Literature DB >> 23306465

Inflation of correlation in the pursuit of drug-likeness.

Peter W Kenny1, Carlos A Montanari.   

Abstract

Drug-likeness is a frequently invoked, although not always precisely defined, concept in drug discovery. Opinions on drug-likeness are to a large extent shaped by the relationships that are observed between surrogate measures of drug-likeness (e.g. aqueous solubility; permeability; pharmacological promiscuity) and fundamental physicochemical properties (e.g. lipophilicity; molecular size). This article draws on examples from the literature to highlight approaches to data analysis that exaggerate trends in data and the term correlation inflation is introduced in the context of drug discovery. Averaging groups of data points prior to analysis is a common cause of correlation inflation and results from analysis of binned continuous data should always be treated with caution.

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Year:  2013        PMID: 23306465     DOI: 10.1007/s10822-012-9631-5

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


  23 in total

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2.  Impact of lipophilic efficiency on compound quality.

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3.  Computation, experiment and molecular design.

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

4.  Medicinal chemistry matters - a call for discipline in our discipline.

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Review 5.  On effect size.

Authors:  Ken Kelley; Kristopher J Preacher
Journal:  Psychol Methods       Date:  2012-04-30

Review 6.  The effect of plasma protein binding on in vivo efficacy: misconceptions in drug discovery.

Authors:  Dennis A Smith; Li Di; Edward H Kerns
Journal:  Nat Rev Drug Discov       Date:  2010-12       Impact factor: 84.694

Review 7.  Can we rationally design promiscuous drugs?

Authors:  Andrew L Hopkins; Jonathan S Mason; John P Overington
Journal:  Curr Opin Struct Biol       Date:  2006-01-25       Impact factor: 6.809

8.  High throughput solubility determination with application to selection of compounds for fragment screening.

Authors:  Nicola Colclough; Alison Hunter; Peter W Kenny; Rod S Kittlety; Lynsey Lobedan; Kin Y Tam; Mark A Timms
Journal:  Bioorg Med Chem       Date:  2008-05-10       Impact factor: 3.641

9.  Escape from flatland: increasing saturation as an approach to improving clinical success.

Authors:  Frank Lovering; Jack Bikker; Christine Humblet
Journal:  J Med Chem       Date:  2009-11-12       Impact factor: 7.446

10.  Hydrogen bonding. 32. An analysis of water-octanol and water-alkane partitioning and the delta log P parameter of seiler.

Authors:  M H Abraham; H S Chadha; G S Whiting; R C Mitchell
Journal:  J Pharm Sci       Date:  1994-08       Impact factor: 3.534

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  20 in total

Review 1.  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

Review 2.  An analysis of the attrition of drug candidates from four major pharmaceutical companies.

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3.  The influence of hydrogen bonding on partition coefficients.

Authors:  Nádia Melo Borges; Peter W Kenny; Carlos A Montanari; Igor M Prokopczyk; Jean F R Ribeiro; Josmar R Rocha; Geraldo Rodrigues Sartori
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4.  Computer-aided drug discovery research at a global contract research organization.

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Journal:  J Comput Aided Mol Des       Date:  2016-11-01       Impact factor: 3.686

5.  Improving the plausibility of success with inefficient metrics.

Authors:  Michael D Shultz
Journal:  ACS Med Chem Lett       Date:  2013-11-21       Impact factor: 4.345

6.  Ligand efficiency metrics considered harmful.

Authors:  Peter W Kenny; Andrei Leitão; Carlos A Montanari
Journal:  J Comput Aided Mol Des       Date:  2014-06-05       Impact factor: 3.686

7.  The analysis of the market success of FDA approvals by probing top 100 bestselling drugs.

Authors:  Jaroslaw Polanski; Jacek Bogocz; Aleksandra Tkocz
Journal:  J Comput Aided Mol Des       Date:  2016-04-28       Impact factor: 3.686

Review 8.  Counting on natural products for drug design.

Authors:  Tiago Rodrigues; Daniel Reker; Petra Schneider; Gisbert Schneider
Journal:  Nat Chem       Date:  2016-04-25       Impact factor: 24.427

9.  FlavoDb: a web-based chemical repository of flavonoid compounds.

Authors:  Baban S Kolte; Sanjay R Londhe; Kamini T Bagul; Shristi P Pawnikar; Mayuri B Goundge; Rajesh N Gacche; Rohan J Meshram
Journal:  3 Biotech       Date:  2019-10-31       Impact factor: 2.406

10.  How We Think about Targeting RNA with Small Molecules.

Authors:  Matthew G Costales; Jessica L Childs-Disney; Hafeez S Haniff; Matthew D Disney
Journal:  J Med Chem       Date:  2020-03-26       Impact factor: 7.446

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