scholarly journals Synthesis, diuretic activity research and QSAR-analysis of N-(1,3,4-tiadiazol-2-il)substituted amides of alkanecarboxylic acids

2019 ◽  
pp. 55-65 ◽  
Author(s):  
І. V. Drapak
Keyword(s):  
Molecular Descriptors ◽  
Amide Group ◽  
Diuretic Activity ◽  
Qsar Analysis ◽  
White Rats ◽  
Thiadiazole Ring ◽  
Qsar Models ◽  
Diuretic Agents ◽  
Substituted Alkanes ◽  
Effective Drugs

Diuretics are effective drugs that are widely used in medicine, but have unwanted side effects. The derivative of thiadiazole – acetozolamide is a known diuretic. Therefore, the search for diuretics in this series and the establishment of quantitative «structure–activity» (QSAR) dependencies is appropriate. The aim of the work was to synthesis N-(1,3,4-thiadiazol-2-yl)substituted alkanes of alkanecarboxylic acids, study their diuretic activity, and QSAR analysis. The objects of the study were N-(1,3,4-thiadiazol-2-yl)substituted alkanes of alkanecarboxylic acids, obtained by the interaction of 2-amino-5-alkyl-1,3,4-thiadiazole with the corresponding acylchlorides. Investigation of diuretic activity of synthesized compounds was carried out by the method of Berchin. Hyper-Chem and BuildQSAR software were used for calculation of molecular descriptors and QSAR-models. Synthesis of 12 N-(1,3,4-thiadiazol-2-yl)substituted amides of alkanecarboxylic acids, the structure of which was confirmed by PMR spectroscopy and elemental analysis. Studies of diuretic activity showed that the synthesized compounds had pronounced diuretic properties, and some of them according to activity indicators were approaching or exceeding comparative preparations. Compound N-(5-methyl-[1,3,4]thiadiazol-2-yl) propionamide showed the best diuretic effect: increased daily diuresis in white rats, in comparison with intact control, in 2.47 times (p ≤ 0,001), in comparison with hydrochlorothiazide was in 1,6 times and acetazolamide was 1,75 times. The calculation of the molecular descriptors of N-(1,3,4-thiadiazol-2-yl)substituted amides of alkanecarboxylic acids was conducted. Based on the calculated values of molecular descriptors and diuretic activity values of 12 synthesized compounds, a QSAR analysis was performed. Analysis of structure-diuretic activity showed the greatest influence of lipophilicity, energy parameters, spatial structure and size of the molecule. Moreover, diuretic activity increases with increasing logP, decreasing the refractive, volume and area of the molecule, increasing the energy of the higher occupied molecular orbital. Increasing the charge on the Sulfur atom of the thiadiazole ring and the Оxygen atom of the carbonyl group, reducing the angle between the Sulfur atoms, the Nitrogen of the amide group and the Oxygen, and increasing the angle between the Nitrogene atoms of the thiadiazole ring, the Oxygen and the Nitrogen of the amide group, also increases diuretic activity. The results of the diuretic activity of the synthesized compounds N-(1,3,4-thiadiazol-2-yl)substituted amides of alkanecarboxylic acids show the potential for the search for diuretic agents among 1,3,4-thiadiazole derivatives. The resulting QSAR models will be used to modelling and prediction the activity of new potential diuretics.

The Renal Outer Medullary Potassium Channel (ROMK): An Intriguing Pharmacological Target for an Innovative Class of Diuretic Drugs

2018 ◽  
Vol 25 (23) ◽  
pp. 2627-2636 ◽  
Author(s):  
Vincenzo Calderone ◽  
Alma Martelli ◽  
Eugenia Piragine ◽  
Valentina Citi ◽  
Lara Testai ◽  
...  
Keyword(s):  
Physiological Role ◽  
Clinical Use ◽  
Diuretic Activity ◽  
First Line ◽  
Potassium Homeostasis ◽  
Diuretic Drugs ◽  
Pharmacological Target ◽  
Diuretic Agents ◽  
Effective Drugs

In the last four decades, the several classes of diuretics, currently available for clinical use, have been the first line option for the therapy of widespread cardiovascular and non-cardiovascular diseases. Diuretic drugs generally exhibit an overall favourable risk/benefit balance. However, they are not devoid of side effects. In particular, all the classes of diuretics cause alteration of potassium homeostasis. <p> In recent years, understanding of the physiological role of the renal outer medullary potassium (ROMK) channels, has shown an intriguing pharmacological target for developing an innovative class of diuretic agents: the ROMK inhibitors. This novel class is expected to promote diuretic activity comparable to (or even higher than) that provided by the most effective drugs used in clinics (such as furosemide), with limited effects on potassium homeostasis. <p> In this review, the physio-pharmacological roles of ROMK channels in the renal function are reported, along with the most representative molecules which have been currently developed as ROMK inhibitors.

QSAR Analysis of Selected Antimicrobial Structures Belonging to Nitro-derivatives of Heterocyclic Compounds

2020 ◽  
Vol 17 (2) ◽  
pp. 214-225 ◽  
Author(s):  
Piotr Kawczak ◽  
Leszek Bober ◽  
Tomasz Bączek
Keyword(s):  
Antimicrobial Activity ◽  
Heterocyclic Compounds ◽  
Molecular Descriptors ◽  
Microbiological Activity ◽  
Activity Data ◽  
Qsar Analysis ◽  
Qsar Models ◽  
Nitro Derivatives ◽  
Semi Empirical ◽  
Derivatives Of

Background: Nitro-derivatives of heterocyclic compounds were used as active agents against pathogenic microorganisms. A set of 4- and 5-nitroimidazole derivatives exhibiting antimicrobial activity was analyzed with the use of Quantitative Structure-Activity Relationships (QSAR) method. The study included compounds used both in documented treatment and those described as experimental. Objective: The purpose of this study was to demonstrate the common and differentiating characteristics of the above-mentioned chemical compounds alike physicochemically as well as pharmacologically based on the quantum chemical calculations and microbiological activity data. Methods: During the study PCA and MLR analysis were performed, as the types of proposed chemometric approach. The semi-empirical and ab initio level of in silico molecular modeling was performed for calculations of molecular descriptors. Results: QSAR models were proposed based on chosen descriptors. The relationship between the nitro-derivatives structure and microbiological activity data was able to class and describe the antimicrobial activity with the use of statistically significant molecular descriptors. Conclusion: The applied chemometric approaches revealed the influential features of the tested structures responsible for the antimicrobial activity of studied nitro-derivatives.

Role of Topological, Electronic, Geometrical, Constitutional and Quantum Chemical Based Descriptors in QSAR: mPGES-1 as a Case Study

2018 ◽  
Vol 18 (13) ◽  
pp. 1075-1090 ◽  
Author(s):  
Ashish Gupta ◽  
Virender Kumar ◽  
Polamarasetty Aparoy
Keyword(s):  
Molecular Descriptors ◽  
Biological Activities ◽  
3D Structure ◽  
Qsar Model ◽  
Single Class ◽  
Test Set ◽  
Qsar Analysis ◽  
Qsar Models

Quantitative Structure Activity Relationship (QSAR) is one of the widely used ligand based drug design strategies. Although a number of QSAR studies have been reported, debates over the limitations and accuracy of QSAR models are at large. In this review the applicability of various classes of molecular descriptors in QSAR has been explained. Protocol for QSAR model development and validation is presented. Here we discuss a case study on 7-Phenyl-imidazoquinolin-4(5H)-one derivatives as potent mPGES-1 inhibitors to identify crucial physicochemical properties responsible for mPGES-1 inhibition. The case study explains the methodology for QSAR analysis, validation of the developed models and role of diverse classes of molecular descriptors in defining the inhibitory activity of considered inhibitors. Various molecular descriptors derived from 2D/3D structure and quantum mechanics were considered in the study. Initially, QSAR models for the training set compounds were developed individually for each class of molecular descriptors. Further, a combined QSAR model was developed using the best descriptor from all the classes. The models obtained were further validated using an external test set. Combined QSAR model exhibited the best correlation (r = 0.80) between the predicted and experimental biological activities of test set compounds. The results of the QSAR analysis were further backed by docking studies. From the results of the case study it is evident that rather than a single class of molecular descriptors, a combination of molecular descriptors belonging to different classes significantly improves the QSAR predictions. The techniques and protocol discussed in the present work might be of significant importance while developing QSAR models of various drug targets.

scholarly journals QSAR Analysis of Quinazolinyl-arylurea Derivatives as Potential Anti-Cancer Agents: GA-MLR Chemometric Approach

2021 ◽  
Vol 01 ◽  
Author(s):  
Medidi Srinivas ◽  
K Grace Neharika
Keyword(s):  
Cell Lines ◽  
Cancer Cell ◽  
Molecular Descriptors ◽  
Cancer Cell Lines ◽  
Structural Features ◽  
Anticancer Activities ◽  
Qsar Analysis ◽  
2D Qsar ◽  
Anti Cancer ◽  
Qsar Models

Background: Cancer is the most common malignancy in men and women globally. The tyrosine kinases and serine/threonine kinases are essential to cell mediators for extra & intra-cellular signal transduction processes and play a key role in cell proliferation, differentiation, migration, metabolism, and programmed cell deaths. In this context, kinases are considered as a potential drug target for cancer therapy. Methods: In the present study, a two-dimensional (2D) quantitative structure-activity relationship (2D-QSAR) was performed to analyze anticancer activities of 28 quinazolinyl-arylurea (QZA) derivatives based on the liver (BEL-7402), stomach (MGC-803), and colon (HCC-827) cancer cell lines using multiple linear regression (MLR) analysis. It was accomplished by using 2D-QSAR analysis on the available IC50 data of 28 molecules based on theoretical molecular descriptors to develop predictive models that correlate structural features of QZA derivatives to their anticancer activities. A suitable set of molecular descriptors such as constitutional, topological, geometrical, electrostatic, and quantum-chemical descriptors were calculated to represent the structural features of compounds. The genetic algorithm (GA) method was used to identify the important molecular descriptors to build the QSAR models and used to predict the anti-cancer activities. Results and Discussion: The obtained 2D-QSAR models were vigorously validated using various statistical metrics using leave-one-out (LOO) and external test set prediction approaches. The best predictive models by MLR gave highly significant square of correlation coefficient (R2train) values of 0.799, 0.815, and 0.779 for the training set and the correlation coefficients (R2test) were obtained 0.885, 0.929, and 0.774 for the test set for the liver, stomach, and colon cancer cell lines. The models also demonstrated good predictive power confirmed by the high value of cross-validated correlation coefficient Q2 value of 0.663, 0.717, and 0.671 for three different cancer cell lines. Importantly, the model's quality was judged as well based on mean absolute error (MAE) criteria and the results were consistent with proposed limits by Golbraikh and Tropsha. Conclusion: The QSAR results of the study indicated that the proposed models were robust and free from chance correlation. This study indicated that maxHBint7, SpMax8_Bhm, and ETA_Beta_ns_d have positively contributed descriptors for anti-cancer activity in the liver, stomach, and colon cancer cell lines and a detailed mechanistic interpretation of each model revealed important structural features that were responsible for favorable or unfavorable for anti-cancer activity. The predictive ability of the proposed models was good and may be useful for developing more potent quinazolinyl-arylurea compounds as anti-cancer agents.

scholarly journals QSAR-ANALYSIS OF POLYSUBSTITUTED FUNCTIONALIZED AMINOTHIAZOLES WITH ANTIHYPERTENSIVE ACTIVITY

2020 ◽  
Vol 5 (2) ◽  
pp. 98-104
Author(s):  
I. V. Drapak
Keyword(s):  
Theoretical Basis ◽  
Molecular Descriptors ◽  
De Novo ◽  
Antihypertensive Drugs ◽  
Biologically Active ◽  
Antihypertensive Activity ◽  
Activity Parameter ◽  
Qsar Analysis ◽  
Qsar Models

Background. QSAR analysis is an important tool for the identification of pharmacophore fragments in biologically active substances and helps optimize the search for new effective drugs. Objective. The aim of the study was to determine the molecular descriptors for QSAR analysis of polysubstituted functionalized aminothiazoles as a theoretical basis for purposeful search de novo of potential antihypertensive drugs among the investigated compounds. Methods. Calculation of molecular descriptors and QSAR-models creation was carried out using the Hyper-Chem 7.5 and BuildQSAR packages. Results. The calculation of a number of molecular descriptors (electronic, steric, geometric, energy) was performed for 15 new polysubstituted functionalized aminothiazoles, with established in vivo antihypertensive activity. According to the calculated molecular descriptors and antihypertensive activity parameter, the QSAR models were derived НА = a + b ∙ X1 + c ∙ X2 + d ∙ X3 , where the activity parameter НА is antihypertensive activity and X1, X2, X3 are molecular descriptors. Conclusion. The study of ‘the structure - antihypertensive activity’ relationship for polysubstituted functionalized aminothiazoles was carried out. QSAR analysis revealed that volume, area, lipophilicity, dipole moment, refractivity, polarization of the molecule and energy of the lowest unoccupied molecular orbital have the most significant effect on antihypertensive activity. It was suggested that the attained QSAR-models may have antihypertensive activity within abovementioned row of compounds and can be considered as theoretical basis for de novo design of new potential antihypertensive drugs.

scholarly journals QSAR analysis and molecular docking study of pyrrolo- and pyridoquinolinecarboxamides with diuretic activity

2021 ◽  
pp. 19-27
Author(s):  
Mykola Golik ◽  
Tetiana Titko ◽  
Angelina Shaposhnyk ◽  
Marharyta Suleiman ◽  
Iryna Drapak ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Carbonic Anhydrase ◽  
De Novo ◽  
Molecular Descriptor ◽  
External Validation ◽  
Docking Study ◽  
Quinoline Derivatives ◽  
Diuretic Activity ◽  
Qsar Analysis ◽  
Qsar Models

The aim. The aim of the study was to reveal QSAR and ascertain the possible mechanism of action via docking study in the row of tricyclic quinoline derivatives with diuretic activity. Materials and methods. Pyrrolo- and pyridoquinolinecarboxamides with proven diuretic activity were involved in the study. Molecular descriptors were calculated using HyperChem and GRAGON software, and QSAR models were built using BuildQSAR software. For receptor-oriented flexible docking, the Autodock 4.2 software package was used. Results. Multivariate linear QSAR models were built on two datasets of quinolinecarboxamides: Vol = a∙X1 + b∙X2 + c∙X3 + d, where Vol – volume of the daily produced urine in rats, Xi – molecular descriptor. QSAR analysis showed that the diuretic activity is determined by the geometric and spatial structure of molecules, logP, the energy values, RDF- and 3D-MoRSE-descriptors. Based upon internal and external validation of the models, the most informative two-parameter linear QSAR model 3а was proposed. Docking data showed the high affinity of two lead compounds to the carbonic anhydrase II. Conclusions. QSAR analysis of tricyclic quinoline derivatives revealed that the diuretic activity increases with the increase of value of logP, refractivity, and dipole moment and with the decrease of volume, surface area, and polarization of the molecules. Increase of values of such energy descriptors as bonds energy, core-core interaction, and energy of the highest occupied molecular orbital results in higher diuresis; decrease in hydration energy leads to higher diuretic activity. Based upon molecular docking calculation, the mechanism of diuretic action is proposed to be carbonic anhydrase inhibition. QSAR models and docking data are useful for in-depth study of diuretic activity of tricyclic quinolines and could be a theoretical basis for de novo-design of new diuretics

scholarly journals Design of New Potent Insecticides of Organophosphate Derivatives Based on QSAR Analysis

2013 ◽  
Vol 13 (1) ◽  
pp. 86-93 ◽  
Author(s):  
Mudasir Mudasir ◽  
Yari Mukti Wibowo ◽  
Harno Dwi Pranowo
Keyword(s):  
Sulfonic Acid ◽  
Molecular Descriptors ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Quantitative Structure ◽  
Benzene Sulfonic Acid ◽  
Qsar Analysis ◽  
Structure Activity ◽  
Qsar Models ◽  
New Compounds

Design of new potent insecticide compounds of organophosphate derivatives based on QSAR (Quantitative Structure-Activity Relationship) analytical model has been conducted. Organophosphate derivative compounds and their activities were obtained from the literature. Computational modeling of the structure of organophosphate derivative compounds and calculation of their QSAR descriptors have been done by AM1 (Austin Model 1) method. The best QSAR model was selected from the QSAR models that used only electronic descriptors and from those using both electronic and molecular descriptors. The best QSAR model obtained was:Log LD50 = 50.872 - 66.457 qC1 - 65.735 qC6 + 83.115 qO7 (n = 30, r = 0.876, adjusted r2 = 0.741, Fcal/Ftab = 9.636, PRESS = 2.414 x 10-6)The best QSAR model was then used to design in silico new compounds of insecticide of organophosphate derivatives with better activity as compared to the existing synthesized organophosphate derivatives. So far, the most potent insecticide of organophosphate compound that has been successfully synthesized had log LD50 of -5.20, while the new designed compound based on the best QSAR model, i.e.: 4-(diethoxy phosphoryloxy) benzene sulfonic acid, had log LD50 prediction of -7.29. Therefore, the new designed insecticide compound is suggested to be synthesized and tested for its activity in laboratory for further verification.

scholarly journals Qsar-analysis of 1-[2-(R-phenylimino)-4-methyl-3-(3-[morpholine-4-yl]propyl)-2,3-dihydro-1,3-thiazol-5-yl]ethane-1-one’s derivatives as potential antioxidants

Pharmacia ◽  
2019 ◽  
Vol 66 (1) ◽  
pp. 33-40 ◽  
Author(s):  
Іryna Drapak ◽  
Borys Zimenkovsky ◽  
Lina Perekhoda ◽  
Hanna Yeromina ◽  
Kateryna Lipakova ◽  
...  
Keyword(s):  
Antioxidant Activity ◽  
Dipole Moment ◽  
Theoretical Basis ◽  
Molecular Descriptors ◽  
De Novo ◽  
Antioxidant Activities ◽  
Activity Level ◽  
Qsar Analysis ◽  
Qsar Models ◽  
Derivatives Of

Aim. The aim of study was to determine of the parameters of the molecular structure of new 1-[2-(R-phenylimino)-4-methyl-3-(3-[morpholine-4-yl]propyl)-2,3-dihydro-1,3-thiazol-5-yl]ethane-1-one derivatives and QSAR-analysis. The latter can be considered as the theoretical basis for de novo design of new potential antioxidants. Materials and methods. 14 new derivatives of 1-[2-(R-phenylimino)-4-methyl-3-(3-[morpholine-4-yl] propyl)-2,3-dihydro-1,3-thiazol-5-yl]ethane-1-one were involved in the study and their antioxidant activities were evaluated. Hyper-Chem 7.59 and BuildQSAR software were used for calculation of molecular descriptors and building the QSAR-models. Results. The calculation of number of molecular descriptors (electronic, steric, geometric, energy) was carried out for the tested compounds: 14 derivatives of 1-[2-(R-phenylimino)-4-methyl-3-(3-[morpholine-4-yl] propyl) -2,3-dihydro-1,3-thiazol-5-yl]ethane-1-one. For QSAR analysis, the compounds studied were divided into a training and test sample. The correlations between the antioxidant activity level and abovementioned molecular descriptors were shown in multivariate linear QSAR-model: Activity = ∑хіаі + bі, where xi – molecular descriptor. Based on the analysis of the obtained QSAR-models, it was found that antioxidant activity increases with decreasing of the area, molecular volume, lipophilicity, polarisation and increasing the magnitude of the dipole moment. The increase in the energy of the bonds, the energy of inter-nuclear interactions, the energy of the lower vacant molecular orbit and the reduction of the energy of hydration and energy of the higher vacant molecular orbitals also results in an increase in the antioxidant activity. The greatest effect of effective charges on atoms on the antioxidant activity was detected: the increase in the charge value on the morpholine cycle Oxygen and the decrease in the charge size on the Sulphur atom of the thiazole ring and the Oxygen atom of the acetyl group. QSAR models with better statistics were selected. QSAR models obtained are characterised by high predictive ability, determined both by internal and external validation and can be used for virtual screening of the antioxidant activity of substances of this class of compounds. Conclusions. 1). The study of the structure–activity relationships for 1-[2-(R-phenylimino)-4-methyl-3-(3- [morpholine-4-yl]propyl)-2,3-dihydro-1,3-thiazol-5-yl]ethane-1-one derivatives were carried out. 2). QSAR analysis revealed the following: polarisation, dipole moment, lipophilicity, energy parameters as well as the size of the molecule and its branching possessed the most significant effect on antioxidant activity; the antioxidant activities of the compounds were increased with the increase in their hydrophilic and reductive properties; the molecules with small volume and surface area showed the higher level of antioxidant activity. 3). Obtained QSAR models are proposed for antioxidant activity prediction within the above-mentioned row of compounds and can be considered as a theoretical basis for de novo design of new potential antioxidants.

scholarly journals ASCoVPred: a machine learning-based platform for quantitative prediction of anti-SARS-CoV-2 activity and human cell toxicity of molecules

2021 ◽  
Author(s):  
Arun Sharma ◽  
Neeraj Chaturvedi ◽  
Dinesh Gupta
Keyword(s):  
Machine Learning ◽  
Human Cell ◽  
Molecular Descriptors ◽  
Quantitative Prediction ◽  
Free Access ◽  
Cell Toxicity ◽  
Inhibitory Compounds ◽  
Qsar Models ◽  
Selection For ◽  
Effective Drugs

Abstract There is an urgent need to accelerate the discovery of effective drugs for COVID-19. We have developed machine learning models for rapid discovery of molecules potentially inhibitory to SARS-CoV-2 and negligible or no human cell toxicity. The machine learning (ML) QSAR models were trained and optimized with features (descriptors and fingerprints) of the experimentally validated SARS-CoV-2 inhibitory compounds. Several molecular descriptors and fingerprints were calculated to select the decisive ones for the training and evaluation of thousands of ML models. The best-optimized models are deployed as ASCoVPred webserver and standalone software, that provides easy and free access to the models. The feature selection for selecting the best descriptors for ML models training helped identify a set of decisive descriptors and fingerprints that correlate positively or negatively with the anti-SARS-CoV-2 activity and toxicity of the compounds. Systematic prediction and optimization of compounds with the help of ASCoVPred can facilitate the discovery of novel anti-SARS-CoV-2 compounds. The ASCoVPred web server and standalone software are freely available at http://14.139.62.220/ascovpred/.

DESIGN OF NEW PEROXISOME PROLIFERATORS GAMMA ACTIVATED RECEPTOR AGONISTS (PPARγ) VIA QSAR BASED MODELING

2018 ◽  
pp. 23-26 ◽  
Author(s):  
Tripathi RB ◽  
Jain J ◽  
Siddiqui AW
Keyword(s):  
Molecular Descriptor ◽  
Binding Pocket ◽  
Peroxisome Proliferators ◽  
Qsar Study ◽  
Qsar Analysis ◽  
Qsar Models ◽  
Artery Disease ◽  
Peroxisome Proliferators Activated Receptors ◽  
Recent Attention

The Peroxisome proliferators-activated receptors (PPARs) are one of the nuclear fatty acid receptors, which contain a type II zincfinger DNA binding pattern and a hydrophobic ligand binding pocket. These receptors are thought to play an essential role in metabolic diseasessuch as obesity, insulin resistance, and coronary artery disease. Therefore Peroxisome Proliferators-Activated Receptor (PPARγ) activators havedrawn great recent attention in the clinical management of type 2 diabetes mellitus, prompting several attempts to discover and optimize newPPARγ activators. Objective: The aim of the study was to finding new selective human PPARγ (PPARγ) modulators that are able to improveglucose homeostasis with reduced side effects compared with TZDs and identify the specific molecular descriptor and structural constraint toimprove the agonist activity of PPARγ analogs. Material and Method: Software’s that was used for this study include S.P. Gupta QSARsoftware (QSAR analysis), Valstat (Comparative QSAR analysis and calculation of L-O-O, Q2, r2, Spress), BILIN (Comparative QSAR analysisand calculation of Q2, r, S, Spress, and F), etc., allowing directly performing statistical analysis. Then multiple linear regression based QSARsoftware (received from BITS-Pilani, India) generates QSAR equations. Result and Discussion: In this study, we explored the quantitativestructure–activity relationship (QSAR) study of a series of meta-substituted Phenyl-propanoic acids as Peroxisome Proliferators Gamma activatedreceptor agonists (PPARγ).The activities of meta-substituted Phenyl-propanoic acids derivatives correlated with various physicochemical, electronic and steric parameters.Conclusion: The identified QSAR models highlighted the significance of molar refractivity and hydrophobicity to the biological activity.

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