A QSAR study of macrocyclic diterpenes with P-gp inhibitory activity isolated from Euphorbia species

QSAR study has been carried out on the MMP-13 inhibitory activity of fused pyrimidine derivatives possessing a1,2,4-triazol-3-yl group as a ZBG in 0D- to 2D-Dragon descriptors. The derived QSAR models have revealed that the number of Sulfur atoms (descriptor nS), Balaban mean square distance index (descriptor MSD), molecular electrotopological variation (descriptor DELS), structural information content index of neighborhood symmetry of 2nd and 3rd order (descriptors SIC2 and SIC3), average valence connectivity index chi-4 (descriptor X4Av) in addition to 1st order Galvez topological charge index (descriptor JGI1) and global topological charge index (descriptor JGT) played a pivotal role in rationalization of MMP-13 inhibition activity of titled compounds. Atomic properties such as mass and volume in terms of atomic properties weighted descriptors MATS5m and MATS3v, and certain atom centred fragments such as CH2RX (descriptor C-006), X--CX--X (descriptor C-044), H attached to heteroatom (descriptor H-050) and H attached to C0(sp3) with 1X attached to next C (descriptor H-052) are also predominant to explain MMP-13 inhibition actions of fused pyrimidines. PLS analysis has also corroborated the dominance of CP-MLR identified descriptors. Applicability domain analysis revealed that the suggested model matches the high-quality parameters with good fitting power and the capability of assessing external data and all of the compounds was within the applicability domain of the proposed model and were evaluated correctly.

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Application of Topological Descriptors in QSAR Modeling: Substituted Hydrazones Used As a Model System

Letters in Drug Design & Discovery ◽

10.2174/1570180816666181226145411 ◽

2020 ◽

Vol 17 (3) ◽

pp. 253-263

Author(s):

Vesna Dimova ◽

Mirjana Stojan Jankulovska

Keyword(s):

Antimicrobial Activity ◽

Bacillus Subtilis ◽

Inhibitory Activity ◽

Candida Utilis ◽

Topological Descriptors ◽

Projection Area ◽

Statistical Parameters ◽

Qsar Study ◽

Qsar Models

Background: QSAR study of p-substituted aromatic hydrazones was performed to estimate the quantitative effects of selected topological descriptors on their antimicrobial activity. None of the hydrazones inhibited the growth of the Aspergillus spp., while the data obtained with regard to the antifungal activity of the compounds against Candida utilis were insufficient to develop reliable statistical QSAR models. Therefore, the investigation was focused on developing QSAR models for predicting the antibacterial activity of the compounds against Bacillus subtilis. Methods: A set of substituted hydrazones were tested for their in vitro growth inhibitory activity against Candida utilis, Bacillus subtilis and Aspergillus niger and the diameter of the inhibition zone (mm) was measured. The inhibitory activity data, determined in μg/mL, were transformed to the negative logarithms of molar MICs (log1/CMIC). Using Marvinsketch software package, 28 topological descriptors were calculated. Statistical parameters, such as R2, Sd, F-test, R2 adj, Q, SPRESS, PSE and Q2, were used to test the quality of the developed two-, three-, four-parametric and higher QSAR models. Results and Conclusion: Statistical evaluation of the data used to test the quality of the obtained QSAR models indicated that the two-parametric model involving the descriptors Atom Count (AC) and Maximal Projection Area (MAPA) was statistically significant when all the statistical parameters were summarized. The two parameters, AC and MAPA, had opposite input in modeling the antimicrobial activity of the selected hydrazones against Bacillus subtilis.

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Probing the origin of estrogen receptor alpha inhibition via large-scale QSAR study

RSC Advances ◽

10.1039/c7ra10979b ◽

2018 ◽

Vol 8 (21) ◽

pp. 11344-11356 ◽

Cited By ~ 8

Author(s):

Naravut Suvannang ◽

Likit Preeyanon ◽

Aijaz Ahmad Malik ◽

Nalini Schaduangrat ◽

Watshara Shoombuatong ◽

...

Keyword(s):

Estrogen Receptor ◽

Inhibitory Activity ◽

Large Scale ◽

Estrogen Receptor Alpha ◽

Qsar Modeling ◽

Qsar Study ◽

Receptor Alpha

This study compiles a large, non-redundant set of compounds tested for ERα inhibitory activity and applies QSAR modeling for unveiling the privileged substructures governing the activity.

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Atom- and Bond-Based 2D TOMOCOMD-CARDD Approach and Ligand-Based Virtual Screening for the Drug Discovery of New Tyrosinase Inhibitors

CrossRef Listing of Deleted DOIs ◽

10.1177/1087057108326078 ◽

2008 ◽

Vol 13 (10) ◽

pp. 1014-1024 ◽

Cited By ~ 17

Author(s):

Gerardo M. Casañola-Martín ◽

Yovani Marrero-Ponce ◽

Mahmud Tareq Hassan Khan ◽

Francisco Torrens ◽

Facundo Pérez-Giménez ◽

...

Keyword(s):

Drug Discovery ◽

Inhibitory Activity ◽

External Validation ◽

Qsar Study ◽

Good Correspondence ◽

Linear Discriminant ◽

Tyrosinase Inhibitory Activity ◽

Starting Point ◽

Qsar Models ◽

Antityrosinase Activity

Two-dimensional atom- and bond-based TOMOCOMD-CARDD descriptors and linear discriminant analysis (LDA) are used in this report to perform a quantitative structure-activity relationship (QSAR) study of tyrosinase-inhibitory activity. A database of inhibitors of the enzyme is collected for this study, within 246 highly dissimilar molecules presenting antityrosinase activity. In total, 7 discriminant functions are obtained by using the whole set of atom- and bond-based 2D indices. All the LDA-based QSAR models show accuracies above 90% in the training set and values of the Matthews correlation coefficient ( C) varying from 0.85 to 0.90. The external validation set shows globally good classifications between 89% and 91% and C values ranging from 0.75 to 0.81. Finally, QSAR models are used in the selection/identification of the 20 new dicoumarins subset to search for tyrosinase inhibitory activity. Theoretical and experimental results show good correspondence between one another. It is important to remark that most compounds in this series exhibit a more potent inhibitory activity against the mushroom tyrosinase enzyme than the reference compound, Kojic acid (IC50 = 16.67 μM), resulting in a novel nucleus base (lead) with antityrosinase activity, and this could serve as a starting point for the drug discovery of novel tyrosinase inhibitor lead compounds. ( Journal of Biomolecular Screening 2008:1014-1024)

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A comparative QSAR study of benzamidines complement–inhibitory activity and benzene derivatives acute toxicity

Computers & Chemistry ◽

10.1016/s0097-8485(99)00059-5 ◽

2000 ◽

Vol 24 (2) ◽

pp. 181-191 ◽

Cited By ~ 10

Author(s):

Subhash C. Basak ◽

Brian D. Gute ◽

Bono Lučić ◽

Sonja Nikolić ◽

Nenad Trinajstić

Keyword(s):

Acute Toxicity ◽

Inhibitory Activity ◽

Benzene Derivatives ◽

Qsar Study

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

ISRN Medicinal Chemistry ◽

10.1155/2013/107840 ◽

2013 ◽

Vol 2013 ◽

pp. 1-8 ◽

Cited By ~ 2

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.

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Performance of PLS, GA-PLS and OSC-GA-PLS Models in QSAR Study of Pyrazolone Derivatives Inhibitory Activity, and Image Processing for New Compounds Designing

International Journal of Pharmaceutical Research ◽

10.31838/ijpr/2021.13.03.171 ◽

2021 ◽

Vol 13 (03) ◽

Keyword(s):

Image Processing ◽

Inhibitory Activity ◽

Qsar Study ◽

Pyrazolone Derivatives ◽

New Compounds

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Performance of PLS, GA-PLS and OSC-GA-PLS Models in QSAR Study of Pyrazolone Derivatives Inhibitory Activity, and Image Processing for New Compounds Designing

Journal of Advanced Research in Dynamical and Control Systems ◽

10.5373/jardcs/v13i1/20211002 ◽

2021 ◽

Vol 13 (1) ◽

pp. 08-16

Author(s):

Mitra Mirshafiei ◽

Ali Niazi ◽

Atisa Yazdanipour

Keyword(s):

Inhibitory Activity ◽

Mean Squared Error ◽

Hidden Variables ◽

Calibration Model ◽

Qsar Modeling ◽

Qsar Study ◽

Pyrazolone Derivatives ◽

Orthogonal Signal Correction ◽

New Compounds ◽

Pls Method

Nowadays, Pyrazolone and its derivatives have gained a lot of attention due to their biological and medicinal applications. These compounds have antimicrobial, antifungal and anticancer properties. Therefore, using simple methods to prepare these compounds is important. Pyrazolone is one of the inhibitors of kinase domain containing receptor KDR or VEGFR-2. In this study, Quantitative Structure-Activity Relationship (QSAR) analysis was used to predict the inhibitory activity of new pyrazolone derivatives. Also, Bi-dimensional images were used to calculate pixels for QSAR modeling. Furthermore, the partial least squares (PLS) was used to establish a relationship between IC50-dependent variables and independent variables, i.e., pixels or hidden variables. In addition, Genetic Algorithm (GA) was used in PLS method (GA-PLS) to select the descriptors. In this method, the variables which selected to form the calibration model had negligible errors with acceptable characteristics. Pre-processing methods such as Orthogonal Signal Correction (OSC) were used to provide a suitable input for modeling as well as to improve the results of the GA (OSC-GA-PLS). Furthermore, Root Mean Squared Error of Prediction (RMSEP) was used to assess the performance of the models to predict the pIC50 of the studied compounds, the value of which was obtained equal to 0.30, 0.22, and 0.19 for PLS, GA-PLS and OSC-GA-PLS models, respectively. Finally, the proposed QSAR model was developed with the OSC-GA-PLS method to predict the inhibitory activity of the new compounds.

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