into the 3D requirements for enhanced potency against the IP6K1 enzyme, we employed multiple alignment techniques to set up 3D-QSAR models. Given the absence of an available X-ray crystal structure for IP6K1, a reliable homology model for the enzyme was developed and structurally validated in order to perform structure-based analyses on the selected dataset compounds. Finally, molecular dynamic simulations, using the docked poses of these compounds, provided further insights. Our findings consistently supported the mechanistic interpretations derived from both ligand-based and structure-based analyses. This study offers valuable guidance on the design of novel IP6K1 inhibitors. Importantly, our work exclusively relies on non-commercial software packages, ensuring accessibility for reproducing the reported models.

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Section: Methodsmentioning

confidence: 99%

Shaping the Future of Obesity Treatment: In Silico Multi-Modeling of IP6K1 Inhibitors for Obesity and Metabolic Dysfunction

Mondal,

Halder,

Pattanayak

et al. 2024

Pharmaceuticals

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Unveiling structural determinants for FXR antagonism in 1,3,4-trisubstituted-Pyrazol amide derivatives: A multi-scale in silico modelling approach

Mitra,

Halder,

Koley

et al. 2024

Computers in Biology and Medicine

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Explore of potential targets and mechanisms of hesperetin in treating metabolic dysfunction-associated steatosis liver disease via network pharmacology and in vitro experiments

Wu,

Lin,

et al. 2024

Preprint

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Metabolic dysfunction-associated steatosic liver disease (MASLD) is a serious public health issue globally; however, there is no specific drug treatment. Hesperetin, a flavonoid extracted from citrus, possesses multiple pharmacological properties. However, limited reports have elucidated the pharmacological targets of and molecular mechanisms underlying hesperetin on lipid metabolism disorders in MASLD. First, in vitro experiments confirmed the ameliorative effect of hesperetin on lipid accumulations. Second, putative target genes of the compounds were screened using public databases. MASLD-related targets were obtained through data mining of the GEO database. Third, a PPI network was constructed to screen for the core targets through the STRING database. Additionally, GO and KEGG enrichment analyses were performed on the key targets to identify the enriched genes with specific biological themes. We analyzed the binding mode of hesperetin to the key targets using molecular docking. Finally, the potential mechanism by which hesperetin affects MASLD was validated experimentally on an in vitro model. The current evidence suggested that hesperetin ameliorated lipid accumulation by inhibiting the IL-6-mediated STAT3-SOCS3 signaling pathway. Our findings provided novel insights into the underlying mechanisms and the clinical potential of hesperetin in MASLD management or prevention.

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Multi-model in silico characterization of 3-benzamidobenzoic acid derivatives as partial agonists of Farnesoid X receptor in the management of NAFLD

Cited by 3 publications

References 51 publications

Shaping the Future of Obesity Treatment: In Silico Multi-Modeling of IP6K1 Inhibitors for Obesity and Metabolic Dysfunction

Shaping the Future of Obesity Treatment: In Silico Multi-Modeling of IP6K1 Inhibitors for Obesity and Metabolic Dysfunction

Unveiling structural determinants for FXR antagonism in 1,3,4-trisubstituted-Pyrazol amide derivatives: A multi-scale in silico modelling approach

Explore of potential targets and mechanisms of hesperetin in treating metabolic dysfunction-associated steatosis liver disease via network pharmacology and in vitro experiments

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