PREDICTIVE QSAR MODELING OF PYRIDAZINYL DERIVATIVES USING K-NEAREST NEIGHBOR AND PHARMACOPHORE APPROACH

INDIAN DRUGS ◽  
2017 ◽  
Vol 54 (07) ◽  
pp. 10-17
Author(s):  
M.C. Sharma ◽  
◽  
D.V. Kohli
Keyword(s):  
Correlation Coefficient ◽  
Nearest Neighbor ◽  
Predictive Ability ◽  
3D Qsar ◽  
Qsar Model ◽  
Field Analysis ◽  
Angiotensin Ii Receptor ◽  
K Nearest Neighbor ◽  
Qsar Modeling ◽  
Leave One Out

This study was carried out elucidate the structural properties required for pyridazinyl derivatives to exhibit angiotensin II receptor activity. The best 2D-QSAR model was selected, having correlation coefficient r2 = 0.8156, cross validated squared correlation coefficient q2 = 0.7348 and predictive ability of the selected model was also confirmed by leave one out cross validation method. Further analysis was carried out using 3D-QSAR method k-nearest neighbor molecular field analysis approach; a leave-one-out crossvalidated correlation coefficient of 0.7188 and a predictivity for the external test set (0.7613) were obtained. By studying the QSAR models, one can select the suitable substituent for active compound with maximum potency.

THREE-DIMENSIONAL QSAR MODELING BENZIMIDAZOLE ANALOGUES USING THE K-NEAREST NEIGHBOR METHOD

INDIAN DRUGS ◽  
2019 ◽  
Vol 56 (12) ◽  
pp. 62-67
Author(s):  
M. C Sharma ◽  
◽  
D. V. Kohli
Keyword(s):  
Nearest Neighbor ◽  
Three Dimensional ◽  
Antihypertensive Agents ◽  
3D Qsar ◽  
Good Alternative ◽  
Qsar Model ◽  
Field Analysis ◽  
K Nearest Neighbor ◽  
Qsar Modeling ◽  
Qsar Studies

We undertook the three-dimensional (3D) QSAR studies of a series of benzimidazole analogues to elucidate the structural properties required for angiotensin II. The 3D-QSAR studies were performed using the stepwise, simulated annealing (SA) and genetic algorithm (GA) selection k-nearest neighbor molecular field analysis approach; a leave-one-out cross-validated correlation coefficient q2 = 0.8216 and a pred_r2 = 0.7852 were obtained. The 3D QSAR model is expected to provide a good alternative to predict the biological activity prior to synthesis as antihypertensive agents.

DEVELOPMENT OF A CREDIBLE QSAR AND K NEAREST NEIGHBOR MODELS FOR IMIDAZOLYL DERIVATIVES

INDIAN DRUGS ◽  
2018 ◽  
Vol 55 (05) ◽  
pp. 7-13
Author(s):  
M. C Sharma ◽  
Keyword(s):  
Correlation Coefficient ◽  
Nearest Neighbor ◽  
Antihypertensive Agents ◽  
3D Qsar ◽  
Qsar Model ◽  
Structural Features ◽  
Field Analysis ◽  
Molecular Field ◽  
K Nearest Neighbor ◽  
Molecular Field Analysis

Quantitative Structure-Activity Relationship studies were performed for correlating the imidazolyl derivatives and their activity using molecular modeling studies. The statistically significant best 2D model was having correlation coefficient = 0.8221 and cross-validated squared correlation coefficient = 0.7534 with external predictive ability of pred_r2 = 0.7716. Molecular field analysis was used to construct the best 3D-QSAR model showing good correlative and predictive capabilities in terms of q2 =0.6781 and pred_r2 =0.7299. The molecular field analysis (MFA) contour plots provided further understanding of the relationship between structural features of Imidazolyl derivatives and their activities which should be applicable to design newer potential antihypertensive agents.

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.

scholarly journals 3D QSAR AND DOCKING STUDY OF INDOLE DERIVATIVES AS SELECTIVE COX-2 INHIBITORS

2019 ◽  
pp. 84-92
Author(s):  
Rajashree Chavan ◽  
HARINATH MORE
Keyword(s):  
Binding Affinity ◽  
Correlation Coefficient ◽  
3D Qsar ◽  
Docking Study ◽  
Field Analysis ◽  
Indole Derivatives ◽  
K Nearest Neighbor ◽  
Qsar Study ◽  
Cox 2 ◽  
Anti Inflammatory

Objective: Non-steroidal anti-inflammatory agents (NSAIDs) continue to be one of the most widely used groups of therapeutic agents. QSAR (quantitative structure-activity relationship) approach is a very useful and widespread technique for drug design. 3D QSAR facilitates evaluation of three-dimensional molecular fields around molecules and generates a relationship of these fields' values with the activity. Methods: 3D QSAR study was performed on selected twenty-four compounds from synthesized indole derivatives using the stepwise variable selection k-nearest neighbor (kNN) molecular field analysis approach for indicating the contribution of the steric and electronic field for activity. The docking study was performed to further confirm the binding affinity of synthesized molecules (ligands) to COX-2 enzyme as well as to study binding nature. Results: Statistically significant model was generated using VLife Molecular Design Suite 3.5 software with cross-validated correlation coefficient q2 of 0.9461 and high predictive correlation coefficient (Pred_r2) of 0.8782 indicating that the model is robust. The results of docking study suggest that the synthesized compounds have a comparable binding affinity with the COX-2 enzyme. Conclusion: The present study may prove to be helpful in the development and optimization of existing indole derivatives as anti-inflammatory agents with selective COX-2 inhibition.

Molecular Docking and 3D-QSAR Studies of 4-Phenylpiperidine Derivatives as μ-Opioid Agonists

2011 ◽  
Vol 361-363 ◽  
pp. 263-267 ◽  
Author(s):  
Ming Liu ◽  
Wen Xiang Hu ◽  
Xiao Li Liu
Keyword(s):  
Electrostatic Interactions ◽  
Biological Activities ◽  
3D Qsar ◽  
Qsar Model ◽  
Field Analysis ◽  
Qsar Studies ◽  
Chemical Structures ◽  
Opioid Agonists ◽  
Qsar Models ◽  
Leave One Out

A predictive 3D-QSAR model which correlates the biological activities with the chemical structures of a series of 4-phenylpiperidine derivatives as μ opioid agonists was developed by means of comparative molecular field analysis (CoMFA). The stabilities of the 3D-QSAR models were verified by the leave-one-out cross-validation method. Moreover, the predictive capabilities of the models were validated by an external test set. Best predictions were obtained with CoMFA standard model(q2=0.504, N=6, r2=0.968) which revealed how steric and electrostatic interactions contribute to agonists bioactivities, and provided us with important information to understand the interaction of agonists and μ opioid receptor .

QSAR STUDIES ON HUMAN CARBONIC ANHYDRASE II INHIBITORS

INDIAN DRUGS ◽  
2021 ◽  
Vol 58 (11) ◽  
pp. 18-28
Author(s):  
Tanvi V. Wani ◽  
◽  
Mrunmayee P. Toraskar
Keyword(s):  
Carbonic Anhydrase ◽  
Nearest Neighbor ◽  
3D Qsar ◽  
Field Analysis ◽  
Molecular Field ◽  
Carbonic Anhydrase Ii ◽  
Carbonic Anhydrases ◽  
K Nearest Neighbor ◽  
Qsar Studies ◽  
Molecular Field Analysis

Carbonic anhydrase II is one of the forms of human α carbonic anhydrases which are ubiquitous metalloenzymes that catalyze inter-conversion of carbon dioxide and water to bicarbonate and proton, overexpression of which leads to disorders such as glaucoma. 2D and 3D Quantitative Structure Activity Relationship studies were carried out on previously synthesized series of sulfanilamide derivatives by VLife MDS software using stepwise variable, multi-linear regression and k-nearest neighbor molecular field analysis methods. 2D-QSAR model depicts contribution of halogens (such as chlorine and fluorine), methylene and oxygen atoms to inhibition of human carbonic anhydrases II activity. Using k-nearest neighbor molecular field analysis method two 3D-QSAR models (model A and B) were generated from which model A was found to be the best validated model with q2 (0.9494), pred_r2 (0.7367) and q2 _ se (0.2037). It displayed the fact that the inhibitory action of sulfanilamide derivatives against human carbonic anhydrases II is influenced by hydrophobicity and electro positivity.

scholarly journals 3D-QSAR Study of Indol-2-yl Ethanones Derivatives as Novel Indoleamine 2,3-Dioxygenase (IDO) Inhibitors

2012 ◽  
Vol 9 (4) ◽  
pp. 1753-1759 ◽  
Author(s):  
Kamlendra S. Bhadoriya ◽  
Shailesh V. Jain ◽  
Sanjaykumar B. Bari ◽  
Manish L. Chavhan ◽  
Kuldeep R. Vispute
Keyword(s):  
Nearest Neighbor ◽  
External Validation ◽  
3D Qsar ◽  
Qsar Model ◽  
Field Analysis ◽  
Qsar Study ◽  
Internal Validation ◽  
Contour Maps ◽  
Model Classification ◽  
Ido Inhibitors

3D-QSAR approach usingkNN-MFA was applied to a series of Indol-2-yl ethanones derivatives as novel IDO inhibitors. For the purpose, 22 compounds were used to develop models. To elucidate the structural properties required for IDO inhibitory activity, we report herek-nearest neighbor molecular field analysis (kNN-MFA)-based 3D-QSAR model for Indol-2-yl ethanones derivatives as novel IDO inhibitors. Overall model classification accuracy was 76.27% (q2= 0.7627, representing internal validation) in training set and 79.35% (pred_r2= 0.7935, representing external validation) in test set using sphere exclusion and forward as a method of data selection and variable selection, respectively. Contour maps using this approach showed that hydrophobic and steric effects dominantly determine binding affinities. The information rendered by 3D-QSAR model may lead to a better understanding of structural requirements of IDO inhibitors and can help in the design of novel potent molecules.

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