Three Dimensional Quantitative Structure Activity Relationship and Molecular Docking Studies of Flavonoids as Reverse Transcriptase Inhibitors

2021 ◽  
Vol 6 (1) ◽  
pp. 33-39
Author(s):  
Bikash Kumar Sarkar ◽  
Nabanita Giri
Keyword(s):  
Correlation Coefficient ◽  
Three Dimensional ◽  
Predictive Ability ◽  
Binding Pocket ◽  
Quantitative Structure Activity Relationship ◽  
Docking Studies ◽  
Field Analysis ◽  
Comfa Model ◽  
Bonding Interaction ◽  
Hiv 1

A set of 29 flavonoid molecules are used to generate comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models. The best CoMFA model showed a cross-validated correlation coefficient (q2) = 0.762, noncross- validated correlation coefficient (r2) = 0.939, standard error of estimate (S) = 0.038 and F = 396. And that for CoMSIA model were q2 = 0.758, r2 = 0.957, S = 0.063 and F = 236. The models show a high predictive ability, validated by 11 favonoid molecules. The docking studies shows the hydrogen bonding interaction is mostly responsible for binding of the flavonoids molecules in the binding pocket of HIV 1-RT protein (3HVT.pdb).

3D-QSAR Studies of S-DABO Derivatives as Non-nucleoside HIV-1 Reverse Transcriptase Inhibitors

2019 ◽  
Vol 16 (8) ◽  
pp. 868-881
Author(s):  
Yueping Wang ◽  
Jie Chang ◽  
Jiangyuan Wang ◽  
Peng Zhong ◽  
Yufang Zhang ◽  
...  
Keyword(s):  
Reverse Transcriptase ◽  
Three Dimensional ◽  
Predictive Ability ◽  
3D Qsar ◽  
Binding Mode ◽  
Quantitative Structure Activity Relationship ◽  
Field Analysis ◽  
Reverse Transcriptase Inhibitors ◽  
Qsar Studies ◽  
Hiv 1

Background: S-dihydro-alkyloxy-benzyl-oxopyrimidines (S-DABOs) as non-nucleoside reverse transcriptase inhibitors have received considerable attention during the last decade due to their high potency against HIV-1. Methods: In this study, three-dimensional quantitative structure-activity relationship (3D-QSAR) of a series of 38 S-DABO analogues developed in our lab was studied using Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA). The Docking/MMFF94s computational protocol based on the co-crystallized complex (PDB ID: 1RT2) was used to determine the most probable binding mode and to obtain reliable conformations for molecular alignment. Statistically significant CoMFA (q2=0.766 and r2=0.949) and CoMSIA (q2=0.827 and r2=0.974) models were generated using the training set of 30 compounds on the basis of hybrid docking-based and ligand-based alignment. Results: The predictive ability of CoMFA and CoMSIA models was further validated using a test set of eight compounds with predictive r2 pred values of 0.843 and 0.723, respectively. Conclusion: The information obtained from the 3D contour maps can be used in designing new SDABO derivatives with improved HIV-1 inhibitory activity.

3D-QSAR AND DOCKING STUDIES OF NOVEL QUINAZOLINE ANALOGUES AS ORAL INHIBITORS TOWARDS AP-1 AND NF-κB

2009 ◽  
Vol 08 (03) ◽  
pp. 373-384
Author(s):  
LI QIAN ◽  
HAI-LIANG LU ◽  
SI-YAN LIAO ◽  
TI-FANG MIAO ◽  
YONG SHEN ◽  
...  
Keyword(s):  
Molecular Design ◽  
Three Dimensional ◽  
Predictive Ability ◽  
3D Qsar ◽  
Quantitative Structure Activity Relationship ◽  
Docking Studies ◽  
Field Analysis ◽  
Activator Protein 1 ◽  
Mechanism Analysis ◽  
Qsar Study

Three-dimensional quantitative structure-activity relationship (3D-QSAR) and Docking studies of novel quinazoline analogues, which are oral potential inhibitors towards the activator protein-1 (AP-1) and nuclear factor kappa B (NF-κB), have been carried out. The 3D-QSAR study based on the comparative molecular field analysis (CoMFA) shows the established model having a significant statistical quality and excellent predictive ability, in which the correlation coefficient R is 0.972 and cross-validation coefficient q2 is 0.619. The Docking results also show a considerable correlation (or trend) between the energy scores and the corresponding experimental values for these compounds at some sites. Meanwhile, it is very interesting to find the binding sites just fall on the joint regions between AP-1 (or NF-κB) and DNA. It may be the reason that the quinazoline analogues have inhibition function because their existence on these joint regions can effectively prevent free AP-1 and NF-κB from binding to DNA. Based on the established 3D-QSAR and Docking analyses, six new compounds of quinazoline analogues with higher inhibitory activities were theoretically designed and presented. The above results can offer some valuable theoretical references for the pharmaceutical molecular design as well as the action mechanism analysis.

QSAR Studies on Thiazole Derivatives as HCV NS5A Inhibitors via CoMFA and CoMSIA Methods

2019 ◽  
Vol 16 (4) ◽  
pp. 453-460 ◽  
Author(s):  
Jiayu Li ◽  
Wenyue Tian ◽  
Diaohui Gao ◽  
Yuying Li ◽  
Yiqun Chang ◽  
...  
Keyword(s):  
Nonstructural Protein ◽  
External Validation ◽  
Three Dimensional ◽  
3D Qsar ◽  
Quantitative Structure Activity Relationship ◽  
Field Analysis ◽  
Thiazole Derivatives ◽  
Hydrogen Bond Acceptor ◽  
Qsar Studies ◽  
Comfa Model

Background: Hepatitis C Virus (HCV) infection is the major cause of hepatitis after transfusion. And HCV Nonstructural Protein 5A (NS5A) inhibitors have become a new hotspot in the study of HCV inhibitors due to their strong antiviral activity, rapid speed of viral removing and broad antiviral spectrum. Methods: Forty-five NS5A inhibitors were chosen to process three-dimensional quantitative structure- activity relationship (3D-QSAR) by using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models. A training set consisting of 30 compounds was applied to establish the models and a test set consisting of 15 compounds was applied to do the external validation. Results: The CoMFA model predicted a q2 value of 0.607 and an r2 value of 0.934. And the CoMSIA model predicted a q2 value of 0.516 and an r2 value of 0.960 established on the effects of steric, electrostatic, hydrophobic and hydrogen-bond acceptor. 0.713 and 0.939 were the predictive correlation co-efficients (r2pred) of CoMFA and CoMSIA models, respectively. Conclusion: These conclusions provide a theoretical basis for drug design and screening of HCV NS5A complex inhibitors.

Non-Nucleoside HIV-1 Reverse Transcriptase Inhibition Activity of a Series of Dihydroalkoxybenzyloxopyrimidine (DABO) Derivatives: CoMFA, CoMSIA and Docking Studies

2020 ◽  
Vol 5 (3) ◽  
pp. 265-272
Author(s):  
Bikash Kumar Sarkar ◽  
Ananda Sarkar ◽  
Atish Dipankar Jana
Keyword(s):  
3D Qsar ◽  
Docking Study ◽  
Binding Pocket ◽  
Qsar Model ◽  
Docking Studies ◽  
Field Analysis ◽  
Qsar Studies ◽  
3D Space ◽  
Pyrimidine Moiety ◽  
Hiv 1

CoMFA, CoMSIA and molecular docking studies have been carried out for a set of 42 dihydroalkoxybenzyloxopyrimidine (DABO) derivatives for which anti-HIV activity values are available. In 3D-QSAR studies-comparative molecular field analysis (CoMFA) as well as comparative molecular similarity indices analysis (CoMSIA) have been performed. Both the QSAR model nicely explains the inhibitory activities of DABO derivatives as well as provides molecular level insights revealing which regions in 3D space around the molecules are more important for their anti HIVactivities. These models have a quite high square correlation coefficient (r2 = 0.817 for CoMFA and r2 = 0.943 for CoMSIA). A docking study of the highest active molecule into the binding site of the protein HIV-1 RT (PDB ID-1RT1) shows that hydrogen bonding between pyrimidine moiety of the ligand and the Lysine-101 moiety along with Valine-106 moiety of the HIV protein play most important role for stabilizing the ligand in the binding pocket of the protein.

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.

QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIP MODELING FOR PREDICTION OF PYRIDINE SUBSTITUTED ANALOGUES WITH K-NEAREST NEIGHBOR STUDIES

INDIAN DRUGS ◽  
2017 ◽  
Vol 54 (10) ◽  
pp. 16-22
Author(s):  
M. C. Sharma ◽  
◽  
D.V. Kohli
Keyword(s):  
Correlation Coefficient ◽  
Quantitative Relationship ◽  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Field Analysis ◽  
Activity Relationship ◽  
Quantitative Structure ◽  
Angiotensin Ii Receptor ◽  
K Nearest Neighbor ◽  
Structure Activity

A quantitative structure activity relationship study was performed on a series of imidazo[4,5-b]pyridine substituted compounds as angiotensin II receptor antagonists for establishing quantitative relationship between activity and their physicochemical properties. The best quantitative structure activity relationship model was generated with correlation coefficient of 0.8318, cross validated correlation coefficient of 0.7142 and r2 for external test set 0.7965. Molecular field analysis was used to construct the best 3D-QSAR model using PLS method, showing good correlative and predictive capabilities in terms of q2 = 0.7264 and pred_r2 = 0.8164. These results will be useful for the design of new antihypertensive molecules.

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