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.

2D and 3D QSAR Studies on a Series of Antichagasic Fenarimol Derivatives

2017 ◽  
Vol 2 (1) ◽  
pp. 44-63
Author(s):  
Anacleto S. de Souza ◽  
Leonardo G. Ferreira ◽  
Adriano D. Andricopulo
Keyword(s):  
Neglected Tropical Diseases ◽  
Public Health Problem ◽  
Predictive Ability ◽  
3D Qsar ◽  
Structural Features ◽  
Field Analysis ◽  
Global Public Health ◽  
Qsar Studies ◽  
Qsar Models ◽  
2D And 3D

Chagas disease is one of the most important neglected tropical diseases. Endemic in Latin America, the disease is a global public health problem, affecting several countries in North America, Europe, Asia and Oceania. The disease affects around 8-10 million people worldwide and the limited treatments available present low efficacy and severe side effects, highlighting the urgent need for new therapeutic options. In this work, the authors developed QSAR models for a series of fenarimol derivatives exhibiting anti-T. cruzi activity. The models were constructed using the Hologram QSAR (HQSAR), Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) methods. The QSAR models presented substantial predictive ability for a series of test set compounds (HQSAR, r2pred = 0.66; CoMFA, r2pred = 0.82; and CoMSIA, r2pred = 0.76), and were valuable to identify key structural features related to the observed trypanocidal activity. The results reported herein are useful for the design of novel derivatives having improved antichagasic properties.

scholarly journals Structural investigations of CXCR2 receptor antagonists by CoMFA, CoMSIA and flexible docking studies

2012 ◽  
Vol 62 (3) ◽  
pp. 287-304 ◽  
Author(s):  
Shravan Kumar Gunda ◽  
Rohith Kumar Anugolu ◽  
Sri Ramya Tata ◽  
Saikh Mahmood
Keyword(s):  
Standard Error ◽  
Three Dimensional ◽  
3D Qsar ◽  
Homology Model ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Field Analysis ◽  
Structural Investigations ◽  
Qsar Analysis ◽  
Qsar Studies

= Three-dimensional quantitative structure activity relationship (3D QSAR) analysis was carried out on a et of 56 N,N’-diarylsquaramides, N,N’-diarylureas and diaminocyclobutenediones in order to understand their antagonistic activities against CXCR2. The studies included comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Models with good predictive abilities were generated with CoMFA q2 0.709, r2 (non-cross-validated square of correlation coefficient) = 0.951, F value = 139.903, r2 bs = 0.978 with five components, standard error of estimate = 0.144 and the CoMSIA q2 = 0.592, r2 = 0.955, F value = 122.399, r2 bs = 0.973 with six components, standard error of estimate = 0.141. In addition, a homology model of CXCR2 was used for docking based alignment of the compounds. The most active compound then served as a template for alignment of the remaining structures. Further, mapping of contours onto the active site validated each other in terms of residues involved with reference to the respective contours. This integrated molecular docking based alignment followed by 3D QSAR studies provided a further insight to support the structure-based design of CXCR2 antagonistic agents with improved activity profiles. Furthermore, in silico screening was adapted to the QSAR model in order to predict the structures of new, potentially active compounds.

scholarly journals Integrated Ligand and Structure-Based Investigation of Structural Requirements for Silent Information Regulator 1 (SIRT1) Activation

2019 ◽  
Vol 18 (27) ◽  
pp. 2313-2324
Author(s):  
Amit K. Gupta ◽  
Sun Choi
Keyword(s):  
3D Model ◽  
Therapeutic Agent ◽  
Statistical Significance ◽  
3D Qsar ◽  
Qsar Model ◽  
Hydrogen Bond Acceptor ◽  
High Statistical Significance ◽  
Qsar Models ◽  
Silent Information Regulator 1 ◽  
2D And 3D

A series of imidazothiazole and oxazolopyridine derivatives as human Silent Information Regulator 1 (SIRT1) activators were subjected to the integrated 2D and 3D QSAR approaches. The derived 3D QSAR models yielded high cross-validated q2 values of 0.682 and 0.628 for CoMFA and CoMSIA, respectively. The non-cross validated values of r2 training = 0.89; predictive r2 test = 0.69 for CoMFA and r2=0.87; predictive r2 test =0.67 for CoMSIA reflected the statistical significance of the developed model. The steric, electrostatic, hydrophobic and hydrogen bond acceptor interactions have been found important in describing the variation in human SIRT1 activation. Further, 2D QSAR model for the same dataset yielded high statistical significance and derived 2D model’s parameters corroborated with the 3D model in terms of features. Derived model was also validated by the crystal structure of active conformation of SIRT1. Developed models may be useful for the identification of potential novel human SIRT1 activators as a therapeutic agent.

scholarly journals 2D and 3D QSAR Studies on a Series of Antichagasic Fenarimol Derivatives

2017 ◽  
pp. 956-977
Author(s):  
Anacleto S. de Souza ◽  
Leonardo G. Ferreira ◽  
Adriano D. Andricopulo
Keyword(s):  
Neglected Tropical Diseases ◽  
Public Health Problem ◽  
Predictive Ability ◽  
3D Qsar ◽  
Structural Features ◽  
Field Analysis ◽  
Global Public Health ◽  
Qsar Studies ◽  
Qsar Models ◽  
2D And 3D

Chagas disease is one of the most important neglected tropical diseases. Endemic in Latin America, the disease is a global public health problem, affecting several countries in North America, Europe, Asia and Oceania. The disease affects around 8-10 million people worldwide and the limited treatments available present low efficacy and severe side effects, highlighting the urgent need for new therapeutic options. In this work, the authors developed QSAR models for a series of fenarimol derivatives exhibiting anti-T. cruzi activity. The models were constructed using the Hologram QSAR (HQSAR), Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) methods. The QSAR models presented substantial predictive ability for a series of test set compounds (HQSAR, r2pred = 0.66; CoMFA, r2pred = 0.82; and CoMSIA, r2pred = 0.76), and were valuable to identify key structural features related to the observed trypanocidal activity. The results reported herein are useful for the design of novel derivatives having improved antichagasic properties.

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 .

scholarly journals Biological enrichment prediction of polychlorinated biphenyls and novel molecular design based on 3D-QSAR/HQSAR associated with molecule docking

2019 ◽  
Vol 39 (5) ◽  
Author(s):  
Jiawen Yang ◽  
Wenwen Gu ◽  
Yu Li
Keyword(s):  
Partition Coefficients ◽  
Polychlorinated Biphenyl ◽  
Molecular Design ◽  
3D Qsar ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Field Analysis ◽  
Similarity Indices ◽  
Qsar Models ◽  
Molecule Docking

Abstract Based on the experimental data of octanol-water partition coefficients (Kow, represents bioaccumulation) for 13 polychlorinated biphenyl (PCB) congeners, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used to establish 3D-QSAR models, combined with the hologram quantitative structure–activity relationship (HQSAR), the substitution sites (mono-substituted and bis-substituted) and substituent groups (electron-withdrawing hydrophobic groups) that significantly affect the octanol-water partition coefficients values of PCBs were identified, a total of 63 monosubstituted and bis-substituted were identified. Compared with using 3D-QSAR model alone, the coupling of 3D-QSAR and HQSAR models greatly increased the number of newly designed bis-substituted molecules, and the logKow reduction in newly designed bis-substituted molecules was larger than that of monosubstituted molecules. This was established to predict the Kow values of 196 additional PCBs and carry out a modification of target molecular PCB-207 to lower its Kow (biological enrichment) significantly, simultaneously maintaining the flame retardancy and insulativity after calculation by using Gaussian09. Simultaneously, molecular docking could further screen out three more environmental friendly low biological enrichment newly designed PCB-207 molecules (5-methyl-PCB-207, 5-amino-PCB-207, and 4-amino-5-ethyl-PCB-207).

scholarly journals CoMFA and CoMSIA Studies on Inhibitors of HIV-1 Integrase - Bicyclic Pyrimidinones

2010 ◽  
Vol 7 (s1) ◽  
pp. S75-S84 ◽  
Author(s):  
V. Radhika ◽  
S. Sree Kanth ◽  
M. Vijjulatha
Keyword(s):  
Biological Activities ◽  
3D Qsar ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Field Analysis ◽  
Integrase Inhibitors ◽  
Inhibitory Potency ◽  
Similarity Indices ◽  
Qsar Models ◽  
Hiv 1

To understand the structural requirements of HIV-1 integrase inhibitors and to design new ligands against human HIV-1 integrase with enhanced inhibitory potency, a 3D QSAR (quantitative structure-activity relationship) study with comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) for a dataset of 35 bicyclic pyrimidinones which are inhibitors of human HIV-1 integrase was performed. QSAR models were computed with Sybyl. The 3D QSAR model showed very good statistical result, namely q2, r2and r2predvalues were high for both CoMFA and CoMSIA. Based on the high values for q2and r2we are confident that the 3D QSAR model gives good predictions that may be used to design better HIV-1 integrase inhibitors. The CoMFA and CoMSIA models reveal that steric and electrostatic fields contribute significantly with biological activities of the studied compounds.

Identifying the Structural Features of Diphenyl Ether Analogues for InhA Inhibition: A 2D and 3D QSAR Based Study

2019 ◽  
Vol 17 (1) ◽  
pp. 31-47 ◽  
Author(s):  
Ashutosh Prasad Tiwari ◽  
Varadaraj Bhat Giliyar ◽  
Gurypur Gautham Shenoy ◽  
Vandana Kalwaja Eshwara
Keyword(s):  
Inhibitory Activity ◽  
Diphenyl Ether ◽  
3D Qsar ◽  
Qsar Model ◽  
Structural Features ◽  
Mycolic Acids ◽  
2D Qsar ◽  
Qsar Models ◽  
Mycobacterial Cell Wall ◽  
2D And 3D

Background: Enoyl acyl carrier protein reductase (InhA) is a validated target for Mycobacterium. It is an enzyme which is associated with the biosynthesis of mycolic acids in type II fatty acid synthase system. Mycobacterial cell wall majorly comprises mycolic acids, which are responsible for virulence of the microorganism. Several diphenyl ether derivatives have been known to be direct inhibitors of InhA. Objective: In the present work, a Quantitative Structure Activity Relationship (QSAR) study was performed to identify the structural features of diphenyl ether analogues which contribute to InhA inhibitory activity in a favourable way. Method: Both 2D and 3D QSAR models were built and compared. Several fingerprint based 2D QSAR models were generated and their relationship with the structural features was studied. Models which corroborated the inhibitory activity of the molecules with their structural features were selected and studied in detail. Results: A 2D-QSAR model, with dendritic fingerprints having regression coefficient, for test set molecules Q2 =0.8132 and for the training set molecules, R2 =0.9607 was obtained. Additionally, an atom-based 3D-QSAR model with Q2 =0.7697 and R2 =0.9159 was also constructed. Conclusion: The data reported by various models provides guidance for the designing of structurally new diphenyl ether inhibitors with potential activity against InhA of M. tuberculosis.

scholarly journals Integrated ligand and structure-based investigation of structural requirements for silent information regulator [SIRT1] activation

2018 ◽  
Author(s):  
Amit K. Gupta ◽  
Sun Choi
Keyword(s):  
3D Model ◽  
Therapeutic Agent ◽  
Statistical Significance ◽  
3D Qsar ◽  
Qsar Model ◽  
Active Conformation ◽  
Hydrogen Bond Acceptor ◽  
High Statistical Significance ◽  
Qsar Models ◽  
2D And 3D

AbstractA series of imidazothiazole and oxazolopyridine derivatives as human silent information regulator (SIRT1) activators were subjected to the integrated 2D and 3D QSAR approaches. The derived 3D QSAR models yielded high cross validated q2 values of 0.682 and 0.628 for CoMFA and CoMSIA respectively. The non-cross validated correlation values of r2training = 0.89; predictive r2test = 0.69 for CoMFA and r2=0.87; predictive r2test =0.67 for CoMSIA reflected the statistical significance of the developed model. The steric, electrostatic, hydrophobic and hydrogen bond acceptor interactions have been found important in describing the variation in human SIRT1 activation. Further, 2D QSAR model for the same dataset yielded high statistical significance and derived 2D model’s parameters corroborated with 3D model in terms of features. The developed model was also validated through the available active conformation structure of SIRT1. Developed models may be useful for the identification of potential novel human SIRT1 activators as therapeutic agent.

QSAR Analysis for Antioxidant Activity of Dipicolinic Acid Derivatives

2018 ◽  
Vol 21 (3) ◽  
pp. 204-214 ◽  
Author(s):  
Vesna Rastija ◽  
Maja Molnar ◽  
Tena Siladi ◽  
Vijay Hariram Masand
Keyword(s):  
Antioxidant Activity ◽  
Antioxidant Activities ◽  
Dipicolinic Acid ◽  
External Validation ◽  
Qsar Model ◽  
Internal Validation ◽  
Qsar Analysis ◽  
Dragon Descriptors ◽  
Qsar Models ◽  
New Compounds

Aims and Objectives: The aim of this study was to derive robust and reliable QSAR models for clarification and prediction of antioxidant activity of 43 heterocyclic and Schiff bases dipicolinic acid derivatives. According to the best obtained QSAR model, structures of new compounds with possible great activities should be proposed. Methods: Molecular descriptors were calculated by DRAGON and ADMEWORKS from optimized molecular structure and two algorithms were used for creating the training and test sets in both set of descriptors. Regression analysis and validation of models were performed using QSARINS. Results: The model with best internal validation result was obtained by DRAGON descriptors (MATS4m, EEig03d, BELm4, Mor10p), split by ranking method (R2 = 0.805; R2 ext = 0.833; F = 30.914). The model with best external validation result was obtained by ADMEWORKS descriptors (NDB, MATS5p, MDEN33, TPSA), split by random method (R2 = 0.692; R2 ext = 0.848; F = 16.818). Conclusion: Important structural requirements for great antioxidant activity are: low number of double bonds in molecules; absence of tertial nitrogen atoms; higher number of hydrogen bond donors; enhanced molecular polarity; and symmetrical moiety. Two new compounds with potentially great antioxidant activities were proposed.

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