Literature DB >> 15729857

3D-QSAR illusions.

Arthur M Doweyko1.   

Abstract

3D-QSAR is typically used to construct models (1) to predict activities, (2) to illustrate significant regions, and (3) to provide insight into possible interactions. To the contrary, examples are described herein which make it clear that the predictivity of such models remains elusive, that so-called significant regions are subject to the vagaries of alignment, and that the nature of possible interactions heavily depends on the eye of the beholder. Although great strides have been made in the imaginative use of 3D-descriptors, 3D-QSAR remains largely a retrospective analytical tool. The arbitrary nature of both the alignment paradigm and atom description lends itself to capricious models, which in turn can lead to distorted conclusions. Despite these illusionary pitfalls, predictions can be enhanced when the test set is bounded by the descriptor space represented in the training set. Interpretation of significant interaction regions becomes more meaningful when alignment is constrained by a binding site. Correlations obtained with a variety of atom descriptors suggest choosing useful ones, in particular, in guiding synthetic effort.

Mesh:

Year:  2004        PMID: 15729857     DOI: 10.1007/s10822-004-4068-0

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


  41 in total

1.  3D-QSAR CoMFA study on imidazolinergic I(2) ligands: a significant model through a combined exploration of structural diversity and methodology.

Authors:  N Baurin; E Vangrevelinghe; L Morin-Allory; J Y Mérour; P Renard; M Payard; G Guillaumet; C Marot
Journal:  J Med Chem       Date:  2000-03-23       Impact factor: 7.446

2.  Evaluation of a novel molecular vibration-based descriptor (EVA) for QSAR studies: 2. Model validation using a benchmark steroid dataset.

Authors:  D B Turner; P Willett; A M Ferguson; T W Heritage
Journal:  J Comput Aided Mol Des       Date:  1999-05       Impact factor: 3.686

3.  Three-dimensional quantitative structure-activity relationship of 1,4-dihydropyridines as antitubercular agents.

Authors:  Prashant S Kharkar; Bhavik Desai; Harsukh Gaveria; Bharat Varu; Rajesh Loriya; Yogesh Naliapara; Anamik Shah; Vithal M Kulkarni
Journal:  J Med Chem       Date:  2002-10-24       Impact factor: 7.446

4.  Rational selection of training and test sets for the development of validated QSAR models.

Authors:  Alexander Golbraikh; Min Shen; Zhiyan Xiao; Yun-De Xiao; Kuo-Hsiung Lee; Alexander Tropsha
Journal:  J Comput Aided Mol Des       Date:  2003 Feb-Apr       Impact factor: 3.686

5.  A MATHEMATICAL CONTRIBUTION TO STRUCTURE-ACTIVITY STUDIES.

Authors:  S M FREE; J W WILSON
Journal:  J Med Chem       Date:  1964-07       Impact factor: 7.446

6.  Pharmacophore mapping of a series of 2,4-diamino-5-deazapteridine inhibitors of Mycobacterium avium complex dihydrofolate reductase.

Authors:  Asim Kumar Debnath
Journal:  J Med Chem       Date:  2002-01-03       Impact factor: 7.446

7.  Antileishmanial chalcones: statistical design, synthesis, and three-dimensional quantitative structure-activity relationship analysis.

Authors:  S F Nielsen; S B Christensen; G Cruciani; A Kharazmi; T Liljefors
Journal:  J Med Chem       Date:  1998-11-19       Impact factor: 7.446

8.  Future Papers.

Authors: 
Journal:  J Chem Inf Comput Sci       Date:  1999-05-25

9.  Molecular similarity indices in a comparative analysis (CoMSIA) of drug molecules to correlate and predict their biological activity.

Authors:  G Klebe; U Abraham; T Mietzner
Journal:  J Med Chem       Date:  1994-11-25       Impact factor: 7.446

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

Authors:  T I Oprea; A E García
Journal:  J Comput Aided Mol Des       Date:  1996-06       Impact factor: 3.686

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  26 in total

1.  R-group template CoMFA combines benefits of "ad hoc" and topomer alignments using 3D-QSAR for lead optimization.

Authors:  Richard D Cramer
Journal:  J Comput Aided Mol Des       Date:  2012-06-04       Impact factor: 3.686

2.  Tautomers and topomers: challenging the uncertainties of direct physicochemical modeling.

Authors:  Richard D Cramer
Journal:  J Comput Aided Mol Des       Date:  2010-03-21       Impact factor: 3.686

3.  Theoretical studies on the interaction of partial agonists with the 5-HT2A receptor.

Authors:  Maria Elena Silva; Ralf Heim; Andrea Strasser; Sigurd Elz; Stefan Dove
Journal:  J Comput Aided Mol Des       Date:  2010-11-19       Impact factor: 3.686

4.  QSAR modeling: where have you been? Where are you going to?

Authors:  Artem Cherkasov; Eugene N Muratov; Denis Fourches; Alexandre Varnek; Igor I Baskin; Mark Cronin; John Dearden; Paola Gramatica; Yvonne C Martin; Roberto Todeschini; Viviana Consonni; Victor E Kuz'min; Richard Cramer; Romualdo Benigni; Chihae Yang; James Rathman; Lothar Terfloth; Johann Gasteiger; Ann Richard; Alexander Tropsha
Journal:  J Med Chem       Date:  2014-01-06       Impact factor: 7.446

5.  QSAR modelling of the toxicity to Tetrahymena pyriformis by balance of correlations.

Authors:  A A Toropov; A P Toropova; E Benfenati; A Manganaro
Journal:  Mol Divers       Date:  2009-08-14       Impact factor: 2.943

6.  3D-QSAR studies of triazolopyrimidine derivatives of Plasmodium falciparum dihydroorotate dehydrogenase inhibitors using a combination of molecular dynamics, docking, and genetic algorithm-based methods.

Authors:  Priyanka Shah; Sumit Kumar; Sunita Tiwari; Mohammad Imran Siddiqi
Journal:  J Chem Biol       Date:  2012-02-05

7.  Challenging the gold standard for 3D-QSAR: template CoMFA versus X-ray alignment.

Authors:  Bernd Wendt; Richard D Cramer
Journal:  J Comput Aided Mol Des       Date:  2014-06-17       Impact factor: 3.686

8.  QSAR models for predicting the activity of non-peptide luteinizing hormone-releasing hormone (LHRH) antagonists derived from erythromycin A using quantum chemical properties.

Authors:  Michael Fernández; Julio Caballero
Journal:  J Mol Model       Date:  2007-01-10       Impact factor: 1.810

9.  Modeling of peroxide activation in artemisinin derivatives by serial docking.

Authors:  Roy J Little; Alexis A Pestano; Zaida Parra
Journal:  J Mol Model       Date:  2009-01-14       Impact factor: 1.810

10.  Structure-activity relationship and comparative docking studies for cycloguanil analogs as PfDHFR-TS inhibitors.

Authors:  Prasanna Sivaprakasam; Perrer N Tosso; Robert J Doerksen
Journal:  J Chem Inf Model       Date:  2009-07       Impact factor: 4.956

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