4.7 Article

Exploration of N-Arylsulfonyl-indole-2-carboxamide Derivatives as Novel Fructose-1,6-bisphosphatase Inhibitors by Molecular Simulation

Journal

Publisher

MDPI
DOI: 10.3390/ijms231810259

Keywords

fructose-1; 6-biphosphatase inhibitor; 3D-QSAR; virtual screening; molecular docking; molecular dynamics

Funding

  1. National Natural Science Foundation of China [22177090, 21807082]
  2. Graduate Innovative Fund ofWuhan Institute of Technology [CX2021013]
  3. Outstanding Young and Middle-aged Scientific Innovation Team of Colleges and Universities of Hubei Province: Biomass chemical technologies and materials [T201908]
  4. Special Projects of the Central Government in Guidance of Local Science and Technology Development in Hubei Province [2020ZYYD040]
  5. Key Research and Development Project of Hubei Province [2020BAB073]
  6. Innovation Project of Key Laboratory of Novel Biomass-Based Environmental and Energy Materials in Petroleum and Chemical Industry [2022BEEA02]

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A series of potential fructose-1,6-bisphosphatase (FBPase) inhibitors for type II diabetes mellitus treatment were identified through computational modeling. The study provided important insights into the development of novel FBPase inhibitors.
A series of N-arylsulfonyl-indole-2-carboxamide derivatives have been identified as potent fructose-1,6-bisphosphatase (FBPase) inhibitors (FBPIs) with excellent selectivity for the potential therapy of type II diabetes mellitus. To explore the structure-activity relationships (SARs) and the mechanisms of action of these FBPIs, a systematic computational study was performed in the present study, including three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling, pharmacophore modeling, molecular dynamics (MD), and virtual screening. The constructed 3D-QSAR models exhibited good predictive ability with reasonable parameters using comparative molecular field analysis (q(2) = 0.709, R-2 = 0.979, r(pre)(2) = 0.932) and comparative molecular similarity indices analysis (q(2) = 0.716, R-2 = 0.978, r(pre)(2) = 0.890). Twelve hit compounds were obtained by virtual screening using the best pharmacophore model in combination with molecular dockings. Three compounds with relatively higher docking scores and better ADME properties were then selected for further studies by docking and MD analyses. The docking results revealed that the amino acid residues Met18, Gly21, Gly26, Leu30, and Thr31 at the binding site were of great importance for the effective bindings of these FBPIs. The MD results indicated that the screened compounds VS01 and VS02 could bind with FBPase stably as its cognate ligand in dynamic conditions. This work identified several potential FBPIs by modeling studies and might provide important insights into developing novel FBPIs.

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