Literature DB >> 18189157

QSAR: dead or alive?

Arthur M Doweyko1.   

Abstract

This perspective concerns the methods employed within the current drug discovery community to develop predictive quantitative structure-activity relationships (QSAR). Specifically, a number of cautions are provided which may circumvent misuse and misunderstanding of the technique. Ignorance of such caveats has led to a discouraging tendency of the methods to result in poorly predictive models. Among these pitfalls are the fondness with which we associate correlation with causation, the mesmerizing influence of large numbers of molecular descriptors, the incessant misuse of the leave-one-out paradigm, and finally, the QSAR enigma wherein model predictivity is not a necessary component of a model's usefulness.

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Year:  2008        PMID: 18189157     DOI: 10.1007/s10822-007-9162-7

Source DB:  PubMed          Journal:  J Comput Aided Mol Des        ISSN: 0920-654X            Impact factor:   4.179


  19 in total

1.  Beware of q2!

Authors:  Alexander Golbraikh; Alexander Tropsha
Journal:  J Mol Graph Model       Date:  2002-01       Impact factor: 2.518

Review 2.  Pharmacophore discovery--lessons learned.

Authors:  John H van Drie
Journal:  Curr Pharm Des       Date:  2003       Impact factor: 3.116

3.  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

4.  Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins.

Authors:  R D Cramer; D E Patterson; J D Bunce
Journal:  J Am Chem Soc       Date:  1988-08-01       Impact factor: 15.419

5.  On outliers and activity cliffs--why QSAR often disappoints.

Authors:  Gerald M Maggiora
Journal:  J Chem Inf Model       Date:  2006 Jul-Aug       Impact factor: 4.956

6.  Three-dimensional quantitative similarity-activity relationships (3D QSiAR) from SEAL similarity matrices.

Authors:  H Kubinyi; F A Hamprecht; T Mietzner
Journal:  J Med Chem       Date:  1998-07-02       Impact factor: 7.446

7.  Chance factors in studies of quantitative structure-activity relationships.

Authors:  J G Topliss; R P Edwards
Journal:  J Med Chem       Date:  1979-10       Impact factor: 7.446

8.  Correlation, causation and agreement.

Authors:  G A Diamond
Journal:  Am J Cardiol       Date:  1989-02-01       Impact factor: 2.778

9.  A new method for predicting binding affinity in computer-aided drug design.

Authors:  J Aqvist; C Medina; J E Samuelsson
Journal:  Protein Eng       Date:  1994-03

10.  Quantitative structure-activity relationships for 2-[(phenylmethyl)sulfonyl]pyridine 1-oxide herbicides.

Authors:  A M Doweyko; A R Bell; J A Minatelli; D I Relyea
Journal:  J Med Chem       Date:  1983-04       Impact factor: 7.446

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  18 in total

1.  Computation, experiment and molecular design.

Authors:  Peter W Kenny
Journal:  J Comput Aided Mol Des       Date:  2011-12-11       Impact factor: 3.686

2.  Estimation of influential points in any data set from coefficient of determination and its leave-one-out cross-validated counterpart.

Authors:  Gergely Tóth; Zsolt Bodai; Károly Héberger
Journal:  J Comput Aided Mol Des       Date:  2013-10-20       Impact factor: 3.686

Review 3.  Chemical predictive modelling to improve compound quality.

Authors:  John G Cumming; Andrew M Davis; Sorel Muresan; Markus Haeberlein; Hongming Chen
Journal:  Nat Rev Drug Discov       Date:  2013-12       Impact factor: 84.694

4.  On the interpretation and interpretability of quantitative structure-activity relationship models.

Authors:  Rajarshi Guha
Journal:  J Comput Aided Mol Des       Date:  2008-09-11       Impact factor: 3.686

5.  Molecular properties and CYP2D6 substrates: central nervous system therapeutics case study and pattern analysis of a substrate database.

Authors:  Laura K Chico; Heather A Behanna; Wenhui Hu; Guifa Zhong; Saktimayee Mitra Roy; D Martin Watterson
Journal:  Drug Metab Dispos       Date:  2009-08-06       Impact factor: 3.922

6.  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

7.  Rescoring of docking poses under Occam's Razor: are there simpler solutions?

Authors:  Michael Zhenin; Malkeet Singh Bahia; Gilles Marcou; Alexandre Varnek; Hanoch Senderowitz; Dragos Horvath
Journal:  J Comput Aided Mol Des       Date:  2018-09-01       Impact factor: 3.686

8.  Reliably assessing prediction reliability for high dimensional QSAR data.

Authors:  Jianping Huang; Xiaohui Fan
Journal:  Mol Divers       Date:  2012-12-19       Impact factor: 2.943

9.  A systematic investigation of quaternary ammonium ions as asymmetric phase-transfer catalysts. Application of quantitative structure activity/selectivity relationships.

Authors:  Scott E Denmark; Nathan D Gould; Larry M Wolf
Journal:  J Org Chem       Date:  2011-05-06       Impact factor: 4.354

10.  Prediction of drug distribution in rat and humans using an artificial neural networks ensemble and a PBPK model.

Authors:  Paulo Paixão; Natália Aniceto; Luís F Gouveia; José A G Morais
Journal:  Pharm Res       Date:  2014-05-28       Impact factor: 4.200

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