QSAR study of isonicotinamides derivatives as Alzheimr's disease inhibitors using PLS-R and ANN methods

Aissouq, Abdellah El; Toufik, Hamid; Lamchouri, Fatima; Stitou, Mourad; Ouammou, Abdelkrim

doi:10.1109/isacs48493.2019.9068919

Cited by 9 publications

(5 citation statements)

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“…Calculating molecular descriptors is an essential step in QSAR research since they quantitatively represent the chemical information associated with compounds. 12 In this study, a set of 354 descriptors was generated using molecular operating environment (MOE) software (https:// www.chemcomp.com). The descriptors with identical or null values were eliminated, and the remaining ones were chosen.…”

Section: D-qsar Modelmentioning

confidence: 99%

Computer-aided drug design applied to a series of pyridinyl imidazole derivatives targeting p38α MAP kinase: 2D-QSAR, docking, MD simulation, and ADMET investigations

et al. 2022

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Section: D-qsar Modelmentioning

confidence: 99%

Computer-aided drug design applied to a series of pyridinyl imidazole derivatives targeting p38α MAP kinase: 2D-QSAR, docking, MD simulation, and ADMET investigations

et al. 2022

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“…1 Where r 2 is the multiple correlation coefficient of one descriptor's effect regressed on the remaining molecular descriptors. If the VIF value is greater than 5 (VIF > 5), multicollinearity is very high [39].…”

Section: D-qsar Analysis 221 Molecular Descriptors Calculationmentioning

confidence: 99%

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

2021

Turk J Chem

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Computer-aided drug design (CADD) approaches have recently become essential in drug discovery. These techniques proved to be effective in various stages of the drug development process, reducing both the cost and time required to develop a drug compared to conventional methods [21]. In general, CADD approaches are classified into two types: structure-based drug design (SBDD) and ligand-based drug design (LBDD). When the 3D structure of the protein is

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“…To evaluate the significance of generated models and their precise predictive capacity, internal and external validations were used [35,36]. The best HepG-2 and MCF-7models revealed a leave one out cross-validation coefficients R 2 cv [37] values of 0.618 and 0.509, respectively.…”

Section: Internal and External Validationmentioning

confidence: 99%

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

Kasmi

Hadaji

Chedadi

et al. 2020

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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. The predictive power of these models has been confirmed by internal and external validation. The Leverage method was used to determine the domain of applicability of the 2D-QSAR models developed. The results indicate that the best QSAR model is the one that links the 2D descriptors with the CDK inhibitory activity of the cell line (HepG-2) R 2 = 0.748, R 2 cv = 0.618, MSE = 0.03 for the learning series and R 2 = 0.73, MSE = 0.18 for the test series. This model implies that coumarin inhibitory activity is strongly related to dipole moment and the number of hydrogen bond donors. The results obtained suggest the importance of studying structure-activity relationships as a principal axis in drug design. The docking procedure using AutoDOCK Tools was also used to understand the mechanisms of molecular interactions and consequently, to develop new inhibitors.

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QSAR study of isonicotinamides derivatives as Alzheimr's disease inhibitors using PLS-R and ANN methods

Cited by 9 publications

References 20 publications

Computer-aided drug design applied to a series of pyridinyl imidazole derivatives targeting p38α MAP kinase: 2D-QSAR, docking, MD simulation, and ADMET investigations

Computer-aided drug design applied to a series of pyridinyl imidazole derivatives targeting p38α MAP kinase: 2D-QSAR, docking, MD simulation, and ADMET investigations

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

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

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