Morpholino Pyrimidine/Pyrimidino‐Oxazines: An Integrated Study as DGAT1 Inhibitors Through QSAR, Molecular Docking, ADMET, and Computational Simulation

Abstract Obesity has become a widespread health issue, often leading to serious conditions like fatty liver disease, type 2 diabetes, and heart disease. A significant factor in obesity is the buildup of triglycerides, with diacylglycerol acyltransferase (DGAT1) being a key enzyme involved in triglyceride synthesis and a potential target for treatment. This study explored the potential of morpholino pyrimidine/pyrimidino‐oxazine as DGAT1 inhibitors using computational methods. A library of 250 compounds from PubChem and ZINC databases was docked against DGAT1 (PDB ID: 6VP0), yielding binding energies between −6.0 and −11.6 kcal/mol. ADME and physicochemical assessments narrowed these to the top 20 candidates. A 2D‐QSAR model ( R 2 = 0.928, Q 2 = 0.624) was created using known DGAT1 inhibitors and predicted ‐LogIC 50 values for the top compounds showed close alignment. Furthermore, molecular dynamics simulations (100 ns), three sets of short MD run for 25 ns and principal component analysis (PCA) were conducted on the top two hits, PubChem CID155551474 and CID46268159. The results demonstrated stable complexes with DGAT1, with CID155551474 exhibiting superior performance. MMPBSA analysis confirmed binding stability with maximum energy at −300.42 ± 12.41 kJ/mol. This work is the first to suggest morpholino‐pyrimidine and pyrimidino‐oxazine derivatives as DGAT1 inhibitors, recommending further in vivo studies to confirm therapeutic efficacy.

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Journal
ChemistrySelect
Published
2025-09-01
DOI
https://doi.org/10.1002/slct.202502210
Primary Topic
Computational Drug Discovery Methods
Type
article
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article

Morpholino Pyrimidine/Pyrimidino‐Oxazines: An Integrated Study as DGAT1 Inhibitors Through QSAR, Molecular Docking, ADMET, and Computational Simulation

Leena Khanna, Asmita Singh, Deepshikha Gupta, Pankaj Khanna et al.
ChemistrySelect
Computational Drug Discovery Methods
article

Morpholino Pyrimidine/Pyrimidino‐Oxazines: An Integrated Study as DGAT1 Inhibitors Through QSAR, Molecular Docking, ADMET, and Computational Simulation

Leena Khanna, Asmita Singh, Deepshikha Gupta, Pankaj Khanna, Mansi, Sandeep Kumar Singh
article en

Abstract

Abstract Obesity has become a widespread health issue, often leading to serious conditions like fatty liver disease, type 2 diabetes, and heart disease. A significant factor in obesity is the buildup of triglycerides, with diacylglycerol acyltransferase (DGAT1) being a key enzyme involved in triglyceride synthesis and a potential target for treatment. This study explored the potential of morpholino pyrimidine/pyrimidino‐oxazine as DGAT1 inhibitors using computational methods. A library of 250 compounds from PubChem and ZINC databases was docked against DGAT1 (PDB ID: 6VP0), yielding binding energies between −6.0 and −11.6 kcal/mol. ADME and physicochemical assessments narrowed these to the top 20 candidates. A 2D‐QSAR model ( R 2 = 0.928, Q 2 = 0.624) was created using known DGAT1 inhibitors and predicted ‐LogIC 50 values for the top compounds showed close alignment. Furthermore, molecular dynamics simulations (100 ns), three sets of short MD run for 25 ns and principal component analysis (PCA) were conducted on the top two hits, PubChem CID155551474 and CID46268159. The results demonstrated stable complexes with DGAT1, with CID155551474 exhibiting superior performance. MMPBSA analysis confirmed binding stability with maximum energy at −300.42 ± 12.41 kJ/mol. This work is the first to suggest morpholino‐pyrimidine and pyrimidino‐oxazine derivatives as DGAT1 inhibitors, recommending further in vivo studies to confirm therapeutic efficacy.

ChemistrySelectVol. 10(34)
Guru Gobind Singh Indraprastha University (IN), Amity University (IN), Acharya Narendra Deva University of Agriculture and Technology (IN), O. P. Jindal Global University (IN)
Openalex Percentile: Top 75%
Computational Drug Discovery Methods
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