Literature DB >> 8808736

Three-dimensional quantitative structure-activity relationships of steroid aromatase inhibitors.

T I Oprea1, A E García.   

Abstract

Inhibition of aromatase, a cytochrome P450 that converts androgens to estrogens, is relevant in the therapeutic control of breast cancer. We investigate this inhibition using a three-dimensional quantitative structure-activity relationship (3D QSAR) method known as Comparative Molecular Field Analysis, CoMFA [Cramer III, R.D. et al., J. Am. Chem. Soc., 110 (1988) 5959]. We analyzed the data for 50 steroid inhibitors [Numazawa, M. et al., J. Med. Chem., 37 (1994) 2198, and references cited therein] assayed against androstenedione on human placental microsomes. An initial CoMFA resulted in a three-component model for log(l/Ki), with an explained variance r2 of 0.885, and a cross-validated q2 of 0.673. Chemometric studies were performed using GOLPE [Baroni, M. et al., Quant. Struct.-Act. Relatsh., 12 (1993) 9]. The CoMFA/GOLPE model is discussed in terms of robustness, predictivity, explanatory power and simplicity. After randomized exclusion of 25 or 10 compounds (repeated 25 times), the q2 for one component was 0.62 and 0.61, respectively, while r2 was 0.674. We demonstrate that the predictive r2 based on the mean activity (Ym) of the training set is misleading, while the test set Ym-based predictive r2 index gives a more accurate estimate of external predictivity. Using CoMFA, the observed differences in aromatase inhibition among C6-substituted steroids are rationalized at the atomic level. The CoMFA fields are consistent with known, potent inhibitors of aromatase, not included in the model. When positioned in the same alignment, these compounds have distinct features that overlap with the steric and electrostatic fields obtained in the CoMFA model. The presence of two hydrophobic binding pockets near the aromatase active site is discussed: a steric bulk tolerant one, common for C4, C6-alpha and C7-alpha substituents, and a smaller one at the C6-beta region.

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Year:  1996        PMID: 8808736     DOI: 10.1007/bf00355042

Source DB:  PubMed          Journal:  J Comput Aided Mol Des        ISSN: 0920-654X            Impact factor:   3.686


  42 in total

1.  High-resolution crystal structure of cytochrome P450cam.

Authors:  T L Poulos; B C Finzel; A J Howard
Journal:  J Mol Biol       Date:  1987-06-05       Impact factor: 5.469

2.  Change correlations in structure-activity studies using multiple regression analysis.

Authors:  J G Topliss; R J Costello
Journal:  J Med Chem       Date:  1972-10       Impact factor: 7.446

3.  Comparative molecular field analysis using GRID force-field and GOLPE variable selection methods in a study of inhibitors of glycogen phosphorylase b.

Authors:  G Cruciani; K A Watson
Journal:  J Med Chem       Date:  1994-08-05       Impact factor: 7.446

4.  19-Hydroxy-4-androsten-17-one: potential competitive inhibitor of estrogen biosynthesis.

Authors:  M Numazawa; A Mutsumi; K Hoshi; R Koike
Journal:  Biochem Biophys Res Commun       Date:  1989-05-15       Impact factor: 3.575

Review 5.  Biochemical and pharmacological development of steroidal inhibitors of aromatase.

Authors:  R W Brueggemeier; P K Li; H H Chen; P P Moh; N E Katlic
Journal:  J Steroid Biochem Mol Biol       Date:  1990-11-20       Impact factor: 4.292

6.  Three-dimensional quantitative structure-activity relationship of human immunodeficiency virus (I) protease inhibitors. 2. Predictive power using limited exploration of alternate binding modes.

Authors:  T I Oprea; C L Waller; G R Marshall
Journal:  J Med Chem       Date:  1994-07-08       Impact factor: 7.446

Review 7.  Aromatase inhibitors in the treatment of breast cancer.

Authors:  A M Brodie
Journal:  J Steroid Biochem Mol Biol       Date:  1994-06       Impact factor: 4.292

Review 8.  Aromatase and its inhibitors in breast cancer treatment--overview and perspective.

Authors:  A M Brodie; R J Santen
Journal:  Breast Cancer Res Treat       Date:  1994       Impact factor: 4.872

9.  A site-directed mutagenesis study of human placental aromatase.

Authors:  D J Zhou; K R Korzekwa; T Poulos; S A Chen
Journal:  J Biol Chem       Date:  1992-01-15       Impact factor: 5.157

10.  Molecular basis of crossreactivity and the limits of antibody-antigen complementarity.

Authors:  J H Arevalo; M J Taussig; I A Wilson
Journal:  Nature       Date:  1993-10-28       Impact factor: 49.962

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  9 in total

1.  Receptor-based 3D QSAR analysis of estrogen receptor ligands--merging the accuracy of receptor-based alignments with the computational efficiency of ligand-based methods.

Authors:  W Sippl
Journal:  J Comput Aided Mol Des       Date:  2000-08       Impact factor: 3.686

2.  Molecular modelling studies on the ORL1-receptor and ORL1-agonists.

Authors:  Britta M Bröer; Marion Gurrath; Hans-Dieter Höltje
Journal:  J Comput Aided Mol Des       Date:  2003-11       Impact factor: 3.686

3.  3D-QSAR illusions.

Authors:  Arthur M Doweyko
Journal:  J Comput Aided Mol Des       Date:  2004 Jul-Sep       Impact factor: 3.686

4.  www.3d-qsar.com: a web portal that brings 3-D QSAR to all electronic devices-the Py-CoMFA web application as tool to build models from pre-aligned datasets.

Authors:  Rino Ragno
Journal:  J Comput Aided Mol Des       Date:  2019-10-08       Impact factor: 3.686

5.  Structure-based 3D QSAR and design of novel acetylcholinesterase inhibitors.

Authors:  W Sippl; J M Contreras; I Parrot; Y M Rival; C G Wermuth
Journal:  J Comput Aided Mol Des       Date:  2001-05       Impact factor: 3.686

Review 6.  Computational prediction of metabolism: sites, products, SAR, P450 enzyme dynamics, and mechanisms.

Authors:  Johannes Kirchmair; Mark J Williamson; Jonathan D Tyzack; Lu Tan; Peter J Bond; Andreas Bender; Robert C Glen
Journal:  J Chem Inf Model       Date:  2012-02-17       Impact factor: 4.956

7.  A structure-activity relationship study of catechol-O-methyltransferase inhibitors combining molecular docking and 3D QSAR methods.

Authors:  Anu J Tervo; Tommi H Nyrönen; Toni Rönkkö; Antti Poso
Journal:  J Comput Aided Mol Des       Date:  2003-12       Impact factor: 3.686

8.  Quantitative structure-activity relationships (QSARs) for estrogen binding to the estrogen receptor: predictions across species.

Authors:  W Tong; R Perkins; R Strelitz; E R Collantes; S Keenan; W J Welsh; W S Branham; D M Sheehan
Journal:  Environ Health Perspect       Date:  1997-10       Impact factor: 9.031

Review 9.  Towards understanding aromatase inhibitory activity via QSAR modeling.

Authors:  Watshara Shoombuatong; Nalini Schaduangrat; Chanin Nantasenamat
Journal:  EXCLI J       Date:  2018-07-20       Impact factor: 4.068

  9 in total

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