Predicting pharmacophore signals for post-coital antifertility activity of 1-trifluoromethyl-1,2,2-triphenylethylene derivatives: a statistical approximation using E-state index

Mukherjee, Subhendu; Mukherjee, Arup; Saha, Achintya

doi:10.1016/j.bmcl.2003.12.020

Cited by 6 publications

(5 citation statements)

References 32 publications

(23 reference statements)

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“…The importance of atoms C 1 and C 15 can be conceptualized as the influence of unsaturation in the C 1 −C 15 linkage. The significance of an ethylenic fragment in nonsteroidal estrogens has been explored in a series of diverse compounds containing the diarylhydroxy unit. − , In terms of binding selectivity to ER (β/α), the best model (eq 3) generated with 78% binding selectivity indicated that increase in E -state values of atoms O 6 and C 11 will decrease selectivity of ER β over ER α . Consequently, substituents that tend to decrease the e - density around these atoms should result in increased selectivity.…”

Section: Discussionmentioning

confidence: 99%

“…The 1,1-diaryl component is a chemical moiety common to many potential SERMs, such as tamoxifen, toremifene, and idoxifene . Our group has also explored this feature to be prime pharmacophore signals for estrogen mediated bioactivities of a different group of compounds, viz., 1-trifluoromethyl-1,2,2-triphenylethylenes, bromotriphenylethylenes, and triphenylacrylonitriles through Quantitative Structure−Activity Relationship (QSAR) studies. − …”

Section: Introductionmentioning

confidence: 99%

“…15 Our group has also explored this feature to be prime pharmacophore signals for estrogen mediated bioactivities of a different group of compounds, viz., 1-trifluoromethyl-1,2,2triphenylethylenes, bromotriphenylethylenes, and triphenylacrylonitriles through Quantitative Structure-Activity Relationship (QSAR) studies. [16][17][18] QSARs are mathematical methodology, statistically validated, and mostly used to correlate experimental or calculated properties derived from chemical structures with biological activities. They also may be applied to predict the activity values of nonsynthesized compounds structurally related to the training set.…”

Section: Introductionmentioning

confidence: 99%

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Pharmacophore Mapping of Selective Binding Affinity of Estrogen Modulators through Classical and Space Modeling Approaches: Exploration of Bridged-Cyclic Compounds with Diarylethylene Linkage

Mukherjee

Nagar

Mullick

et al. 2007

J. Chem. Inf. Model.

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Research on Selective Estrogen Receptor Modulators (SERMs) has been driven by interest in discovering target selective molecules. In view of such significance, the present work explored the pharmacophores of estrogen receptor (ER) subtypes specific binding affinities of diverse compounds belonging to the category of bridged bicyclic-1,1-diarylethylene derivatives. Implementing classical QSAR and CATALYST based space-modeling approaches, it has been explored that attachment of aryl ring systems to unsaturated linkages, availability of phenolic hydroxyl group, global hydrophobicity, and stereochemistry of certain functional groups might be important for governing the subtype specific estrogenic behavior of this group of compounds. Supplementing this deduction, critical interfeature distances between hydrogen bond acceptor, hydrophobic, and ring aromatic features along with steric influence are found to primarily influence the ER-subtypes specific binding of this series of compounds.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Pharmacophore Mapping of Selective Binding Affinity of Estrogen Modulators through Classical and Space Modeling Approaches: Exploration of Bridged-Cyclic Compounds with Diarylethylene Linkage

Mukherjee

Nagar

Mullick

et al. 2007

J. Chem. Inf. Model.

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“…Our group has explored the prime pharmacophore signals for estrogen mediated bioactivities of a different group of compounds through Quantitative Structure Activity Relationships (QSAR) studies. [24][25][26] Attempts range from the use of simple two-dimensional 27) graph theoretical parameters and semiemperical quantum chemical methods 28) to highly sophisticated three dimensional (3D) approaches. [29][30][31][32][33][34] Structurally diverse 60 environmental estrogens 27) are classified through QSAR studies.…”

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confidence: 99%

Molecular Design Based on Receptor-Independent Pharmacophore: Application to Estrogen Receptor Ligands

Islam

Nagar

Das

et al. 2008

Biological & Pharmaceutical Bulletin

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Estrogens, a group of steroid hormones, act primarily by regulating gene expression after binding with estrogen receptor (ER), a nuclear ligand-activated transcription factor, translocates to the nucleus after dimer formation, enhances the gene transcription. Estrogen Receptor Modulators (ERMs) have selective agonist and antagonist effects to different tissues, and the purpose of research on ERMs is to identify new potent and less toxic drug molecules. The present study has been focused on finding the structural requirements of ER ligand, using receptor-independent pharmacophore space modeling studies that can explore 3D structural features and configurations, responsible for the biological activity of structurally diverse compounds. The studies show (R‫,549.0؍‬ RMSD‫,681.2؍‬ D Dcost‫)453.776؍‬ the importance of hydrogen bond acceptors in the aromatic rings and a planner hydrophobic region in the molecular architecture along with critical geometrical distance between features are effectively crucial for binding with ER.

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“…13) We had earlier established some basic pharmacophore features of different triphenylethylenes with trifluoromethyl as the fourth substituent. 14) Consequently, the present work was taken up as continuation of the previous attempt in defining pharmacophore signals of different triphenylethylenes and is based on a series of triphenylethylenes with CN as the fourth substituent. The estrogenic activities exhibited by hydroxy, methylated substituents and bulky functional groups on different triphenylacrylonitrile derivatives have been reported.…”

mentioning

confidence: 99%

QSAR Studies with E-State Index: Predicting Pharmacophore Signals for Estrogen Receptor Binding Affinity of Triphenylacrylonitriles

Mukherjee

Saha

2005

Biological & Pharmaceutical Bulletin

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Estrogens are endocrine regulators of both the male and female reproductive systems like the mammary gland, uterus, ovary, testis and prostate. They also play essential roles in non-target tissues, e.g., bone, liver, or in the cardiovascular system, where estrogens have protective actions.1-3) Such effects on different organs are the result of the interaction with the estrogen receptor (ER), of which two subtypes (ER a and ER b ) are presently known. 4,5) The interaction with ER is also involved for the treatment in a range of diseases such as breast cancer, osteoporosis, endometrial cancer, and prostate hypertrophy.6) ER is a member of the nuclear hormone receptor super family.7) The principal endogenous ligand for ER in most species is 17b estradiol (E 2 ). Over the years, many synthetic ligands have been investigated as potential analogues of E 2 , 8,9) in the search for agents that would be useful in regulating fertility, in preventing and treating breast cancer and other therapeutic areas. Selective estrogen receptor modulators (SERMs) that show tissue-dependent agonistic or antagonistic behavior, are used as first line treatment for estrogenresponsive breast cancer and for therapy against osteoporosis. 10,11) This pure estrogen antagonists (anti-estrogens) are currently in clinical development for breast cancer treatment. 12)Several estrogenic triphenylethylenes having an NO 2 , Cl or ethyl fragment as fourth substituent on the ethylene have been investigated as therapeutic agents.13) We had earlier established some basic pharmacophore features of different triphenylethylenes with trifluoromethyl as the fourth substituent.14) Consequently, the present work was taken up as continuation of the previous attempt in defining pharmacophore signals of different triphenylethylenes and is based on a series of triphenylethylenes with CN as the fourth substituent. The estrogenic activities exhibited by hydroxy, methylated substituents and bulky functional groups on different triphenylacrylonitrile derivatives have been reported. 15,16) The present study explores selectivity requirements of such diverse sequence of hydroxylated and non-hydroxylated triphenylacrylonitriles, including compounds with bulky hydrophobic substituents for binding to calf uterus estrogen receptor (ER). 17)Structure-activity relationships has been drawn, investigating topological features of constituting atoms of the triphenylacrylonitrile molecular architecture for characterization of unique pharmacophore features.Topological models directly give structural information to guide design of new molecules 18) and may predict three-dimensional structural parameters, as well.19) The electrotopological state (E-State) of atoms has proved to be a significant tool in elucidating major drug-receptor interactions. [20][21][22] An atom in a molecule is part of a field of information with regard to electronic influences and topological surrounding. 20,23) Quantification of influence of this field on any atom, can correlate to the biological performance of...

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Predicting pharmacophore signals for post-coital antifertility activity of 1-trifluoromethyl-1,2,2-triphenylethylene derivatives: a statistical approximation using E-state index

Cited by 6 publications

References 32 publications

Pharmacophore Mapping of Selective Binding Affinity of Estrogen Modulators through Classical and Space Modeling Approaches: Exploration of Bridged-Cyclic Compounds with Diarylethylene Linkage

Pharmacophore Mapping of Selective Binding Affinity of Estrogen Modulators through Classical and Space Modeling Approaches: Exploration of Bridged-Cyclic Compounds with Diarylethylene Linkage

Molecular Design Based on Receptor-Independent Pharmacophore: Application to Estrogen Receptor Ligands

QSAR Studies with E-State Index: Predicting Pharmacophore Signals for Estrogen Receptor Binding Affinity of Triphenylacrylonitriles

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