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Article ; Online: Computational assessment of the reactivity and pharmaceutical potential of novel triazole derivatives

Kamal Tabti / Abdelouahid Sbai / Hamid Maghat / Tahar Lakhlifi / Mohammed Bouachrine

Arabian Journal of Chemistry, Vol 17, Iss 1, Pp 105376- (2024)

An approach combining DFT calculations, molecular dynamics simulations, and molecular docking

1481

Abstract: The worldwide prevalence of cancer and its increasing frequency make it a key research area in drug discovery programs. The current research paper describes the development of QSAR models based on the in vitro against topoisomerase II, which identified ... ...

Abstract	The worldwide prevalence of cancer and its increasing frequency make it a key research area in drug discovery programs. The current research paper describes the development of QSAR models based on the in vitro against topoisomerase II, which identified the structural origin of anticancer activity for derivatives of triazole moieties linked to mansonone E. The models PLS regression QSARs validated by LOO showed an R2 of 0.92, 0.89 and 0.99 and a Q2 of 0.75, 0.62 and 0.88 for CoMFA, CoMSIA and HQSAR respectively. External validation criteria were used to validate the reliability of the models. These results show the impact of electrostatic and steric fields and of the hydrogen bond donor on the activity of the compounds studied. Based on these results, seven novel inhibitors with high activity were designed, which successfully passed Lipinski's rule of five for oral bioavailability. The evaluations of ADME/Tox parameters and synthetic accessibility for chemical synthesis showed acceptable results. Ligand interactions in binding site protein were assessed using molecular docking. The results show the correct conformational pose of the designed compounds especially the compound T1 where it forms hydrogen and hydrophobic interactions with the main binding site residues. The stability of the complexes was confirmed by the MD study and the calculation of the free binding energy. The T1 synthesis reaction was carried out according to the 1,3 cycloaddition reaction. The study of the local and global reactivity and the energy of activation of this reaction have shown the predicted of the regioselectivity of compound T1. Also we have described the state of transition of two isomers T1,4 and T1.5. Finally, this study would be interesting to help identify and optimize avenues for early discovery of anticancer drugs.
Keywords	QSAR ; Topoisomerase IIα ; Docking ; MD simulation ; ADMET ; Chemistry ; QD1-999
Subject code	540
Language	English
Publishing date	2024-01-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Molecular docking, molecular dynamics simulation, and ADMET analysis of levamisole derivatives against the SARS-CoV-2 main protease (MPro)

Khalil EL Khatabi / Ilham Aanouz / Marwa Alaqarbeh / Mohammed Aziz Ajana / Tahar Lakhlifi / Mohammed Bouachrine

BioImpacts, Vol 12, Iss 2, Pp 107-

2022 Volume 113

Abstract: Introduction: The new species of coronaviruses (CoVs), SARS-CoV-2, was reported as responsible for an outbreak of respiratory disease. Scientists and researchers are endeavoring to develop new approaches for the effective treatment against of the COVID- ... ...

Abstract	Introduction: The new species of coronaviruses (CoVs), SARS-CoV-2, was reported as responsible for an outbreak of respiratory disease. Scientists and researchers are endeavoring to develop new approaches for the effective treatment against of the COVID-19 disease. There are no finally targeted antiviral agents able to inhibit the SARS-CoV-2 at present. Therefore, it is of interest to investigate the potential uses of levamisole derivatives, which are reported to be antiviral agents targeting the influenza virus. Methods: In the present study, 12 selected levamisole derivatives containing imidazo[2,1-b]thiazole were subjected to molecular docking in order to explore the binding mechanisms between these derivatives and the SARS-CoV-2 Mpro (PDB: 7BQY). The levamisole derivatives were evaluated for in silico ADMET properties for wet-lab applicability. Further, the stability of the best-docked complex was checked using molecular dynamics (MD) simulation at 20 ns. Results: Levamisole derivatives and especially molecule N°6 showed more promising docking results, presenting favorable binding interactions as well as better docking energy compared to chloroquine and mefloquine. The results of ADMET prediction and MD simulation support the potential of the molecule N°6 to be further developed as a novel inhibitor able to stop the newly emerged SARS-CoV-2. Conclusion: This research provided an effective first line in the rapid discovery of drug leads against the novel CoV (SARS-CoV-2).
Keywords	covid-19 ; sars-cov-2 ; levamisole ; molecular docking ; molecular dynamics simulation ; in silico admet ; Medicine (General) ; R5-920 ; Biology (General) ; QH301-705.5
Subject code	540
Language	English
Publishing date	2022-02-01T00:00:00Z
Publisher	Tabriz University of Medical Sciences
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: ADMET profiling and molecular docking of pyrazole and pyrazolines derivatives as antimicrobial agents

Fatima EN-NAHLI / Halima HAJJI / Mohamed OUABANE / Mohammed Aziz AJANA / Chakib SEKATTE / Tahar LAKHLIFI / Mohammed BOUACHRINE

Arabian Journal of Chemistry, Vol 16, Iss 11, Pp 105262- (2023)

2023

Abstract: In the present study, a Molecular Docking and in silico ADMET analysis were performed to identify the possible inhibitory effect of 23 molecules, pyrazole and pyrazolines derivatives, on Escherichia coli and to predict the absorption, distribution, ... ...

Abstract	In the present study, a Molecular Docking and in silico ADMET analysis were performed to identify the possible inhibitory effect of 23 molecules, pyrazole and pyrazolines derivatives, on Escherichia coli and to predict the absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of all compounds. According to the results, every compound examined might bind to this bacterium's active site (PDB: 1FJ4). The results obtained in silico demonstrated that Only 4 (M6, M17, M19 and M20) of the 23 compounds were selected due to their inhibitory action and proximity to the important catalytic residues Thr302, Thr300, Val270, and His298 of the major protease and could be considered as orally active drug candidates due to their physical and chemical properties. The compounds M6, M17, M19 and M20 were subjected to Lipinski’s rule of five because it has the best binding affinity score in the binding study of the compound with the protein (-9.6, −9.3, −9.5, −10.3 Kcal/mol) successively. Pyrazole derivatives and the structure of pyrazolines are also effectively discussed in this paper for potential application as antibacterial agents due to their significant inhibitory activity. We were also able to predict a new potential inhibitor against a target of interest because to the result that we obtained.
Keywords	ADMET ; Escherichia coli ; Molecular Docking ; Lipinski’s rule ; Pyrazole and pyrazolines derivatives ; Chemistry ; QD1-999
Subject code	540
Language	English
Publishing date	2023-11-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: 2D-QSPR Study of Olfactive Thresholds for Pyrazine Derivatives Using DFT and Statistical Methods

Assia Belhassan / Samir Chtita / Tahar Lakhlifi / Mohammed Bouachrine

Emerging Science Journal, Vol 3, Iss 3, Pp 179-

2019 Volume 186

Abstract: In this study, we have established two-dimensional quantitative structure propriety relationships (2D-QSPR) model, for a group of 78 molecules based on pyrazine, these molecules were subjected to a 2D-QSPR analyze for their odors thresholds propriety ... ...

Abstract	In this study, we have established two-dimensional quantitative structure propriety relationships (2D-QSPR) model, for a group of 78 molecules based on pyrazine, these molecules were subjected to a 2D-QSPR analyze for their odors thresholds propriety using stepwise Multiple Linear Regression (MLR). The 35 parameters are calculated for the 78 studied compounds using the Gaussian 09W, ChemOffice and ChemSketch softwares. Quantum chemical calculations are used to calculate electronic and quantum chemical descriptors, using the density functional theory (B3LYP/6-31G (d) DFT) methods. The model was used to predict the odors thresholds propriety of the test and training set compounds, and the statistical results exhibited high internal and external consistency as demonstrated by the validation methods.
Keywords	Olfactive thresholds ; Pyrazine ; Quantitative Structure Propriety Relationship ; Density Functional Theory ; Multiple Linear Regression ; Technology (General) ; T1-995 ; Social sciences (General) ; H1-99
Subject code	541
Language	English
Publishing date	2019-06-01T00:00:00Z
Publisher	Ital Publication
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: 3D-QSAR Study of the Chalcone Derivatives as Anticancer Agents

Larbi ElMchichi / Assia Belhassan / Tahar Lakhlifi / Mohammed Bouachrine

Journal of Chemistry, Vol

2020 Volume 2020

Abstract: For their biological properties and particularly for their anticancer activities, chalcones are widely studied. In this work, we have submitted diverse sets of chalcone derivatives to the 3D-QSAR (3-dimensional quantitative structural-activity ... ...

Abstract	For their biological properties and particularly for their anticancer activities, chalcones are widely studied. In this work, we have submitted diverse sets of chalcone derivatives to the 3D-QSAR (3-dimensional quantitative structural-activity relationship) to study their anticancer activities against HTC116 (human colon cancer), relying on the 3-dimensional descriptors: steric and electrostatic descriptors for the CoMFA (comparative molecular field analysis) method and steric, electrostatic, hydrophobic, H-bond donor, and H-bond acceptor descriptors for the CoMSIA method. CoMFA as well as the CoMSIA model have encouraging values of the cross-validation coefficient (Q2) of 0.608 and 0.806 and conventional correlation coefficient (R2) of 0.960 and 0.934, respectively. Furthermore, values of R2test have been obtained as 0.75 and 0.90, respectively. Besides, y-randomization test was also performed to validate our 3D-QSAR models. Based on these satisfactory results, ten new compounds have been designed and predicted by in silico ADMET method. This study could expand the understanding of chalcone derivatives as anticancer agents and would be of great help in lead optimization for early drug discovery of highly potent anticancer activity.
Keywords	Chemistry ; QD1-999
Subject code	540
Language	English
Publishing date	2020-01-01T00:00:00Z
Publisher	Hindawi Limited
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Study of novel triazolo-benzodiazepine analogues as antidepressants targeting by molecular docking and ADMET properties prediction

Assia Belhassan / Hanane Zaki / Mohamed Benlyas / Tahar Lakhlifi / Mohammed Bouachrine

Heliyon, Vol 5, Iss 9, Pp e02446- (2019)

2019

Abstract: In this study, we have selected a series of a new family of molecules bearing Triazolo-benzodiazepines, an eleven membered heterocyclic ring has been studied for antidepression activity. Docking studies suggested that all the eleven ligands interacted ... ...

Abstract	In this study, we have selected a series of a new family of molecules bearing Triazolo-benzodiazepines, an eleven membered heterocyclic ring has been studied for antidepression activity. Docking studies suggested that all the eleven ligands interacted well within active site of Drosophila melanogaster dopamine transporter (dDAT) (PDB ID: 4M48). Most ligands formed H-bond with amino acid Phe43, Asp46, Asp475, Tyr123, Ser421 and/or Gln316 and also exhibited Pi and Pi-Pi interactions with amino acid residues Tyr124, Phe319, Phe43, Phe325, Ala479 and Val120. In silico ADME evaluations of compounds showed more than 96% intestinal absorption for all compounds. During in vitro Toxicity properties prediction, the Triazolo-benzodiazepines derivatives: M1, M2, M3 and M11 showed less toxicity than the other studied molecules against algae, for daphnia the molecules M1, M2, M3, M8, M10 and M11 showed less toxicity than the reference molecule (Nortriptyline).
Keywords	Theoretical chemistry ; Pharmaceutical chemistry ; Bioinformatics ; Biochemistry ; Triazolo-benzodiazepine ; Antidepressant activity ; Science (General) ; Q1-390 ; Social sciences (General) ; H1-99
Subject code	540
Language	English
Publishing date	2019-09-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: QSPR study of the retention/release property of odorant molecules in pectin gels using statistical methods

Assia Belhassan / Samir Chtita / Tahar Lakhlifi / Mohammed Bouachrine

Journal of Taibah University for Science, Vol 11, Iss 6, Pp 1030-

2017 Volume 1046

Abstract: The ACD/ChemSketch, MarvinSketch, and ChemOffice programmes were used to calculate several molecular descriptors of 51 odorant molecules (15 alcohols, 11 aldehydes, 9 ketones and 16 esters). The best descriptors were selected to establish the ... ...

Abstract	The ACD/ChemSketch, MarvinSketch, and ChemOffice programmes were used to calculate several molecular descriptors of 51 odorant molecules (15 alcohols, 11 aldehydes, 9 ketones and 16 esters). The best descriptors were selected to establish the Quantitative Structure-Property Relationship (QSPR) of the retention/release property of odorant molecules in pectin gels using Principal Components Analysis (PCA), Multiple Linear Regression (MLR), Multiple Non-linear Regression (MNLR) and Artificial Neural Network (ANN) methods We propose a quantitative model based on these analyses. PCA has been used to select descriptors that exhibit high correlation with the retention/release property. The MLR method yielded correlation coefficients of 0.960 and 0.958 for PG-0.4 (pectin concentration: 0.4% w/w) and PG-0.8 (pectin concentration: 0.8% w/w) media, respectively. Internal and external validations were used to determine the statistical quality of the QSPR of the two MLR models. The MNLR method, considering the relevant descriptors obtained from the MLR, yielded correlation coefficients of 0.978 and 0.975 for PG-0.4 and PG-0.8 media, respectively. The applicability domain of MLR models was investigated using simple and leverage approaches to detect outliers and outside compounds. The effects of different descriptors on the retention/release property are described, and these descriptors were used to study and design new compounds with higher and lower values of the property than the existing ones. Keywords: Odorant Molecules, Retention/Release, Pectin Gels, Quantitative Structure Property Relationship, Multiple Linear Regression, Artificial Neural Network
Keywords	Science (General) ; Q1-390
Subject code	540
Language	English
Publishing date	2017-11-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: QSPR Study of the Retention/release Property of Odorant Molecules in Water Using Statistical Methods

Assia Belhassan / Samir Chtita / Tahar Lakhlifi / Mohammed Bouachrine

Orbital: The Electronic Journal of Chemistry, Vol 9, Iss 4, Pp 234-

2017 Volume 247

Abstract: An integrated approach physicochemistry and structures property relationships has been carried out to study the odorant molecules retention/release phenomenon in the water. This study aimed to identify the molecular properties (molecular descriptors) ... ...

Abstract	An integrated approach physicochemistry and structures property relationships has been carried out to study the odorant molecules retention/release phenomenon in the water. This study aimed to identify the molecular properties (molecular descriptors) that govern this phenomenon assuming that modifying the structure leads automatically to a change in the retention/release property of odorant molecules. ACD/ChemSketch, MarvinSketch, and ChemOffice programs were used to calculate several molecular descriptors of 51 odorant molecules (15 alcohols, 11 aldehydes, 9 ketones and 16 esters). A total of 37 molecules (2/3 of the data set) were placed in the training set to build the QSPR models, whereas the remaining, 14 molecules (1/3 of the data set) constitute the test set. The best descriptors were selected to establish the quantitative structure property relationship (QSPR) of the retention/release property of odorant molecules in water using multiple linear regression (MLR), multiple non-linear regression (MNLR) and an artificial neural network (ANN) methods. We propose a quantitative model according to these analyses. The models were used to predict the retention/release property of the test set compounds, and agreement between the experimental and predicted values was verified. The descriptors showed by QSPR study are used for study and designing of new compounds. The statistical results indicate that the predicted values are in good agreement with the experimental results. To validate the predictive power of the resulting models, external validation multiple correlation coefficient was calculated and has both in addition to a performant prediction power, a favorable estimation of stability. DOI: http://dx.doi.org/10.17807/orbital.v9i4.978
Keywords	odorant molecules ; retention/release ; quantitative structure property relationship ; multiple linear regression ; artificial neural network ; Science ; Q ; Chemistry ; QD1-999
Subject code	540
Language	English
Publishing date	2017-10-01T00:00:00Z
Publisher	Universidade Federal de Mato Grosso do Sul
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Catastrophic Collision Between Obesity and COVID-19 Have Evoked the Computational Chemistry for Research in Silico Design of New CaMKKII Inhibitors Against Obesity by Using 3D-QSAR, Molecular Docking, and ADMET

Halima HAJJI / Fatima En-nahli / Ilham Aanouz / Hanane Zaki / Tahar Lakhlifi / Mohammed Aziz Ajana / Mohammed Bouachrine

Orbital: The Electronic Journal of Chemistry, Vol 13, Iss 4, Pp 316-

2021 Volume 327

Abstract: The purpose of the paper is to discuss the various methods and computational approaches, which are used in computer-aided drug design. For this reason, pyrimidine and azaindole derivatives have been used to study the inhibitory activity of CaMKKII. It is ...

Abstract	The purpose of the paper is to discuss the various methods and computational approaches, which are used in computer-aided drug design. For this reason, pyrimidine and azaindole derivatives have been used to study the inhibitory activity of CaMKKII. It is an enzyme that enters the brain to greatly reduce food from regulating the production of Ghrelin that is synthesized by the stomach and acts on the hypothalamus. The obtained results from different techniques such as the 3D-QSAR, molecular docking, and ADMET were applied to study series of new CaMKKII inhibitors of 23 molecules based on pyrimidine and azaindole derivatives. The CoMFA and CoMSIA models were used in 19 molecules in the training set that give high values of determination coefficient R 2 0.970 and 0.902 respectively, and significant values of Leave-One-Out cross-validation coefficient Q 2 0.614 and 0.583 respectively. The predictive capacity of this model was examined by external validation though using a test set of four compounds with a predicted determination coefficient test R 2 ext of 0.778 and 0.972 successively. The method of alignment adapted with the appropriate parameters gave credible models. The CoMFA and CoMSIA models produce the contour maps which were used to define a 3D-QSAR mode. DOI: http://dx.doi.org/10.17807/orbital.v13i4.1608
Keywords	3d-qsar ; admet ; camkkii inhibitors ; molecular docking ; obesity ; Science ; Q ; Chemistry ; QD1-999
Subject code	540
Language	English
Publishing date	2021-10-01T00:00:00Z
Publisher	Universidade Federal de Mato Grosso do Sul
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Molecular Docking, Drug likeness Studies and ADMET prediction of Flavonoids as Platelet-Activating Factor (PAF) Receptor Binding

Mohammed BOUACHRINE / Larbi Elmchichi / Abdellah El Aissouq / Assia BELHASSAN / Hanane Zaki / Abdelkrim Ouammou / Tahar Lakhlifi

Chemical Review and Letters, Vol 4, Iss 3, Pp 145-

2021 Volume 152

Abstract: Studies and scientific research indicate that the platelet-activating factor (PAF) is a major pro-inflammatory mediator in the initiation and development of cancer. There is also evidence confirming that PAF is an integral part of suppressing the immune ... ...

Abstract	Studies and scientific research indicate that the platelet-activating factor (PAF) is a major pro-inflammatory mediator in the initiation and development of cancer. There is also evidence confirming that PAF is an integral part of suppressing the immune system and promoting the appearance of a malignant tumor. For this reason, it is useful to analyze the molecular docking data of eleven flavonoids derivatives isolated from the active leaf extracted from chromolaena odorata with their anti-PAF activity. As a result, it is evident that the natural product of flavonoids may have a positive effect in the development of both therapeutic and preventive agents for platelet activating factor (PAF) antagonist and suggests potential guidelines for the design of PAF inhibitors. Based on the docking score analysis, drug likeness study, and ADMET prediction. We found that six compounds respect all drug-likeness rules and can be used as a potent molecule for inhibition of platelet activating factor (PAF).
Keywords	flavonoids ; platelet-activating factor (paf) ; docking study ; admet ; Chemistry ; QD1-999
Subject code	306
Language	English
Publishing date	2021-05-01T00:00:00Z
Publisher	Iranian Chemical Science and Technologies Association
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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