scholarly journals Discovery of High-Affinity Cannabinoid Receptors Ligands through a 3D-QSAR Ushered by Scaffold-Hopping Analysis

Molecules ◽  
2018 ◽  
Vol 23 (9) ◽  
pp. 2183 ◽  
Author(s):  
Giuseppe Floresta ◽  
Orapan Apirakkan ◽  
Antonio Rescifina ◽  
Vincenzo Abbate
Keyword(s):  
Cannabinoid Receptors ◽  
Cannabinoid Receptor ◽  
3D Qsar ◽  
Scaffold Hopping ◽  
Design And Optimization ◽  
High Affinity ◽  
Qsar Models ◽  
Visual Understanding ◽  
The Individual ◽  
New Compounds

Two 3D quantitative structure–activity relationships (3D-QSAR) models for predicting Cannabinoid receptor 1 and 2 (CB1 and CB2) ligands have been produced by way of creating a practical tool for the drug-design and optimization of CB1 and CB2 ligands. A set of 312 molecules have been used to build the model for the CB1 receptor, and a set of 187 molecules for the CB2 receptor. All of the molecules were recovered from the literature among those possessing measured Ki values, and Forge was used as software. The present model shows high and robust predictive potential, confirmed by the quality of the statistical analysis, and an adequate descriptive capability. A visual understanding of the hydrophobic, electrostatic, and shaping features highlighting the principal interactions for the CB1 and CB2 ligands was achieved with the construction of 3D maps. The predictive capabilities of the model were then used for a scaffold-hopping study of two selected compounds, with the generation of a library of new compounds with high affinity for the two receptors. Herein, we report two new 3D-QSAR models that comprehend a large number of chemically different CB1 and CB2 ligands and well account for the individual ligand affinities. These features will facilitate the recognition of new potent and selective molecules for CB1 and CB2 receptors.

QSAR and Docking Studies on Piperidyl-cyclohexylurea Derivatives for Prediction of Selective and Potent Inhibitor of Matriptase

2019 ◽  
Vol 15 (2) ◽  
pp. 167-181 ◽  
Author(s):  
Agha Zeeshan Mirza ◽  
Hina Shamshad
Keyword(s):  
Active Compound ◽  
Potent Inhibitor ◽  
3D Qsar ◽  
Qsar Model ◽  
Docking Studies ◽  
Lack Of Fit ◽  
Hydrogen Donors ◽  
Qsar Models ◽  
Test Sets ◽  
New Compounds

Background: QSAR models as PLS, GFA, and 3D were developed for a series of matriptase inhibitors using 35 piperidyl-cyclohexylurea compounds. The training and test sets were divided into a set of 28 and 8 compounds, respectively and the pki values of each compound were used in the analysis. Methods: Docking and alignment methodologies were used to develop models in 3D QSAR. The best models among all were selected on the basis of regression statistics as r2, predictive r2 and Friedman Lack of fit measure. Hydrogen donors and rotatable bonds were found to be positively correlated properties for this target. The models were validated and used for the prediction of new compounds. Based on the predictions of 3D-QSAR model, 17 new compounds were prepared and their activities were predicted and compared with the active compound. Prediction of activities was performed for these 18 compounds using consensus results of all models. ADMET was also performed for the best-chosen compound and compared with the known active. Results and Conclusion: The developed model was able to validate the obtained results and can be successfully used to predict new potential and active compounds.

QSAR Study of α-Glucosidase Inhibitors for Benzimidazole Bearing Bis-Schiff Bases Using CoMFA, CoMSIA, and Molecular Docking

2021 ◽  
Vol 6 (1) ◽  
pp. 9-24
Author(s):  
Ayoub Khaldan ◽  
Soukaina Bouamrane ◽  
Reda El-Mernissi ◽  
Khalil El Khatabi ◽  
Ilham Aanouz ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Schiff Bases ◽  
3D Qsar ◽  
Computational Techniques ◽  
Qsar Study ◽  
Contour Maps ◽  
Glucosidase Inhibitors ◽  
Qsar Models ◽  
The Stability ◽  
New Compounds

A new class of benzimidazoles bearing bis-Schiff bases as α-glucosidase inhibitory was studied based on the combination of two computational techniques such as 3D-QSAR and molecular docking. The CoMFA and CoMSIA QSAR models were developed from fifteen compounds in the training set and four compounds in the test set giving Q2 values of 0.587 and 0.597 respectively, and R2 values of 0.970 and 0.990 respectively. The adapted alignment method with the suitable parameters resulted in reliable models. The CoMFA and CoMSIA contour maps allowed the authors to recognize regions where the activity can be increased or decreased by suitable substitutions. According to these contour maps they have proposed three new compounds with high predicted activities. Moreover, to confirm the stability of these newly designed molecules in the receptor with PDB: 3A4A, a Surflex-docking was applied.

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.

Molecular Modeling of an Orphan GPR18 Receptor

2019 ◽  
Vol 16 (10) ◽  
pp. 1167-1174 ◽  
Author(s):  
Kamil J. Kuder ◽  
Tadeusz Karcz ◽  
Maria Kaleta ◽  
Katarzyna Kiec-Kononowicz
Keyword(s):  
Cannabinoid Receptors ◽  
Cannabinoid Receptor ◽  
Glycine Receptor ◽  
Homology Model ◽  
Orphan Receptor ◽  
Receptor Ligands ◽  
Orphan Receptors ◽  
Inactive Form ◽  
Starting Point ◽  
Endogenous Cannabinoid

Background: : One of the best known to date GPCR class A (Rhodopsin) includes more than 100 orphan receptors for which the endogenous ligand is not known or is unclear. One of them is N-arachidonyl glycine receptor, named GPR18, a receptor that has been reported to be activated by Δ9-THC, endogenous cannabinoid receptors agonist anandamide and other cannabinoid receptor ligands suggesting it could be considered as third cannabinoid receptor. GPR18 activity, as well as its distribution might suggest usage of GPR18 ligands in treatment of endometriosis, cancer, and neurodegenerative disorders. Yet, so far only few GPR18 antagonists have been described, thus only ligand-based design approaches appear to be most useful to identify new ligands for this orphan receptor. Methods: : Main goal of this study, GPR18 inactive form homology model was built on the basis of the evolutionary closest homologous template: Human P2Y1 Receptor crystal structure. Results: : Obtained model was further evaluated and showed active/nonactive ligands differentiating properties with acceptable confidence. Moreover, it allowed for preliminary assessment of proteinligand interactions for a set of previously described ligands. Conclusion:: Thus collected data might serve as a starting point for a discovery of novel, active GPR18 blocking ligands.

Insilico studies, synthesis and antitubercular activity of some novel quinoline – azitidinone derivatives

2020 ◽  
Vol 16 ◽  
Author(s):  
Trupti. S. Chitre ◽  
Kalyani. D. Asgaonkar ◽  
Amrut B. Vikhe ◽  
Shital M Patil ◽  
Dinesh. R. Garud ◽  
...  
Keyword(s):  
Combinatorial Library ◽  
3D Qsar ◽  
Antitubercular Activity ◽  
Structural Features ◽  
Docking Studies ◽  
Quinoline Derivatives ◽  
Qsar Models ◽  
Molecular Modeling Studies ◽  
Lead Generation ◽  
Mcf 7

Background: Diarylquinolines like Bedaquiline have shown promising antitubercular activity by their action of Mycobacterial ATPase. Objective: The structural features necessary for good antitubercular activity for a series of quinoline derivatives were explored through computational chemistry tools like QSAR and combinatorial library generation. In the current study, 3-Chloro-4-(2-mercaptoquinoline-3-yl)-1-substitutedphenylazitidin-2-one derivatives have been designed and synthesized based on molecular modeling studies as anti-tubercular agents. Method: 2D and 3DQSAR analysis was used to designed compounds having quinoline scaffold. The synthesized compounds were evaluated against active and dormant strains of Mycobacterium tuberculosis (MTB) H37 Ra and Mycobacterium bovis BCG. The compounds were also tested for cytotoxicity against MCF-7, A549 and Panc-1 cell lines using MTT assay. Binding affinity of designed compounds was gauged by molecular docking studies. Results: Statistically significant QSAR models generated by SA-MLR method for 2D QSAR exhibited r2 = 0.852, q2 = 0.811and whereas 3D QSAR with SA-kNN showed q2 = 0.77. The synthesized compounds exhibited MIC in the range of 1.38-14.59(µg/ml) .These compounds showed some crucial interaction with MTB Atpase. Conclusion: The present study has shown some promising results which can be further explored for lead generation.

Prediction of Oral Acute Toxicity of Organophosphates Using QSAR Methods

2019 ◽  
Vol 16 ◽  
Author(s):  
Mina Kianpour ◽  
Esmat Mohammadinasab ◽  
Tahereh Momeni Esfahani
Keyword(s):  
Acute Toxicity ◽  
Molecular Descriptors ◽  
Back Propagation ◽  
Quantitative Structure Activity Relationship ◽  
Average Deviation ◽  
Qsar Models ◽  
Ann Models ◽  
Similar Class ◽  
New Compounds ◽  
Oral Acute Toxicity

: The aim of the present study was to develop quantitative structure-activity relationship (QSAR) models, based on molecular descriptors to predict the oral acute toxicity (LD50) of organophosphate compounds. The QSAR models based on genetic algorithm-multiple linear regression (GA-MLR) and back-propagation artificial neural network (BP-ANN) methods were proposed. The prediction experiment showed that the BP-ANN method was a reliable model for screening molecular descriptors, and molecular descriptors obtained by BP-ANN models could well characterize the molecular structure of each compound. It was indicated that among molecular descriptors to predict the LD50 (mgkg-1) of organophosphates, ALOGP2, RDF030u, RDF065p and GATS5m descriptors have more importance than the other descriptors. Also BP-ANN approach with the values of root mean square error (RMSE= 0.00168), square correlation coefficient (R2= 0.9999) and absolute average deviation (AAD=0.6981631) gave the best outcome, and the model predictions were in good agreement with experimental data. The proposed model may be useful for predicting LD50 (mgkg-1) of new compounds of similar class.

scholarly journals Alavi–Carlsen Calcification Score (ACCS): A Simple Measure of Global Cardiac Atherosclerosis Burden

Diagnostics ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1421
Author(s):  
Babak Saboury ◽  
Lars Edenbrandt ◽  
Reza Piri ◽  
Oke Gerke ◽  
Tom Werner ◽  
...  
Keyword(s):  
Arterial Wall ◽  
Cardiac Ct ◽  
Standardized Uptake Value ◽  
Coronary Calcification ◽  
High Affinity ◽  
Maximum Standardized Uptake Value ◽  
Atherosclerotic Burden ◽  
Calcification Score ◽  
Pet Ct ◽  
The Individual

Multislice cardiac CT characterizes late stage macrocalcification in epicardial arteries as opposed to PET/CT, which mirrors early phase arterial wall changes in epicardial and transmural coronary arteries. With regard to tracer, there has been a shift from using mainly 18F-fluorodeoxyglucose (FDG), indicating inflammation, to applying predominantly 18F-sodium fluoride (NaF) due to its high affinity for arterial wall microcalcification and more consistent association with cardiovascular risk factors. To make NaF-PET/CT an indispensable adjunct to clinical assessment of cardiac atherosclerosis, the Alavi–Carlsen Calcification Score (ACCS) has been proposed. It constitutes a global assessment of cardiac atherosclerosis burden in the individual patient, supported by an artificial intelligence (AI)-based approach for fast observer-independent segmentation. Common measures for characterizing epicardial coronary atherosclerosis by NaF-PET/CT as the maximum standardized uptake value (SUV) or target-to-background ratio are more versatile, error prone, and less reproducible than the ACCS, which equals the average cardiac SUV. The AI-based approach ensures a quick and easy delineation of the entire heart in 3D to obtain the ACCS expressing ongoing global cardiac atherosclerosis, even before it gives rise to CT-detectable coronary calcification. The quantification of global cardiac atherosclerotic burden by the ACCS is suited for management triage and monitoring of disease progression with and without intervention.

scholarly journals Development of [18F]LU14 for PET Imaging of Cannabinoid Receptor Type 2 in the Brain

2021 ◽  
Vol 22 (15) ◽  
pp. 8051
Author(s):  
Rodrigo Teodoro ◽  
Daniel Gündel ◽  
Winnie Deuther-Conrad ◽  
Lea Ueberham ◽  
Magali Toussaint ◽  
...  
Keyword(s):  
Cannabinoid Receptors ◽  
Cannabinoid Receptor ◽  
Biological Evaluation ◽  
Emission Tomography ◽  
Tailored Therapy ◽  
Positron Emission ◽  
Cannabinoid Receptor Type 2 ◽  
Attractive Therapeutic Target ◽  
The Brain

Cannabinoid receptors type 2 (CB2R) represent an attractive therapeutic target for neurodegenerative diseases and cancer. Aiming at the development of a positron emission tomography (PET) radiotracer to monitor receptor density and/or occupancy during a CB2R-tailored therapy, we herein describe the radiosynthesis of cis-[18F]1-(4-fluorobutyl-N-((1s,4s)-4-methylcyclohexyl)-2-oxo-1,2-dihydro-1,8-naphthyridine-3-carboxamide ([18F]LU14) starting from the corresponding mesylate precursor. The first biological evaluation revealed that [18F]LU14 is a highly affine CB2R radioligand with >80% intact tracer in the brain at 30 min p.i. Its further evaluation by PET in a well-established rat model of CB2R overexpression demonstrated its ability to selectively image the CB2R in the brain and its potential as a tracer to further investigate disease-related changes in CB2R expression.

scholarly journals Tricyclic Pyrazole-Based Compounds as Useful Scaffolds for Cannabinoid CB1/CB2 Receptor Interaction

Molecules ◽  
2021 ◽  
Vol 26 (8) ◽  
pp. 2126
Author(s):  
Battistina Asproni ◽  
Gabriele Murineddu ◽  
Paola Corona ◽  
Gérard A. Pinna
Keyword(s):  
Neuropathic Pain ◽  
Cannabinoid Receptor ◽  
Receptor Interaction ◽  
Pharmacological Properties ◽  
Cb2 Receptor ◽  
Antiemetic Effect ◽  
High Affinity ◽  
Cb1 Antagonist ◽  
Cb2 Receptors ◽  
Sar Study

Cannabinoids comprise different classes of compounds, which aroused interest in recent years because of their several pharmacological properties. Such properties include analgesic activity, bodyweight reduction, the antiemetic effect, the reduction of intraocular pressure and many others, which appear correlated to the affinity of cannabinoids towards CB1 and/or CB2 receptors. Within the search aiming to identify novel chemical scaffolds for cannabinoid receptor interaction, the CB1 antagonist/inverse agonist pyrazole-based derivative rimonabant has been modified, giving rise to several tricyclic pyrazole-based compounds, most of which endowed of high affinity and selectivity for CB1 or CB2 receptors. The aim of this review is to present the synthesis and summarize the SAR study of such tricyclic pyrazole-based compounds, evidencing, for some derivatives, their potential in the treatment of neuropathic pain, obesity or in the management of glaucoma.

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