Molecular modeling to simulation: insights into Gaussian QSAR, molecular docking, and DFT for identification of HDAC3 inhibitors for neurocognitive vascular dementia
Debojyoti Halder, Suvankar Banerjee, Swati Biswas, Nilanjan Adhikari, Balaram Ghosh
Abstract
Vascular dementia is the second most common form of dementia. It is characterized by reduced blood flow in the cerebral cortex due to neurodegeneration and neuroinflammation. Almost 10 crore people will be suffering from it by 2030. Still, there are no therapeutics reported for the treatment of neurocognitive vascular dementia. Hence, we have explored an epigenetic pathway for the targeted inhibition of histone deacetylase 3 (HDAC3) that can further cure the neurocognitive impairment. In the present study, we have incorporated in silico methodologies for small-molecule inhibitor screening. The methodologies include multi-model pharmacophore development, validation, virtual screening by HDAC3 targeted docking and dynamics simulation, quantum chemical analysis, and ADMET properties. After the virtual screening, the best two compounds were selected according to the docking score, MM/GBSA scoring, and IFD. The top two hits—57402 and 46381 represented interactions with zinc-binding and amino acids such as HIE172 and HIE135 GLY143, and ASP93 residues compared with RGFP966. Furthermore, the density function theory study was employed to understand the reactivity and stability of the compounds, and quantum chemical properties relevant to drug design were compared with standard RGFP966. Following the molecular dynamics simulation and ADMET analysis, which evaluates how a substance is absorbed, distributed, metabolized, and excreted, along with its toxicity, the two hit compounds—57402 and 46381 showed superior binding scores and targeted inhibition of HDAC3 by zinc chelation. Therefore, the study is of great significance in the quest for new molecules for the treatment of vascular dementia targeting HDAC3.