Quantitative Structure–Activity Relationship Analysis of Selective Rho Kinase Inhibitors as Neuro-regenerator Agents

Kesar, Seema; Paliwal, Sarvesh; Mishra, Pooja; Chauhan, Monika

doi:10.4274/tjps.galenos.2018.70288

Cited by 3 publications

(2 citation statements)

References 15 publications

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“…Furthermore, for a predictive model, the value of the coefficient of determination (R 2 ) of the validation set of 0.624 is greater than 0.6 and less than the R 2 of the training set (R 2 train = .669). 25 Most of the predicted M/P values were within 95% of the confidence level for prediction. The model displayed only two false negatives (1.5%) by predicting lower M/P values for acyclovir and atenolol (Table 4), suggesting that alternative transport mechanisms may be involved in their partitioning into breast milk.…”

Section: Re Sults and Discussionmentioning

confidence: 64%

“…A predictive squared correlation coefficient ( q 2 ) of 0.695 further validated the model's ability to predict M/P ratios, as a q 2 value above 0.5 renders a QSAR model to be predictive [24]. Furthermore, for a predictive model, the value of the coefficient of determination ( R 2 ) of the validation set of 0.624 is greater than 0.6 and less than the R 2 of the training set ( R 2 train = .669) 25 . Most of the predicted M / P values were within 95% of the confidence level for prediction.…”

Section: Resultsmentioning

confidence: 98%

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QSAR analysis of the partitioning of terpenes and terpenoids into human milk

Agatonović-Kuštrin

Gegechkori

Morton

2022

Flavour & Fragrance J

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Studies have shown that olfactory experience during breastfeeding plays an important role in the later development of certain food preferences in life. Thus, the aim of this study was to predict partitioning of odorous terpenes and terpenoids into breast milk from a predictive QSAR model for drug transfer. A large heterogenous data set based on drugs and their active metabolites that were used to build a QSAR was collected from the literature. Due to the vast structural diversity of these compounds and possibly different mechanisms involved in M/P partitioning, a non-linear artificial neural network (ANN) model was used to develop a predictive QSAR model. The value of the correlation coefficient of predicted versus experimentally measured M/P values for the final model (14-2-1) was high (R = .82). The descriptors selected in the final model (14-2-1) belong to 3 main categories: (a) solubility/permeability descriptors (dipole moment, polar surface area, aromatic ring count and hydroxyl group count), (b) reactivity descriptors (i.e. HOMO energy) and (c) shape descriptors (different ring size counts, counts of methyl groups and molecular depth). Results of this study predict that many volatile terpenes from the essential oils are transferred into breast milk selectively. The highest M/P values (>3.5) were predicted for β-caryophyllene, aromadendrene, alloaromadendrene, and 1,4-and 1,8-cineole, high values for carvacrol (M/P = 3.2), eugenol (M/P = 3.0) and thymol (M/P = 3.6), and moderate values for α-pinene (M/P = 2.3) and low values (M/P = 0.4) for phellandrene and limonene. Our model helps to explain and expand on the current knowledge of volatile compounds in breast milk by predicting that a variety of volatile terpenoids can be found in breast milk.

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Section: Re Sults and Discussionmentioning

confidence: 64%

Section: Resultsmentioning

confidence: 98%

QSAR analysis of the partitioning of terpenes and terpenoids into human milk

Agatonović-Kuštrin

Gegechkori

Morton

2022

Flavour & Fragrance J

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Multivariate Statistical 2D QSAR Analysis of Indenoisoquinoline-based Topoisomerase- I Inhibitors as Anti-lung Cancer Agents

Singh,

Mangla,

Javed

et al. 2023

ACAMC

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Background:: Indenoisoquinoline-based compounds have shown promise as topoisomerase-I inhibitors, presenting an attractive avenue for rational anticancer drug design. However, a detailed QSAR study on these derivatives has not been performed till date. Objective:: To study aimed to identify crucial molecular features and structural requirements for potent topoisomerase- 1 inhibition. objective: In order to characterize the molecular features and structural requirements, a complete 2D QSAR study was performed on a series of 49 indenoisoquinoline derivatives using TSAR3.3 software. Methods:: A comprehensive two-dimensional (2D) QSAR analysis was performed on a series of 49 indenoisoquinoline derivatives using TSAR3.3 software. A robust QSAR model based on a training set of 33 compounds was developed achieving favorable statistical values: r2=0.790, r2CV=0.722, f=36.461, and s=0.461. Validation was conducted using a test set of nine compounds, confirming the predictive capability of the model (r2=0.624). Additionally, artificial neural network (ANN) analysis was employed to further validate the significance of the derived descriptors. Results:: The optimized QSAR model revealed the importance of specific descriptors, including molecular volume, Verloop B2, and Weiner topological index, providing essential insights into effective topoisomerase-1 inhibition. We also obtained a robust partial least-square (PLS) analysis model with high predictive ability (r2=0.788, r2CV=0.743). The ANN results further reinforced the significance of the derived descriptors, with strong r2 values for both the training set (r2=0.798) and the test set (r2=0.669). Conclusion:: 2D QSAR analysis offers valuable molecular insights into indenoisoquinoline-based topoisomerase- I inhibitors, supporting their potential as anti-lung cancer agents. These findings contribute to the rational design of more effective derivatives, advancing the development of targeted therapies for lung cancer treatment. other: No any

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2d-Qsar Study on Some Novel Dihydropyrimidine-4-Carbonitrile Analogs as an Antifungal Activity

PATEL¹,

PASHA²,

Patel³

2023

Int J Pharm Pharm Sci

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Objective: The present study was designed to study the antifungal activity of Dihydropyrimidine-4-Carbonitrile analogs against the fungi Candida albicans by a 2D quantitative structure-activity relationship (QSAR) model. Methods: The pyrimidine derivatives were produced using lipophilic, electronic, and steric parameters by Quantitative Structure Activity-Relationships (QSAR). A relationship between dependent and independent variables (biological activities and physicochemical descriptors, respectively) was resolved statistically using regression analysis. The F value shows the level of statistical significance of the regression (r2) was used to report the fitness of data. The newly synthesized derivatives were evaluated for in vitro antifungal activity against Candida albicansby Nutrient agar and Seaboard dextrose agar media. Results: Multiple linear regression is a method of crucial importance, it allowed us to obtain a relation between the calculated parameters and the antifungal activity; this we can interpret the variance of the activity by contribution to the calculated descriptors. Quantitative structure-activity relationship (QSAR) model showing a significant activity-descriptors relationship accuracy of 90% (R2 ≥ 0.90) and activity prediction accuracy of 81% (R²cv = 0.81). These values prove that the model obtained is reliable. Out of the three descriptors studied; log P has minimum potency, molar refractivity has more potency and heat of formation has moderate potency. Conclusion: Important structural understanding in the pattern of potent antifungal agents by Quantitative Structure Activity-Relationships (QSAR) study. The acquired physicochemical properties (electronic, topological, and steric) show the important structural features required for antifungal activity against Candida albicans.

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Quantitative Structure–Activity Relationship Analysis of Selective Rho Kinase Inhibitors as Neuro-regenerator Agents

Cited by 3 publications

References 15 publications

QSAR analysis of the partitioning of terpenes and terpenoids into human milk

QSAR analysis of the partitioning of terpenes and terpenoids into human milk

Multivariate Statistical 2D QSAR Analysis of Indenoisoquinoline-based Topoisomerase- I Inhibitors as Anti-lung Cancer Agents

2d-Qsar Study on Some Novel Dihydropyrimidine-4-Carbonitrile Analogs as an Antifungal Activity

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