Corrigendum to “3D-QSAR-Based Pharmacophore Modeling, Virtual Screening, and Molecular Docking Studies for Identification of Tubulin Inhibitors with Potential Anticancer Activity”

A discovery of potent kaempferol derivatives as multi-target medicines against diabetes as well as bacterial infections: an in silico approach

Flavonoids demonstrate beneficial effects on human health because flavonoids contain important biological properties. Kaempferol is a flavonol, type of flavonoid found in eatable plants and in plants usually employed in ancient drugs (Moringa oleifera, Tilia spp., fern genus spp. and gingko etc.). Some medicinal studies have shown that the use of foods full of kaempferol decreases the risk of many (cancer, vascular) diseases. All the data of 50 kaempferol derivatives were collected from PubChem database. Through Schrödinger software, 3D-QSAR study was performed for 50 compounds by using method of field base. Conformer of kaempferol derivatives was docked against anti-diabetic, anti-microbial co-crystal structures and protein. To monitor the best anti-diabetic and antibacterial agent, particular kaempferol derivatives were downloaded from PubChem database. Virtual screening by molecular docking provided four lead compounds with four different proteins. These hit compounds were found to be potent inhibitor for diabetic enzymes alpha-amylase and DPP IV and had the potential to suppress DNA gyrase and dihydrofolate reductase synthesis. Molecular dynamic simulation of docked complexes evaluates the value of root mean square fluctuation by iMOD server. Kaempferol 3-O-alpha-L-(2, 3-di-Z-p-coumaroyl) rhamnoside (42) compound used as anti-diabetic and kaempferol 3-O-gentiobioside (3) as antibacterial with good results can be used for drug discovery.Communicated by Ramaswamy H. Sarma.

3D-QSAR-based pharmacophore modelling of quinazoline derivatives for the identification of acetylcholinesterase inhibitors through virtual screening, molecular docking, molecular dynamics and DFT studies

Alzheimer's disease (AD) is a progressive neurological disorder responsible for the cognitive dysfunction and cognitive impairment in the patients. Acetylcholinesterase inhibitors (AChEIs) are used to treat AD however, these only provided symptomatic relief and more efficient drug molecules are desired for the effective treatment of the disease. In this article, ligand-based drug-designing strategy was used to develop and validate a field-based 3D-QSAR pharmacophore model on quinazoline-based AChEIs reported in the literature. The validated pharmacophore model (AAAHR_1) was used as a prefilter to screen an ASINEX database via virtual screening workflow (VSW). The hits generated were subjected to MM-GBSA to identify potential AChEIs and top three scoring molecules (BAS 05264565, LEG 12727144 and SYN 22339886) were evaluated for thermodynamic stability at the target site using molecular dynamic simulations. Additionally, DFT study was performed to predict the reactivity of lead molecules towards acetylcholinesterase (AChE). Thus, by utilising various computational tools, three molecules were identified as potent AChEIs that can be developed as potential drug candidates for the treatment of AD.Communicated by Ramaswamy H. Sarma.

4-Phthalimidobenzenesulfonamide Derivatives as Acetylcholinesterase and Butyrylcholinesterase Inhibitors: DFTs, 3D-QSAR, ADMET, and Molecular Dynamics Simulation

INTRODUCTION

Alzheimer's disease is a form of dementia which affects majority of the people. It is characterized by memory loss and other cognitive function disabilities and is one of the most challenging neurodegenerative disorders to treat because of its progressive nature. The disease affects millions of people all around the world, and the number of those affected is expanding every day. In the previous study, the 4-phthalimidobenzenesulfonamide derivatives were synthesized as AChE and BChE inhibitors, and here, we were aiming to further reporting in silico studies of these compounds for efficient drug discovery process and to find out the potential lead compounds.

METHODS

In silico characterization included density functional theory (DFT) studies, 3D-QSAR, ADMET properties, molecular docking, and molecular dynamic simulations. The geometries of all derivatives were optimized using B3LYP method and 6-311G basis set.

RESULTS

The findings of the current study revealed that 4-phthalimidobenzenesulfonamide derivatives exhibited a reactive electronic property which is essential for anticholinesterase activity. Moreover, optimized structures were subjected to molecular docking studies with targeted protein. The compounds 2c and 2g showed excellent binding score of -37.44 and -33.67 kJ/mol with BChE and AChE, respectively, and exhibited strong binding affinity. The potent derivatives produced stable complex with amino acid residues of active pocket of both BChE and AChE. The stability of protein-ligand complexes was determined by molecular dynamic simulation studies, and results were found in correlation with molecular docking findings.

CONCLUSION

Findings of the current study suggested that these derivatives are potent inhibitors of cholinesterase enzyme.