CoMFA, CoMSIA, HQSAR and molecular docking analysis of ionone-based chalcone derivatives as antiprostate cancer activity

Sharma, Rajesh; Dhingra, Naveen; Patil, Shital

doi:10.4103/0250-474x.180251

Cited by 18 publications

(7 citation statements)

References 35 publications

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“…To validate the reliability of the CoMFA and CoMSIA model, the obtained CoMFA and CoMSIA models were validated by 13 test compounds. The formula of predicted non‐cross‐validated coefficient is calculated by the following equation:

r_{normalpred}^{2}

= 1‐PRESS/SD (Sharma, Dhingra, & Patil, ).

r_{normalpred}^{2}

of the CoMFA and CoMSIA was 0.785 and 0.863, respectively.…”

Section: Resultsmentioning

confidence: 99%

Discovery of 2‐(3,4‐dialkoxyphenyl)‐2‐(substituted pyridazin‐3‐yl)acetonitriles as phosphodiesterase 4 inhibitors with anti‐neuroinflammation potential based on three‐dimensional quantitative structure–activity relationship study

et al. 2018

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Phosphodiesterase 4 (PDE4) inhibitors with potential activities for CNS disorders provide a new therapeutic strategy for depression. To discover PDE4 inhibitors with anti‐neuroinflammation activities, reliable three‐dimensional quantitative structure‐activity relationship (3D‐QSAR) models on our previous reported catecholic PDE4 inhibitors was built with a statistically significant cross‐validated coefficient (q2), conventional coefficient (r2), and good predictive capabilities based on the molecular docking results, using comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) methods. Based on the analysis of CoMFA and CoMSIA contour maps, a series of 2‐(3,4‐dialkoxyphenyl)‐2‐(substituted pyridazin‐3‐yl) acetonitriles 16a–i was designed and synthesized. Among these compounds, compound 16a exhibited good inhibitory activities toward PDE4B1 and PDE4D7 with mid‐nanomolar IC50 values and potential anti‐neuroinflammation activity in BV‐2 cells. Docking simulation of compound 16a in the PDE4 catalytic domain activity pocket revealed that compound 16a maybe assumed a “V‐shaped” conformation, extending the side chain to S‐pocket.

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r_{normalpred}^{2}

= 1‐PRESS/SD (Sharma, Dhingra, & Patil, ).

r_{normalpred}^{2}

of the CoMFA and CoMSIA was 0.785 and 0.863, respectively.…”

Section: Resultsmentioning

confidence: 99%

Discovery of 2‐(3,4‐dialkoxyphenyl)‐2‐(substituted pyridazin‐3‐yl)acetonitriles as phosphodiesterase 4 inhibitors with anti‐neuroinflammation potential based on three‐dimensional quantitative structure–activity relationship study

et al. 2018

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“…Forty-two derivatives were separated into a training set to build the QSAR model, and a test set to validate the QSAR model. Nine derivatives (8,12,15,19,21,27,29,30, and 40) were chosen for the test set arbitrarily and were validated using hierarchical clustering analysis. As shown in Supplementary Materials Fig.…”

Section: Resultsmentioning

confidence: 99%

“…They all belong to the group of synthetic chalcones. As listed above, various chalcones with methoxy or naphthyl groups have been known to show anticancer effects [28][29][30][31]. However, anticancer effects of chalcones with naphthyl group have rarely been studied, and the relationships between their structural properties and cytotoxic effects have not been reported.…”

Section: Resultsmentioning

confidence: 99%

Relation between structures of naphthalenylchalcone derivatives and their cytotoxic effects on HCT116 human colon cancer cells

et al. 2018

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To find potent chemotherapeutic agents, cytotoxic effects of 42 synthetic chalcone derivatives bearing naphthyl groups on HCT116 human colon cancer cell lines were tested using the clonogenic long-term survival assay. The relationships between their half-maximal cell growth inhibitory concentrations (GI 50) and structural properties were obtained using comparative molecular field analysis and comparative molecular similarity indices analysis. The structural conditions that showed maximum cytotoxic effects on the colon cancer cells were determined. In addition, a derivative, (E)-1-(2-hydroxy-4,5-dimethoxyphenyl)-3-(naphthalen-1-yl)prop-2-en-1-one, showing the best GI 50 value, was assessed for stimulating reactive oxygen species (ROS) production. While its treatment on non-tumorigenic epithelial MCF-12A cell line did not affect the intracellular ROS levels, its treatment on MDA-MB-231 human breast cancer cell line showed ROS accumulation. These findings demonstrate that naphthalenylchalcones can be developed as potent chemotherapeutic agents.

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“…This is a necessary step, as different ligand-binding modes and bioactive conformations are possible. Examples of 3D-QSAR are Comparative Molecular Field Analysis (CoMFA) [ 97 ] and Comparative Molecular Similarity Indices Analysis (CoMSIA) [ 98 ]. From the created QSAR models, predictions on the bio-activity and toxicity of other molecules are made.…”

Section: Application Of Molecular Modelling Methods In the Study Omentioning

confidence: 99%

Application of Various Molecular Modelling Methods in the Study of Estrogens and Xenoestrogens

Mazurek

Szeleszczuk

Simonson

et al. 2020

IJMS

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In this review, applications of various molecular modelling methods in the study of estrogens and xenoestrogens are summarized. Selected biomolecules that are the most commonly chosen as molecular modelling objects in this field are presented. In most of the reviewed works, ligand docking using solely force field methods was performed, employing various molecular targets involved in metabolism and action of estrogens. Other molecular modelling methods such as molecular dynamics and combined quantum mechanics with molecular mechanics have also been successfully used to predict the properties of estrogens and xenoestrogens. Among published works, a great number also focused on the application of different types of quantitative structure–activity relationship (QSAR) analyses to examine estrogen’s structures and activities. Although the interactions between estrogens and xenoestrogens with various proteins are the most commonly studied, other aspects such as penetration of estrogens through lipid bilayers or their ability to adsorb on different materials are also explored using theoretical calculations. Apart from molecular mechanics and statistical methods, quantum mechanics calculations are also employed in the studies of estrogens and xenoestrogens. Their applications include computation of spectroscopic properties, both vibrational and Nuclear Magnetic Resonance (NMR), and also in quantum molecular dynamics simulations and crystal structure prediction. The main aim of this review is to present the great potential and versatility of various molecular modelling methods in the studies on estrogens and xenoestrogens.

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CoMFA, CoMSIA, HQSAR and molecular docking analysis of ionone-based chalcone derivatives as antiprostate cancer activity

Cited by 18 publications

References 35 publications

Discovery of 2‐(3,4‐dialkoxyphenyl)‐2‐(substituted pyridazin‐3‐yl)acetonitriles as phosphodiesterase 4 inhibitors with anti‐neuroinflammation potential based on three‐dimensional quantitative structure–activity relationship study

Discovery of 2‐(3,4‐dialkoxyphenyl)‐2‐(substituted pyridazin‐3‐yl)acetonitriles as phosphodiesterase 4 inhibitors with anti‐neuroinflammation potential based on three‐dimensional quantitative structure–activity relationship study

Relation between structures of naphthalenylchalcone derivatives and their cytotoxic effects on HCT116 human colon cancer cells

Application of Various Molecular Modelling Methods in the Study of Estrogens and Xenoestrogens

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