DEVELOPMENT OF A ROBUST QSAR MODEL OF ANGIOTENSIN RECEPTOR REVEALS A K NEAREST NEIGHBOR APPLICABLE TO DIVERSE SCAFFOLDS

INDIAN DRUGS ◽  
2017 ◽  
Vol 54 (06) ◽  
pp. 30-36
Author(s):  
M. C Sharma ◽  
◽  
D. V. Kohli
Keyword(s):  
Biological Activity ◽  
Nearest Neighbor ◽  
3D Qsar ◽  
Qsar Model ◽  
Partial Least Square ◽  
Least Square ◽  
Positive Contribution ◽  
K Nearest Neighbor ◽  
Qsar Studies ◽  
2D Qsar

Quantitative structure–activity relationship (QSAR) studies were performed on quinazolinone analogues for prediction of antihypertensive activity. The best significant 2D-QSAR model having r2 = 0.8118 and pred_r2 = 0.7428 was developed by stepwise-partial least square method. k-nearest neighbor molecular field analysis was used to construct the best 3D-QSAR model, showing good correlative and predictive capabilities in terms of q2 = 0.7388 and pred_r2 = 0.6983. Results reveal that the 2D-QSAR studies signify positive contribution of SssOE index and SsCH3 count towards the biological activity. The results have showed that electronegative groups are necessary for activity and halogen, bulky, less bulky groups in quinazolinones nucleus enhanced the biological activity. The information rendered by 2D- and 3D-QSAR models may lead to a better understanding of structural requirements of substituted quinazolinones derivatives and also aid in designing novel potent antihypertensive molecules.

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.

DESIGN OF POTENTIAL CYCLOOXYGENASE INHIBITORS USING PHARMACOPHORE OPTIMIZATION BY MOLECULAR MODELING STUDIES

INDIAN DRUGS ◽  
2015 ◽  
Vol 52 (12) ◽  
pp. 16-22
Author(s):  
S. S Todkar ◽  
◽  
A. H. Hoshmani
Keyword(s):  
Molecular Modeling ◽  
Nearest Neighbor ◽  
3D Qsar ◽  
Field Analysis ◽  
K Nearest Neighbor ◽  
Qsar Studies ◽  
2D Qsar ◽  
Molecular Modeling Studies ◽  
Cox 2 ◽  
Cox 2 Inhibitors

Recently discovery of relation between cyclooxygenase–2 (COX–2) inhibition and prevention of growth of cansar cells is a major area for research in medicinal chemistry, as it is free from side effects which are genetically shown by developed anticancer agents. In an attempt to develop potent and nontoxic COX–2 inhibitors, we have optimized the 1,5- diaryl pyrazole pharmacophore by using molecular modeling studies. In this paper we present results of 2D and 3D QSAR studies of a series of 22 molecules containing 1,5- diaryl pyrazole pharmacophore as selective COX–2 inhibitors. The 3D QSAR studies were performed using two different methods, stepwise variable selection k–nearest neighbor molecular field analysis (SW kNN–MFA) and simulated annealing k–nearest neighbor molecular field analysis (SA kNN–MFA) methods. The 2D QSAR studies were performed using multiple regressions. 3D QSAR studies produced reasonably good predictive models with high cross–validated r2cv value of 0.732 and 0.783 and predicted r2 value of 0.882 and 0.794 values using the models SW kNN–MFA and SA kNN–MFA method, respectively, whereas the r2 & predicted r2 value in 2D QSAR studies was found to be 0.84914 & 0.9157, respectively. the 2D QSAR studies indicated contribution of different physicochemical descriptors and the result of 3D QSAR studies indicated the exact steric and electronic requirement in the ranges at various positions in the 1,5- diaryl pyrazole pharmacophore. The pharmacophore requirement for selective COX–2 inhibition was optimized and requirement at various positions around 1, 5- diaryl pyrazole pharmacophore were defined.

QSAR Analysis of Saquinavir Analogues (Peptidomimetics) as Potent HIV‐Protease Inhibitors

2012 ◽  
Vol 2 (3) ◽  
pp. 118-127
Author(s):  
Vandana Saini ◽  
Ajit Kumar
Keyword(s):  
Biological Activity ◽  
Quantitative Structure Activity Relationship ◽  
Structural Features ◽  
Partial Least Square ◽  
Least Square ◽  
Activity Prediction ◽  
Qsar Analysis ◽  
Qsar Studies ◽  
Physicochemical Descriptors ◽  
Qsar Models

The correlation of structural features with the biological activity has always played an important role in drug designing process. The present paper discussesthe 2D‐ and 3D‐ Quantitative structure activity relationship (QSAR) studies, performed on a series of compounds related to saquinavir, an established HIV‐protease inhibitor (PI). The analysis was done on structure based calculations using various methods of QSAR like multiple linear regression (MLR), k‐nearest neighbour (k‐NN) and partial least square (PLS), to establish QSAR models for biological activity prediction of unknown compounds. A total of 27 peptidomimetics (Saquinavir analogues) were used for the study and models were developed using a training set of 22 compounds and test set of 5 compounds. The r2 value of 0.959 and crossvalidated r2 (q2) of 0.926 was obtained when models were generated using physicochemical descriptors during 2D‐QSAR analysis. In case of 3D‐QSAR analysis, database alignment of all compounds was done by field fit of steric and electrostatic molecular fields. 3D‐QSAR models generated showed r2 of 0.81 when steric and electrostatic fields were considered as basis of model generation. The meaningful information obtained from the study can be used for the design of saquinavir analogues having better inhibitory activity for HIV‐protease. Also, the QSAR models generated can be very useful to predict the HIV‐PIs and also for virtual screening for identification of new lead molecules.

scholarly journals QSAR studies on imidazoles and sulfonamides as antidiabetic agents

2019 ◽  
Vol 30 (1) ◽  
pp. 5-13
Author(s):  
Veerasamy Ravichandran ◽  
Rajak Harish
Keyword(s):  
Predictive Power ◽  
Partial Least Square ◽  
Least Square ◽  
Antidiabetic Activity ◽  
Statistical Parameters ◽  
Qsar Studies ◽  
2D Qsar ◽  
Partial Least Square Analysis ◽  
Qsar Models ◽  
The Relationship

Abstract The main objective of the present study was to establish significant and validated QSAR models for imidazoles and sulfonamides to explore the relationship between their physicochemical properties and antidiabetic activity. Two dimensional QSAR models had been developed by multiple linear regression and partial least square analysis methods, and then validated for internal and external predictions. The established 2D QSAR models were statistically significant and highly predictive. The validation methods provided significant statistical parameters with q2 > 0.5 and pred_r2 > 0.6, which proved the predictive power of the models. The developed 2D QSAR models revealed the significance of SlogP and T_N_O_5, and Mol.Wt and SsBrE-index properties of imidazoles and sulfonamides on their antidiabetic activity, respectively. These results should prove to be an essential guide for the further design and development of new imidazoles and sulfonamides having better antidiabetic activity.

3D-QSAR Studies on 4,5-Dihydro-1H-pyrazolo [4,3-h] Quinazolines as Plk-1, CDK2/A and Aur-A Serine/Threonine Kinase Inhibitors

2020 ◽  
Vol 17 (4) ◽  
pp. 388-395
Author(s):  
Bhoomendra A. Bhongade ◽  
Nikhil D. Amnerkar ◽  
Andanappa K. Gadad
Keyword(s):  
Protein Kinases ◽  
Proliferative Activity ◽  
Ovarian Cancer Cell Line ◽  
3D Qsar ◽  
Partial Least Square ◽  
Least Square ◽  
Cell Cycle Checkpoints ◽  
Hydrogen Bond Donor ◽  
Qsar Studies ◽  
Qsar Models

Background: The family of serine/threonine protein kinases is associated with peculiar tumor cell-cycle checkpoints which are overexpressed in proliferating tissues as well as in cancers, making them as potential targets for cancer chemotherapy. In the present paper, 3D-QSAR studies were carried out on 4,5-dihydro-1H-pyrazolo[4,3-h]quinazolines against serine/threonine protein kinases viz. polo-like 1 (Plk-1), cyclin dependent 2/A (CDK2/A) and Aurora-A (Aur-A) and their in vitro anti-proliferative activity on A2780 ovarian cancer cell line. Methods: 3D-QSAR models were derived using stepwise forward-backward partial least square (SWFB_PLS) regression method using VlifeMDS QSAR plus software and the docking calculations were carried out using Docking Server. Results: The derived statistically significant and predictive 3D-QSAR models exhibited correlation coefficient r2 in the range of 0.875 to 0.966 and predictive r2 in the range of 0.492 to 0.618. The hydrogen bond donor NH group joining the phenyl ring with quinazoline and terminal amide group were found to favored for Plk-1, CDK2/A and anti-proliferative activity. Estimated energy of binding of compound 45 with enzymes was in the range of -8.52 to -9.03. Conclusion: The results of 3D-QSAR studies may be useful in the development of new pyrazolo[ 4,3-h]quinazoline derivatives with better inhibitory activities against serine/threonine kinases.

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 Comparison of Approaches to Photometric Redshift Estimation of Quasars

2015 ◽  
Vol 11 (S319) ◽  
pp. 146-146
Author(s):  
Yang Tu ◽  
Yan-Xia Zhang ◽  
Yong-Heng Zhao ◽  
Hai-Jun Tian
Keyword(s):  
Gradient Descent ◽  
Nearest Neighbor ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Stochastic Gradient Descent ◽  
K Nearest Neighbor ◽  
Photometric Redshift ◽  
K Nearest Neighbor Algorithm ◽  
Selection Operator

AbstractWe probe many kinds of approaches used for photometric redshift estimation of quasars, including KNN (K-nearest neighbor algorithm), Lasso (Least Absolute Shrinkage and Selection Operator), PLS (Partial Least Square regression), ridge regression, SGD (Stochastic Gradient Descent) and Extra-Trees.

STRUCTURAL REQUIREMENTS OF SOME TRIAZOLONE DERIVATIVES USING TOPOLOGICAL AND PHYSICOCHEMICAL DESCRIPTORS: QSAR APPROACH

INDIAN DRUGS ◽  
2020 ◽  
Vol 57 (04) ◽  
pp. 15-19
Author(s):  
Mukesh C Sharma ◽  
D. V. Kohli
Keyword(s):  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Partial Least Square ◽  
Least Square ◽  
Two Dimensional ◽  
Structural Requirements ◽  
Qsar Studies ◽  
Structure Activity ◽  
Partial Least Square Analysis ◽  
Physicochemical Descriptors

Quantitative structure-activity relationship (QSAR) studies were performed on a series of triazolone analogs to find the structural requirements activity by two-dimensional studies. The statistically significant best 2D QSAR model derived from partial least square analysis is correlated with some of the parameters, viz. correlation coefficient (r2)with external ability of predictive activity. The results of this study may be useful to medicinal chemists to design more antihypertensive compounds.

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.

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