Chemoinformatics Study of Benzodiazepine-1, 2, 3-triazole Derivatives Targeting Butyrylcholinesterase.

This study aims to assess the potential bioactivity of newly designed benzodiazepine-1,2,3-triazole derivatives using in-silico methodologies, with a primary focus on elucidating their inhibitory interactions with the butyrylcholinesterase (BuChE) enzyme, which is implicated in Alzheimer's disease. We employed multiple linear regression (MLR) methods to conduct a quantitative structure-activity relationship (QSAR) analysis on a collection of 31 benzodiazepine-1,2,3-triazole derivatives, with the goal of investigating, assessing, and predicting their activities, as well as designing novel compounds. This approach yielded highly accurate results, with coefficients of determination (R²) of 0.

Design of new molecules against cervical cancer using DFT, theoretical spectroscopy, 2D/3D-QSAR, molecular docking, pharmacophore and ADMET investigations.

Cervical cancer is a major health problem of women. Hormone therapy, via aromatase inhibition, has been proposed as a promising way of blocking estrogen production as well as treating the progression of estrogen-dependent cancer. To overcome the challenging complexities of costly drug design, in-silico strategy, integrating Structure-Based Drug Design (SBDD) and Ligand-Based Drug Design (LBDD), was applied to large representative databases of 39 quinazoline and thioquinazolinone compound derivatives.

Structure-based virtual screening of novel natural products as chalcone derivatives against SARS-CoV-2 M.

Coronavirus disease 2019 (COVID-19), which is caused by SARS-CoV-2, has spread quickly around the world, causing a global pandemic. It has infected more than 500 million people as of April 28, 2022. Much research has been reported to stop the virus from spreading, but there are currently no approved medicines to treat COVID-19.

Design of novel quinoline derivatives as antibreast cancer using 3D-QSAR, molecular docking and pharmacokinetic investigation.

Breast cancer has been one of the most challenging women's cancers and leading cause of mortality for decades. There are several studies being conducted all the time to find a cure for breast cancer. Quinoline derivatives have shown their potential as antitumor agents in breast cancer therapy.

Homology modeling, virtual screening, molecular docking, molecular dynamic (MD) simulation, and ADMET approaches for identification of natural anti-Parkinson agents targeting MAO-B protein.

Monoamine oxidase-B (MAO-B) is a flavin-dependent enzyme involved in various neurodegenerative disorders. Here, a dataset of 142 chalcone derivatives, collected from various natural plants, was screened by combining structure-based virtual screening and ADMET approaches. The goal is to discover novel natural chalcones as potential MAO-B inhibitors.

Development of novel monoamine oxidase B (MAO-B) inhibitors by combined application of docking-based alignment, 3D-QSAR, ADMET prediction, molecular dynamics simulation, and MM_GBSA binding free energy.

Unsaturated ketone derivatives are known as inhibitors of monoamine oxidase B (MAO-B), a potential drug target of Parkinson's disease. Here, docking-based alignment, 3 D-QSAR (three-dimensional quantitative structure-activity relationship) studies, ADMET (absorption, distribution, metabolism, excretion, and toxicity) prediction, molecular dynamics (MD) simulation, and MM_GBSA binding free energy were performed on a novel series of MAO-B inhibitors. The objective is to predict new MAO-B inhibitors with high potency activity.

3D-QSAR modeling and molecular docking studies on a series of 2, 4, 5-trisubstituted imidazole derivatives as CK2 inhibitors.

Protein case in kinase II alpha subunit (CK2) plays an imperative function in treating cancer disease. Herein, we have performed a three-dimensional quantitative structure activity relationship (3D-QSAR), and molecular docking analysis on a novel series of 2, 4, 5-trisubstituted imidazole derivatives in order to design potent kinase II alpha subunit (CK2) inhibitors. The 3D-QSAR methods such as comparative molecular similarity indexes analysis (COMSIA), and the comparative molecular field analysis (COMFA) were investigate using twenty-four molecules of 2, 4, 5-trisubstituted imidazole derivatives as anticancer agent.

Computational investigation of unsaturated ketone derivatives as MAO-B inhibitors by using QSAR, ADME/Tox, molecular docking, and molecular dynamics simulations.

Unsaturated ketone derivatives are known as monoamine oxidase B (MAO-B) inhibitors, a potential drug target for Parkinson's disease. Here, molecular modeling studies, including 2D-QSAR, ADMET prediction, molecular docking, and MD simulation, were performed on a new series of MAO-B inhibitors. The objective is to identify new MAO-B inhibitors with high inhibitory efficacy.

2D-QSAR and docking study of a series of coumarin derivatives as inhibitors of CDK (anticancer activity) with an application of the molecular docking method.

Quantitative Structure Activity Relationship (QSAR) analysis techniques are tools largely utilized in many research fields, including drug discovery processes. In this work electronic descriptors are calculated with the Gaussian 03W software using the DFT method with the BecKe 3-parameters exchange functional and Lee-Yang-Parr correlation functional, with Kohn and Sham orbitals (KS) developed on a Gaussian Basis of type 6-31G (d), in combination with five Lipinski parameters that have been calculated with ChemOffice software, in order to develop a statistically verified 2D-QSAR model able to predict the biological activity of new molecules belonging to the same range of coumarins rather than chemical synthesis and biological evaluations that require more time and resources. Two QSAR models against both MCF-7 and HepG-2 cell lines are obtained using the multiple linear regression method.