2D- and 3D-QSAR and Molecular Docking of 2-Hydroxyisoquinoline-1,3-Diones as Inhibitors of HIV Reverse Transcriptase

2020 ◽  
Vol 5 (4) ◽  
pp. 32-52
Author(s):  
Ilham Aanouz ◽  
Khalil El Khatabi ◽  
Assia BelHassan ◽  
Tahar Lakhlifi ◽  
Mostafa Elidrissi ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Molecular Similarity ◽  
Similarity Index ◽  
Principal Component ◽  
3D Qsar ◽  
Hiv Reverse Transcriptase ◽  
Training Set ◽  
Qsar Analysis ◽  
Contour Maps ◽  
2D And 3D

The main objective of this study is to develop 2D- and 3D-QSAR statistical models for a series consisting of 28 molecules. The authors started with a 2D study based on principal component analysis (PCA), multiple linear regression (RLM), and nonlinear regression (RNLM). The models were developed using 28 molecules with a pIC50 between 5.70 and 6.70. Then they applied 3D-QSAR analysis based on the partial least squares (PLS) method. For 3D-QSAR, they used the molecular field comparative analysis (CoMFA) and comparative molecular similarity index (CoMSIA) methods. For this analysis, they have worked on a training set of 24 compounds, which then give acceptable and reliable values of Q2 (0.791 and 0.538, respectively) and R2 (0.974 and 0.98, respectively). To determine the quantitative 3D-QSAR, the interpretations were based on the contour maps which are produced by the CoMFA and CoMSIA models. In addition, molecular docking is also one of the most important methods for confirming the binding interactions of predicted molecules with their receptors.

Design of Dual COX-2 and 5-LOX Inhibitors with Iron-Chelating Properties Using Structure-Based and Ligand-Based Methods

2021 ◽  
Vol 18 ◽  
Author(s):  
Jelena Bošković ◽  
Dušan Ružić ◽  
Olivera Čudina ◽  
Katarina Nikolic ◽  
Vladimir Dobričić
Keyword(s):  
Molecular Docking ◽  
External Validation ◽  
Three Dimensional ◽  
3D Qsar ◽  
Quantitative Structure Activity Relationship ◽  
Docking Studies ◽  
Qsar Analysis ◽  
In Silico Admet ◽  
Cox 2 ◽  
Lox Inhibitors

Background: Inflammation is common pathogenesis of many diseases progression, such as malignancy, cardiovascular and rheumatic diseases. The inhibition of the synthesis of inflammatory mediators by modulation of cyclooxygenase (COX) and lipoxygenase (LOX) pathways provides a challenging strategy for the development of more effective drugs. Objective: The aim of this study was to design dual COX-2 and 5-LOX inhibitors with iron-chelating properties using a combination of ligand-based (three-dimensional quantitative structure-activity relationship (3D-QSAR)) and structure-based (molecular docking) methods. Methods: The 3D-QSAR analysis was applied on a literature dataset consisting of 28 dual COX-2 and 5-LOX inhibitors in Pentacle software. The quality of developed COX-2 and 5-LOX 3D-QSAR models were evaluated by internal and external validation methods. The molecular docking analysis was performed in GOLD software, while selected ADMET properties were predicted in ADMET predictor software. Results: According to the molecular docking studies, the class of sulfohydroxamic acid analogues, previously designed by 3D-QSAR, was clustered as potential dual COX-2 and 5-LOX inhibitors with iron-chelating properties. Based on the 3D-QSAR and molecular docking, 1j, 1g, and 1l were selected as the most promising dual COX-2 and 5-LOX inhibitors. According to the in silico ADMET predictions, all compounds had an ADMET_Risk score less than 7 and a CYP_Risk score lower than 2.5. Designed compounds were not estimated as hERG inhibitors, and 1j had improved intrinsic solubility (8.704) in comparison to the dataset compounds (0.411-7.946). Conclusion: By combining 3D-QSAR and molecular docking, three compounds (1j, 1g, and 1l) are selected as the most promising designed dual COX-2 and 5-LOX inhibitors, for which good activity, as well as favourable ADMET properties and toxicity, are expected.

Quinoxalinones Based Aldose Reductase Inhibitors: 2D and 3D‐QSAR Analysis

2019 ◽  
Vol 38 (8-9) ◽  
pp. 1800149
Author(s):  
Vijay H. Masand ◽  
Nahed N. Elsayed ◽  
Sumersingh D. Thakur ◽  
Nandkishor Gawhale ◽  
Mithilesh M. Rathore
Keyword(s):  
Aldose Reductase ◽  
3D Qsar ◽  
Qsar Analysis ◽  
Aldose Reductase Inhibitors ◽  
Reductase Inhibitors ◽  
2D And 3D

scholarly journals 2D AND 3D-QSAR ANALYSIS OF AMINO (3-((3, 5-DIFLUORO-4-METHYL-6-PHENOXYPYRIDINE-2-YL) OXY) PHENYL) METHANIMINIUM DERIVATIVES AS FACTOR XA INHIBITOR

2019 ◽  
pp. 104-114
Author(s):  
Smita Suhane ◽  
A. G. Nerkar ◽  
Kumud Modi ◽  
Sanjay D. Sawant
Keyword(s):  
Factor Xa ◽  
3D Qsar ◽  
Qsar Model ◽  
Regression Method ◽  
Field Analysis ◽  
Factor Xa Inhibitors ◽  
Nearest Neighbour ◽  
Qsar Analysis ◽  
Qsar Models ◽  
2D And 3D

Objective: The main objective of the present study was to evolve a novel pharmacophore of methaniminium derivatives as factor Xa inhibitors by developing best 2D and 3D QSAR models. The models were developed for amino (3-((3, 5-difluoro-4-methyl-6-phenoxypyridine-2-yl) oxy) phenyl) methaniminium derivatives as factor Xa inhibitors. Methods: With the help of Marvin application, 2D structures of thirty compounds of methaniminium derivatives were drawn and consequently converted to 3D structures. 2D QSAR using multiple linear regression (MLR) analysis and PLS regression method was performed with the help of molecular design suite VLife MDS 4.3.3. 3D QSAR analysis was carried out using k-Nearest Neighbour Molecular Field Analysis (k-NN-MFA). Results: The most significant 2D models of methaniminium derivatives calculated squared correlation coefficient value 0.8002 using multiple linear regression (MLR) analysis. Partial Least Square (PLS) regression method was also employed. The results of both the methods were compared. In 2D QSAR model, T_C_O_5, T_2_O_2, s log p, T_2_O_1 and T_2_O_6 descriptors were found significant. The best 3D QSAR model with k-Nearest Neighbour Molecular Field Analysis have predicted q2 value 0.8790, q2_se value 0.0794, pred r2 value 0.9340 and pred_r2 se value 0.0540. The stepwise regression method was employed for anticipating the inhibitory activity of this class of compound. The 3D model demonstrated that hydrophobic, electrostatic and steric descriptors exhibit a crucial role in determining the inhibitory activity of this class of compounds. Conclusion: The developed 2D and 3D QSAR models have shown good r2 and q2 values of 0.8002 and 0.8790 respectively. There is high agreement in inhibitory properties of experimental and predicted values, which suggests that derived QSAR models have good predicting properties. The contour plots of 3D QSAR (k-NN-MFA) method furnish additional information on the relationship between the structure of the compound and their inhibitory activities which can be employed to construct newer potent factor Xa inhibitors.

MOLECULAR MODELING OF 5‐[(AMIDOBENZYL)OXY]‐ NICOTINAMIDES AS SIRTUIN 2 INHIBITORS USING ALIGNMENT- (IN)DEPENDENT 3D-QSAR ANALYSIS AND MOLECULAR DOCKING

2021 ◽  
Author(s):  
Nemanja Djokovic ◽  
◽  
Ana Postolovic ◽  
Katarina Nikolic
Keyword(s):  
Molecular Docking ◽  
Structural Similarity ◽  
3D Qsar ◽  
Quantitative Structure Activity Relationship ◽  
Study Data ◽  
Rational Drug Design ◽  
Qsar Study ◽  
Data Set ◽  
Qsar Analysis ◽  
Ligand Interactions

The group of 5‐[(amidobenzyl)oxy]‐nicotinamides represents promising group of sirtuin 2 (SIRT2) inhibitors. Despite structural similarity, representatives of this group of inhibitors displayed versatile mechanisms of inhibition which hamper rational drug design. The aim of this research was to form a 3D-QSAR (3D-Quantitative Structure-Activity Relationship) model, define the pharmacophore of this subgroup of SIRT2 inhibitors, define the mode of protein-ligand interactions and design new compounds with improved predicted activity and pharmacokinetics. For the 3D-QSAR study, data set was generated using structures and activities of 166 5‐[(amidobenzyl)oxy]‐nicotinamides. 3D-conformations of compounds were optimized, alignment-independent GRIND2 descriptors were calculated and 3D-QSAR PLS models were generated using 70% of data set. To investigate bioactive conformations of inhibitors, molecular docking was used. Molecular docking analysis identified two clusters of predicted bioactive conformations which is in alignment with experimental observations. The defined pharmacophoric features were used to design novel inhibitors with improved predicted potency and ADMET profiles.

Analysis of B-Raf $$^{\mathrm{V600E}}$$ V 600 E inhibitors using 2D and 3D-QSAR, molecular docking and pharmacophore studies

2015 ◽  
Vol 19 (4) ◽  
pp. 915-930 ◽  
Author(s):  
Reza Aalizadeh ◽  
Eslam Pourbasheer ◽  
Mohammad Reza Ganjali
Keyword(s):  
Molecular Docking ◽  
3D Qsar ◽  
2D And 3D
Sign in / Sign up

Export Citation Format

Share Document