Monte Carlo based modelling approach for designing and predicting cytotoxicity of 2-phenylindole derivatives against breast cancer cell line MCF7

Gaikwad, Ruchi; Ghorai, Soumajit; Amin, Sk. Abdul; Adhikari, Nilanjan; Patel, Tarun; Das, Kalpataru; Jha, Tarun; Gayen, Shovanlal

doi:10.1016/j.tiv.2018.05.016

Cited by 20 publications

(4 citation statements)

References 40 publications

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“…The statistical characteristics of models calculated with Eq. 11-13 are better than the statistical characteristics of the CORAL models suggested in the original work (1), where the best model was characterized by r 2 =0.8603, and mean absolute error=0.225 (validation set). Thus, using the correlation weights for C5 and C6 together with modified target function TF 2 improves the model for cytotoxicity of 2-phenylindole derivatives against the MCF7 breast cancer cell line.…”

Section: Discussionmentioning

confidence: 83%

“…Dataset. The dataset of 102 2-phenylindole derivatives having cytotoxicity against the MCF7 breast cancer cell line was taken from the literature (1). The molecular structure of these 2-phenylindole derivatives are represented by simplified molecular input-line entry system (SMILES) (26) and the concentration of these compounds producing 50% in vitro MCF7 cellular toxicity (IC 50 , in nM) was transformed into the corresponding negative logarithm (pIC 50 ).…”

Section: Methodsmentioning

confidence: 99%

“…comparison of different molecular features (3), molecular docking (4); various chemosensitization effects (5); 2D-QSAR (6, 7); 3D-QSAR (8) with analysis of stereoselectivity (9); study of the molecular C-skeleton architecture (10); and finally, comparative analysis of different classes of molecules with anticancer potential (11)(12)(13)(14)(15)(16), for example as in the abovementioned work (1). It is to be noted, that QSAR analysis should obey principles suggested by the Organisation for Economic Co-operation and Development (OECD) (17) and recommendations of the EU chemical control regulation in the European Union (Registration, Evaluation, Authorisation and Restriction of Chemicals, REACH) (18).…”

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confidence: 99%

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Predicting Cytotoxicity of 2-Phenylindole Derivatives Against Breast Cancer Cells Using Index of Ideality of Correlation

Toropov

Toropova

2018

Anticancer Res

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Background: Breast cancer is one of the leading types of cancer in women worldwide. Quantitative structureactivity relationship (QSAR) methods play an important role in the search for new anticancer agents. A QSAR model for cytotoxicity against the breast cancer cell line MCF7, based on hybrid optimal descriptors, has been suggested. A modified version of the hybrid descriptor is suggested. Materials and Methods: A QSAR model for the anticancer activity of 2-phenylindole derivatives was built using the Index of Ideality of Correlation (IIC), which is a new criterion for predictive potential. The calculation can be carried out with a modified version of the CORAL software. Results: The model for the anticancer activity suggested here is better than the one described in the literature. Conclusion: Taking into account the data on molecular rings together with the use of new criterion of predictive potential (IIC), the QSAR improves the prediction for anticancer activity. Anticancer drug discovery is a complex and important field of natural sciences. Quantitative structure-activity relationships (QSARs) are not able to provide complete data on molecular architecture required for new anticancer agents, but QSARs can help reduce the time needed and cost of the search for such agents (1). The design of new chemical compounds that are active against the breast cancer cell line MCF7 has several conceptually different approaches. These are the well-known ADMET approach (absorption, distribution, metabolism, excretion, and toxicity) (2); general virtual screening based on 6189 This article is freely accessible online.

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Section: Discussionmentioning

confidence: 83%

Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

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Predicting Cytotoxicity of 2-Phenylindole Derivatives Against Breast Cancer Cells Using Index of Ideality of Correlation

Toropov

Toropova

2018

Anticancer Res

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“…A Monte Carlo optimization method has been developed for building QSAR model that can estimate cytotoxicity of 2‐phenylindole derivatives against breast cancer cell line MCF7 [26].…”

Section: Introductionmentioning

confidence: 99%

Comparative QSAR modeling of 2‐phenylindol derivatives for predicting the anticancer activity using genetic algorithm multiple linear regression and back‐propagation‐artificial neural network techniques

Bahrami

Shafiei

Marjani

et al. 2022

Int J of Quantum Chemistry

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Quantitative structure-activity relationship (QSAR) studies on a series of 2-phenylindole derivatives as anticancer drugs were performed to choice the important descriptor, which is responsible for their anticancer activity (expressed as pIC 50 ). The geometry optimizations were performed on the structures using Gaussian software with the density functional B3LYP and 6-311G(d,p) basis sets.Dragon software was used to calculate molecular descriptors, and the genetic algorithm (GA) procedure and backward regression were used to proper selection of the most relevant descriptors. The backward multiple linear regression (BW-MLR) and backpropagation-artificial artificial neural network (BP-ANN) were carried out to design QSAR models. The squared correlation coefficient (R 2 ) and the root mean squared error (RMSE) values of the GA-MLR model were calculated to be 0.2843 and 0.7001, respectively. The BP-ANN model was the most powerful, with the square of predictive correlation coefficient R 2 pred , root mean square error (RMSE), and absolute average deviation (AAD) which was equal to 0.9416, 0.0238, and 0.0099, respectively.

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First Report on 3‐(3‐oxoaryl) Indole Derivatives as Anticancer Agents: Microwave Assisted Synthesis, In Vitro Screening and Molecular Docking Studies

et al. 2019

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In this study ZrCl4 was identified as an efficient Lewis acid catalyst for the synthesis of 3‐(3‐oxoaryl) indole derivatives via microwave assisted Michael addition of 2‐phenylindole with chalcones under solvent‐free condition. The reaction proceeds smoothly with high efficiency under green reaction condition to afford a range of 3‐(3‐oxoaryl) indole derivatives exclusively within a short period of time in excellent yields. The synthesized compounds have shown promising in vitro anticancer activity against murine melanoma (B16F10) and human breast cancer (MCF7) cell lines. Molecular docking analysis showed that this type of indole derivatives may act as anticancer agents through the inhibition of tubulin polymerization.

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Monte Carlo based modelling approach for designing and predicting cytotoxicity of 2-phenylindole derivatives against breast cancer cell line MCF7

Cited by 20 publications

References 40 publications

Predicting Cytotoxicity of 2-Phenylindole Derivatives Against Breast Cancer Cells Using Index of Ideality of Correlation

Predicting Cytotoxicity of 2-Phenylindole Derivatives Against Breast Cancer Cells Using Index of Ideality of Correlation

Comparative QSAR modeling of 2‐phenylindol derivatives for predicting the anticancer activity using genetic algorithm multiple linear regression and back‐propagation‐artificial neural network techniques

First Report on 3‐(3‐oxoaryl) Indole Derivatives as Anticancer Agents: Microwave Assisted Synthesis, In Vitro Screening and Molecular Docking Studies

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