Receptor-Based 3D QSAR Analysis of Serotonin 5-HT1D Receptor Agonists

2005 ◽  
Vol 70 (9) ◽  
pp. 1482-1492 ◽  
Author(s):  
Nalan Terzioglu ◽  
Hans-Dieter Höltje
Keyword(s):  
Excellent Result ◽  
Three Dimensional ◽  
3D Qsar ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Dynamic Simulations ◽  
Qsar Analysis ◽  
Receptor Agonists ◽  
Predictive Quality ◽  
Serotonergic Receptor

A three-dimensional quantitative structure-activity relationship study (3D QSAR) has been successfully applied to explain the binding affinities for the serotonin 5-HT1D receptor of a triptan series. The paper describes the development of a receptor-based 3D QSAR model of some known agonists and recently developed triptans on the 5-HT1D serotonergic receptor, showing a significant correlation between predicted and experimentally measured binding affinity (pIC50). The pIC50 values of these agonists are in the range from 5.40 to 9.50. The ligand alignment obtained from dynamic simulations was taken as basis for a 3D QSAR analysis applying the GRID/GOLPE program. 3D QSAR analysis of the ligands resulted in a model of high quality (r2 = 0.9895, q2LOO = 0.7854). This is an excellent result and proves both the validity of the proposed pharmacophore and the predictive quality of the 3D QSAR model for the triptan series of serotonin 5-HT1D receptor agonists.

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 3D-QSAR and Docking Studies of a Series ofβ-Carboline Derivatives as Antitumor Agents of PLK1

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Jahan B. Ghasemi ◽  
Valentin Davoudian
Keyword(s):  
Antitumor Agents ◽  
Three Dimensional ◽  
Human Tumor ◽  
3D Qsar ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Docking Studies ◽  
Human Tumor Cell Lines ◽  
Qsar Analysis ◽  
Leave One Out

An alignment-free, three dimensional quantitative structure-activity relationship (3D-QSAR) analysis has been performed on a series ofβ-carboline derivatives as potent antitumor agents toward HepG2 human tumor cell lines. A highly descriptive and predictive 3D-QSAR model was obtained through the calculation of alignment-independent descriptors (GRIND descriptors) using ALMOND software. For a training set of 30 compounds, PLS analyses result in a three-component model which displays a squared correlation coefficient (r2) of 0.957 and a standard deviation of the error of calculation (SDEC) of 0.116. Validation of this model was performed using leave-one-out,q2looof 0.85, and leave-multiple-out. This model gives a remarkably highr2pred(0.66) for a test set of 10 compounds. Docking studies were performed to investigate the mode of interaction betweenβ-carboline derivatives and the active site of the most probable anticancer receptor, polo-like kinase 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.

Computational Atom-based Three-Dimensional Quantitative Structure-Activity Relationship (3D QSAR) Model for Predicting Anti-Dengue Agents

2021 ◽  
Vol 16 (10) ◽  
pp. 50-58
Author(s):  
Ali Qusay Khalid ◽  
Vasudeva Rao Avupati ◽  
Husniza Hussain ◽  
Tabarek Najeeb Zaidan
Keyword(s):  
Dengue Fever ◽  
Three Dimensional ◽  
3D Qsar ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Activity Relationship ◽  
Quantitative Structure ◽  
Contour Maps ◽  
Structure Activity ◽  
Bioactive Ligands

Dengue fever is a viral infection spread by the female mosquito Aedes aegypti. It is a virus spread by mosquitoes found all over the tropics with risk levels varying depending on rainfall, relative humidity, temperature and urbanization. There are no specific medications that can be used to treat the condition. The development of possible bioactive ligands to combat Dengue fever before it becomes a pandemic is a global priority. Few studies on building three-dimensional quantitative structure-activity relationship (3D QSAR) models for anti-dengue agents have been reported. Thus, we aimed at building a statistically validated atom-based 3D-QSAR model using bioactive ligands reported to possess significant anti-dengue properties. In this study, the Schrodinger PhaseTM atom-based 3D QSAR model was developed and was validated using known anti-dengue properties as ligand data. This model was also tested to see if there was a link between structural characteristics and anti-dengue activity of a series of 3-acyl-indole derivatives. The established 3D QSAR model has strong predictive capacity and is statistically significant [Model: R2 Training Set = 0.93, Q2 (R2 Test Set) = 0.72]. In addition, the pharmacophore characteristics essential for the reported anti-dengue properties were explored using combined effects contour maps (coloured contour maps: blue: positive potential and red: negative potential) of the model. In the pathway of anti-dengue drug development, the model could be included as a virtual screening method to predict novel hits.

scholarly journals A Modified 3D-QSAR Model Based on Ideal Point Method and Its Application in the Molecular Modification of Plasticizers with Flame Retardancy and Eco-Friendliness

Polymers ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 1942
Author(s):  
Haigang Zhang ◽  
Chengji Zhao ◽  
Hui Na
Keyword(s):  
Flame Retardancy ◽  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Ideal Point ◽  
Three Dimensional ◽  
3D Qsar ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Point Method ◽  
Contour Maps

The addition of plasticizers makes plastics flammable, and thus, poses a potential risk to the environment. In previous researches, plasticizers with flame retardancy had been synthesized, but their eco-friendliness had not been tested or described. Thus, in this paper, eco-friendliness plasticizers with flame retardancy were designed based on phthalic acid esters (PAEs), which are known as common plasticizers and major plastic additives. For a comprehensive analysis, such as flammability, biotoxicity, and enrichment effects, 17 PAEs’ comprehensive evaluation values were calculated based on the ideal point method. Further, a multi-effect three-dimensional quantitative structure-activity relationship (3D-QSAR) model of PAEs’ flammability, biotoxicity and enrichment effects was constructed. Thus, 18 dimethyl phthalate (DMP) derivatives and 20 diallyl phthalate (DAP) derivatives were designed based on three-dimensional contour maps. Through evaluation of eco-friendliness and flammability, six eco-friendly PAE derivatives with flame retardancy were screened out. Based on contour maps analysis, it was confirmed that the introduction of large groups and hydrophobic groups was beneficial to the simultaneous improvement of PAEs’ comprehensive effects, and multiple effects. In addition, the group properties were correlated significantly with improved degrees of the comprehensive effects of corresponding PAE derivatives, confirming the feasibility of the comprehensive evaluation method and modified scheme.

CoMFA, CoMSIA and HQSAR Analysis of 3-aryl-3-ethoxypropanoic Acid Derivatives as GPR40 Modulators

2020 ◽  
Vol 17 (1) ◽  
pp. 100-118
Author(s):  
Krishna A. Gajjar ◽  
Anuradha K. Gajjar
Keyword(s):  
Biological Activity ◽  
Structural Information ◽  
Three Dimensional ◽  
3D Qsar ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Docking Studies ◽  
Statistical Parameters ◽  
Qsar Study ◽  
Negative Contribution

Background: Human GPR40 receptor, also known as free fatty-acid receptor 1, is a Gprotein- coupled receptor that binds long chain free fatty acids to enhance glucose-dependent insulin secretion. In order to improve the resistance and efficacy, computational tools were applied to a series of 3-aryl-3-ethoxypropanoic acid derivatives. A relationship between the structure and biological activity of these compounds, was derived using a three-dimensional quantitative structure-activity relationship (3D-QSAR) study using CoMFA, CoMSIA and two-dimensional QSAR study using HQSAR methods. Methods: Building the 3D-QSAR models, CoMFA, CoMSIA and HQSAR were performed using Sybyl-X software. The ratio of training to test set was kept 70:30. For the generation of 3D-QSAR model three different alignments were used namely, distill, pharmacophore and docking based alignments. Molecular docking studies were carried out on designed molecules using the same software. Results: Among all the three methods used, Distill alignment was found to be reliable and predictive with good statistical results. The results obtained from CoMFA analysis q2, r2cv and r2 pred were 0.693, 0.69 and 0.992 respectively and in CoMSIA analysis q2, r2cv and r2pred were 0.668, 0.648 and 0.990. Contour maps of CoMFA (lipophilic and electrostatic), CoMSIA (lipophilic, electrostatic, hydrophobic, and donor) and HQSAR (positive & negative contribution) provided significant insights i.e. favoured and disfavoured regions or positive & negative contributing fragments with R1 and R2 substitutions, which gave hints for the modifications required to design new molecules with improved biological activity. Conclusion: 3D-QSAR techniques were applied for the first time on the series 3-aryl-3- ethoxypropanoic acids. All the models (CoMFA, CoMSIA and HQSAR) were found to be satisfactory according to the statistical parameters. Therefore such a methodology, whereby maximum structural information (from ligand and biological target) is explored, gives maximum insights into the plausible protein-ligand interactions and is more likely to provide potential lead candidates has been exemplified from this study.

scholarly journals QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP ANALYSIS OF NOVEL PYRAZOLINE DERIVATIVES USING K NEAREST NEIGHBOUR MOLECULAR FIELD ANALYSIS METHOD

2017 ◽  
Vol 9 (12) ◽  
pp. 87
Author(s):  
Deepali M. Jagdale ◽  
Ramaa C. S.
Keyword(s):  
Three Dimensional ◽  
3D Qsar ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Field Analysis ◽  
Quantitative Structure ◽  
Relationship Analysis ◽  
Structure Activity ◽  
Novel Approach ◽  
Vlife Mds

Objective: Malonyl CoA decarboxylase (MCD) enzyme plays important role in fatty acid and glucose oxidation. Inhibition of MCD might turn to a novel approach to treat ischemia. The main objective of this research article was to develop a novel pharmacophore for enhanced activity.Methods: Three-dimensional quantitative structure-activity relationships (3D-QSAR) was performed for pyrazoline derivatives as MCD inhibitors using VLife MDS 4.6 software. The QSAR model was developed using the stepwise 3D-QSAR kNN-MFA method.Results: The statistical results generated from kNN-MFA method indicated the significance and requirements for better MCD inhibitory activity. The information rendered by 3D-QSAR model may render to better understanding and designing of novel MCD inhibitors.Conclusion: 3D-QSAR is an important tool in understanding the structural requirements for the design of novel and potent MCD inhibitors. It can be employed to design new drug discovery.

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