2D/3D-QSAR STUDY ON ANALOGUES OF 2-METHOXYESTRADIOL WITH ANTICANCER ACTIVITY

2008 ◽  
Vol 07 (02) ◽  
pp. 287-301 ◽  
Author(s):  
SI YAN LIAO ◽  
LI QIAN ◽  
JIN CAN CHEN ◽  
YONG SHEN ◽  
KANG CHENG ZHENG
Keyword(s):  
Anticancer Activity ◽  
Molecular Design ◽  
Predictive Ability ◽  
Decisive Role ◽  
3D Qsar ◽  
Qsar Model ◽  
Field Analysis ◽  
Qsar Study ◽  
Comfa Model ◽  
2D Qsar

Two-dimensional (2D) and three-dimensional (3D) quantitative structure–activity relationships (QSARs) of 23 analogs of 2-Methoxyestradiol with anticancer activity (expressed as p GI50) against MCF-7 human breast cancer cells have been studied by using a combined method of the DFT, MM2 and statistics for 2D, as well as the comparative molecular field analysis (CoMFA) for 3D. The established 2D-QSAR model in training set shows not only significant statistical quality, but also predictive ability, with the square of adjusted correlation coefficient [Formula: see text] and the square of the cross-validation coefficient (q2= 0.779). The same model was further applied to predict p GI50values of the four compounds in the test set, and the resulting [Formula: see text] being as high as 0.827, further confirms that this 2D-QSAR model has high predictive ability for this kind of compound. The 3D-QSAR model also shows good correlative and predictive capabilities in terms of R2(0.927) and q2(0.786) obtained from CoMFA model. The results that 2D- and 3D-QSAR analyses accord with each other, suggest that the electrostatic interaction plays a decisive role in determining the anticancer activity of the studied compounds, and that increasing the negative charge of substituent R2and the positive charge of substituents linking to C17as well as decreasing the size of substituent R1are advantageous to improving the cytotoxicity. Such results can offer some useful theoretical references for directing the molecular design and understanding the action mechanism of this kind of compound with anticancer activity.

3D-QSAR STUDIES OF SUBSTITUTED 4-ARYL/HETEROARYL-4H-CHROMENES AS APOPTOSIS INDUCERS USING CoMFA AND CoMSIA

2009 ◽  
Vol 08 (01) ◽  
pp. 143-155 ◽  
Author(s):  
SI YAN LIAO ◽  
LI QIAN ◽  
TI FANG MIAO ◽  
YONG SHEN ◽  
KANG CHENG ZHENG
Keyword(s):  
Anticancer Activity ◽  
Predictive Ability ◽  
Decisive Role ◽  
3D Qsar ◽  
Field Analysis ◽  
Breast Cancer Cell Lines ◽  
Steric Interaction ◽  
Anticancer Activities ◽  
Strong Electron ◽  
Qsar Studies

Three-dimensional (3D) quantitative structure–activity relationships (QSARs) of 36 apoptosis inducers, substituted 4-aryl/heteroaryl-4H-chromenes with anticancer activity against human breast cancer cell lines T47D, have been studied by using methods of comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA). The established 3D-QSAR models in training set show not only significant statistical quality, but also predictive ability, with high correlation coefficient (R2) values and cross-validation coefficient (q2) values: CoMFA (R2, q2: 0.944, 0.747), CoMSIA (R2, q2: 0.944, 0.704). Moreover, the predictive abilities of the CoMFA and CoMSIA models were further confirmed by a test set, giving the predictive correlation coefficients ([Formula: see text] values) of 0.845 and 0.851, respectively. Based on the CoMFA and CoMSIA contour map analyses, some key factors responsible for anticancer activity of this series of compounds have been found as follows: the steric interaction plays a decisive role in determining the anticancer activities of these compounds; bulky groups as substituent R 1 are not tolerated; in addition to a steric moderation, higher degree of electropositivity and hydrophobicity on the terminal alkyl of substituent R 2 might be favorable to the activity; the substituent R 3 should be hydrophobic; bulky and strong electron withdrawing groups for the substituent R 4 are not advantageous to the activity; simultaneously introducing large electronegative atoms as hydrogen-acceptors to the first atoms of the substituents R 5 and R 6 may increase the activity, but substituents R 5 and R 6 with a linking group – OCH 2 O – may decrease the activity. Such results can offer some useful theoretical references for understanding the action mechanism, designing more potent derivatives, and predicting their activities prior to synthesis.

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.

3D-QSAR Study on Toxicities of Substituted Phenols against Vibrio Qinghaiensis(Q67)

2012 ◽  
Vol 610-613 ◽  
pp. 607-611
Author(s):  
Ping Sun ◽  
Hui Liu ◽  
Guo Hua Zhao ◽  
Jun Tan ◽  
Fu Yang Wang
Keyword(s):  
Similarity Index ◽  
3D Qsar ◽  
Field Analysis ◽  
Comparative Molecular Field Analysis ◽  
Substituted Phenols ◽  
Qsar Study ◽  
Prediction Ability ◽  
Comfa Model ◽  
Index Analysis ◽  
Qsar Models

To investigate the relationships between structures and toxicities of 16 substituted phenols against vibrio qinghaiensis (Q67), 3D-QSAR models were proposed by using comparative molecular field analysis (CoMFA) and molecular similarity index analysis (CoMSIA). The results suggest that the steric field of substituted group is the dominating factor for the toxicity. Two obtained models show fine stabilities and predictive abilities. Comaprably, the prediction ability of CoMFA model is slightly more advantageous than that of CoMSIA, which both can be used to predict the toxicity of these kinds of compounds, even to provide further theoretical guide about biological toxic mechanism of substituted phenols.

Structure Activity Design, Synthesis and Biological Activity of Newer Imidazole-Triazine Clubbed Derivative as Antimicrobial and Antitubercular Agents

2021 ◽  
Vol 18 ◽  
Author(s):  
Jaydeep A. Patel ◽  
Navin B. Patel ◽  
Pratik K. Maisuriya ◽  
Monika R. Tiwari ◽  
Amit C. Purohit
Keyword(s):  
Thermodynamic Properties ◽  
Pharmacological Activity ◽  
Predictive Ability ◽  
Antitubercular Activity ◽  
Qsar Model ◽  
Total Surface Area ◽  
Lead Target ◽  
Antitubercular Agents ◽  
Qsar Study ◽  
2D Qsar

Background: Imidazole and triazine derivatives act as antimicrobial and antitubercular agents. 2D-QSAR determination estimates the pharmacological activity on the basis of thermodynamic properties of the structure. Objective: The structural arrangements and thermodynamic properties of the imidazole derivatives are necessary for the enhancement of pharmacological activity. So imidazole-triazine clubbed derivatives were designed on the bases of molecular modeling 2D-QSAR study of antitubercular activity. Methods: PLSR method was applied for 2D-QSAR determination of the (Z)-5-ethylidene-3-(4-methoxy-6-methyl-1,3,5-triazin-2-yl)-2-phenyl-3,5-dihydro-4H-imidazol-4-one (B1-B10). The designed compounds were synthesized and spectrally evicted by IR, 1H NMR, 13C NMR, Mass spectra data as well as biologically screened opposite different antitubercular and antimicrobial species. Result: Compounds B4, B6, B7 were founds potent against different antimicrobial species. Compound B3 was more effective against M. tuberculosis H37Rv. Statistically significant QSAR model generated by PLSR methods shows external r2=0.9775 and internal q2=0.2798 predictive ability. Whereas, the model incorporates with three parameters PolarSurfaceAreaExcluding P and S, MomInertiaY and SsCH3count with their corresponding values for each molecule. Conclusion: 2D-QSAR study advised antitubercular activity directly proportional to total surface area of the polar atoms having molecules and moment of inertia on Y-axis. Whereas, inversely proportional to methyl group joined with single bond. The present study afforded favorable results which were further used to generate lead target molecules.

A new, fully validated and interpreted quantitative structure-activity relationship model of p-aminosalicylic acid derivatives as neuraminidase inhibitors

2013 ◽  
Vol 67 (5) ◽  
Author(s):  
Ana Hartmman ◽  
Daniela Jornada ◽  
Eduardo Melo
Keyword(s):  
Predictive Ability ◽  
3D Qsar ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Neuraminidase Inhibitors ◽  
Aminosalicylic Acid ◽  
Randomization Tests ◽  
Qsar Study ◽  
Relationship Model ◽  
Mechanism Of Interaction

AbstractA multivariate QSAR study with a set of 34 p-aminosalicylic acid derivatives, described as neuraminidase inhibitors of the H1N1 viruses, is presented in this work. The variable selection was performed with the Ordered Predictors Selection (OPS) algorithm and the model was built with the Partial Least Squares (PLS) regression method. Leave-N-out cross-validation and y-randomization tests showed that the model was robust and free from chance correlation. The external predictive ability was superior to the 3D-QSAR model previously published. Moreover, it was possible to perform a mechanistic interpretation, where the descriptors referred directly to the mechanism of interaction with the neuraminidase.

scholarly journals Sulfonamide Based β-Carbonic Anhydrase Inhibitors: 2D QSAR Study

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Meenakshi N. Deodhar ◽  
Priyanka L. Khopade ◽  
Mahesh G. Varat
Keyword(s):  
Carbon Dioxide ◽  
Inhibitory Activity ◽  
Molecular Design ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Carbonic Anhydrases ◽  
Human Pathogens ◽  
Qsar Study ◽  
Physiological Concentration ◽  
2D Qsar

The carbonic anhydrases (CAs) (or carbonate dehydratases) form a family of metalloenzymes that catalyze the rapid interconversion of carbon dioxide and water to bicarbonate and protons (or vice versa), a reversible reaction that occurs rather slowly in the absence of a catalyst. The β-CAs have been characterized in a high number of human pathogens, such as the fungi/yeasts Candida albicans, Candida glabrata, Cryptococcus neoformans, and Saccharomyces cerevisiae and the bacteria Helicobacter pylori, Mycobacterium tuberculosis, Haemophilus influenzae, Brucella suis, and Streptococcus pneumonia. The β-CAs in microorganisms provide physiological concentration of carbon dioxide and bicarbonate (CO2/HCO3-) for their growth. Inhibition of β-CAs from the pathogenic microorganism is recently being explored as a novel pharmacological target to treat infections caused by the these organisms. The present study aimed to establish a relationship between the β-CAs inhibitory activity for structurally related sulphonamide derivatives and the physicochemical descriptors in quantitative terms. The statistically validated two-dimensional quantitative structure activity relationship (2D QSAR) model was obtained through multiple linear regression (MLR) analysis method using Vlife molecular design suits (MDS). Five descriptors showing positive and negative correlation with the β-CAs inhibitory activity have been included in the model. This validated 2D QSAR model may be used to design sulfonamide derivatives with better inhibitory properties.

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 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.

scholarly journals In silico Prediction of Novel SARS-CoV 3CL pro Inhibitors: a Combination of 3D-QSAR, Molecular Docking, ADMET Prediction, and Molecular Dynamics Simulation

2021 ◽  
Vol 12 (4) ◽  
pp. 5100-5115
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Predictive Ability ◽  
3D Qsar ◽  
Quantitative Structure Activity Relationship ◽  
Field Analysis ◽  
Dynamics Simulation ◽  
Qsar Study ◽  
Determination Coefficient ◽  
Pharmacokinetic Properties

The Chymotrypsin-like protease (3CLpro) is a drug target in the coronavirus because of its role in processing the polyproteins that are translated from the viral RNA. This study applied 3D quantitative structure-activity relationship (3D-QSAR), molecular docking, and ADMET prediction on a series of SARS-CoV 3CLpro inhibitors. The 3D-QSAR study was applied using Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) methods, which gave the cross-validation coefficient (Q2) values of 0.64 and 0.80, the determination coefficient (R2) values of 0.998 and 0.993 and the standard error of the estimate (SEE) values of 0.046 and 0.091, respectively. The acceptable values of the determination coefficient (R2 test) to CoMFA and CoMSIA respectively corresponding to values of 0.725 and 0.690 utilizing a test set of seven molecules prove the high predictive ability of this model. Molecular docking analysis was utilized to validate 3D-QSAR methods and explain the binding site interactions and affinity between the most active ligands and the SARS-CoV 3CLpro receptor. Based on these results, a novel series of compounds were predicted, and their pharmacokinetic properties were verified using drug-likeness and ADMET prediction. Finally, the best-docked candidate molecules were subjected to molecular dynamics (MD) simulation to affirm their dynamic behavior and stability.

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