QSAR, molecular docking and ADMET properties in silico studies of novel 4,5,6,7-tetrahydrobenzo[D]-thiazol-2-Yl derivatives derived from dimedone as potent anti-tumor agents through inhibition of C-Met receptor tyrosine kinase

Abstract

A quantitative structure-activity relationship (QSAR) study is performed on 48 novel 4,5,6,7-tetrahydrobenzo[D]thiazol-2 derivatives as anticancer agents capable of inhibiting c-Met receptor tyrosine kinase. The present study is conducted using multiple linear regression, multiple nonlinear regression and artificial neural networks. Three QSAR models are developed after partitioning the database into two sets (training and test) via the k-means method. The obtained values of the correlation coefficients by the three developed QSAR models are 0.90, 0.91 and 0.92, respectively. The resulting models are validated by using the external validation, leave-one-out crossvalidation, Y-randomization test, and applicability domain methods. Moreover, we evaluated the drug-likeness properties of seven selected molecules based on their observed high activity to inhibit the c-Met receptor. The results of the evaluation showed that three of the seven compounds present drug-like characteristics.In order to identify the important active sites for the inhibition of the c-Met receptor responsible for the development of cancer cell lines, the crystallized form of the Crizotinib-c-Met complex (PDB code: 2WGJ) is used. These sites are used as references in the molecular docking test of the three selected molecules to identify the most suitable molecule for use as a new c-Met inhibitor. A comparative study is conducted based on the evaluation of the predicted properties of ADMET in silico between the candidate molecule and the Crizotinib inhibitor. The comparison results show that the selected molecule can be used as new anticancer drug candidates.

Design, synthesis, characterization,in vitroscreening, molecular docking, 3D-QSAR, and ADME-Tox investigations of novel pyrazole derivatives as antimicrobial agents

“…So, the molecular docking process is considered acceptable. 39 Fig. 1 shows the 3D visualization of the original and re-docked poses, for ampicillin (Fig.…”

“…46 Evaluation of drug distribution was expressed by VDss indicators, BBB permeability and CNS permeability. 39 Metabolism was determined by predicting the modes of interactions of molecule candidates with Cytochrome P450 (CYP450). 47 Also, the ability to excrete drugs is estimated by the prediction of the total clearance index.…”

QSAR, ADMET In Silico Pharmacokinetics, Molecular Docking and Molecular Dynamics Studies of Novel Bicyclo (Aryl Methyl) Benzamides as Potent GlyT1 Inhibitors for the Treatment of Schizophrenia

“…Using the k-means method, we randomly divided the database into training and test sets. The first one includes 80% of the total data (35 molecules) and was taken to develop the QSAR models, while the second one contains 20% of the total data (7 molecules) and was used to assess the validity of the developed models [21].…”

“…To make the drugs applicable in clinical trials, it is necessary to study their absorption, distribution, metabolism, excretion and toxicity (ADMET) in the human body before starting the investigation protocols [21,47], respecting some important rules such as those of Lipinski [48], Veber [49], Ghose [50] and Egan [51,52]. This technique is also applied to eliminate the compounds with potentially undesirable physiological qualities, taking into account toxicity and pharmacokinetic properties [53].…”

Rational identification of small molecules derived from 9,10-dihydrophenanthrene as potential inhibitors of 3CLpro enzyme for COVID-19 therapy: a computer-aided drug design approach

“…Based on in vitro results on the suitability of 9,10-dihydrophenanthrene derivatives for the inhibition of 3CL pro , in this work, we perform a large-scale computational study aided by bioinformatics techniques to validate in vitro results and also to rationalize the design of new non-covalent inhibitors of 3CL pro as more convenient drugs against COVID-19. For this purpose, this study includes the following principal objectives: the study of the quantitative structure–activity relationship for 9,10-dihydrofenantrene derivatives based on 3D-QSAR techniques [ 8 , 38 ], improvement of the biological inhibitory activity of these molecules based on the obtained pharmacological hypotheses, screening the most active molecular structures that are able to inhibit SARS-CoV-2 3CL pro , predicting the drug-like and drug-pharmacokinetic ADMET profiles of the candidate drug molecules [ 41 , 42 ], exploring the potential interaction patterns between active amino acids in the protein pocket of 3CL pro (PDB code: 6LU7) (Fig. 1 ) [ 29 ] and the drug molecules using molecular docking and MM-GBSA techniques, and performing molecular dynamics simulations to check the stability of candidate SARS-CoV-2 3CL pro inhibitors in the aquatic environment.…”