Literature DB >> 20873842

Lead optimization using matched molecular pairs: inclusion of contextual information for enhanced prediction of HERG inhibition, solubility, and lipophilicity.

George Papadatos1, Muhammad Alkarouri, Valerie J Gillet, Peter Willett, Visakan Kadirkamanathan, Christopher N Luscombe, Gianpaolo Bravi, Nicola J Richmond, Stephen D Pickett, Jameed Hussain, John M Pritchard, Anthony W J Cooper, Simon J F Macdonald.   

Abstract

Previous studies of the analysis of molecular matched pairs (MMPs) have often assumed that the effect of a substructural transformation on a molecular property is independent of the context (i.e., the local structural environment in which that transformation occurs). Experiments with large sets of hERG, solubility, and lipophilicity data demonstrate that the inclusion of contextual information can enhance the predictive power of MMP analyses, with significant trends (both positive and negative) being identified that are not apparent when using conventional, context-independent approaches.

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Year:  2010        PMID: 20873842     DOI: 10.1021/ci100258p

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  29 in total

1.  Automated molecule editing in molecular design.

Authors:  Peter W Kenny; Carlos A Montanari; Igor M Prokopczyk; Fernanda A Sala; Geraldo Rodrigues Sartori
Journal:  J Comput Aided Mol Des       Date:  2013-09-04       Impact factor: 3.686

Review 2.  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

3.  Compilation and physicochemical classification analysis of a diverse hERG inhibition database.

Authors:  Remigijus Didziapetris; Kiril Lanevskij
Journal:  J Comput Aided Mol Des       Date:  2016-10-25       Impact factor: 3.686

4.  The use of matched molecular series networks for cross target structure activity relationship translation and potency prediction.

Authors:  Christopher E Keefer; George Chang
Journal:  Medchemcomm       Date:  2017-10-11       Impact factor: 3.597

5.  QSAR model based on weighted MCS trees approach for the representation of molecule data sets.

Authors:  Bernardo Palacios-Bejarano; Gonzalo Cerruela García; Irene Luque Ruiz; Miguel Ángel Gómez-Nieto
Journal:  J Comput Aided Mol Des       Date:  2013-02-06       Impact factor: 3.686

6.  Chemical transformations that yield compounds with distinct activity profiles.

Authors:  Ye Hu; Jürgen Bajorath
Journal:  ACS Med Chem Lett       Date:  2011-04-13       Impact factor: 4.345

7.  Targeted kinase selectivity from kinase profiling data.

Authors:  Francesca Milletti; Johannes C Hermann
Journal:  ACS Med Chem Lett       Date:  2012-03-14       Impact factor: 4.345

8.  LogD Contributions of Substituents Commonly Used in Medicinal Chemistry.

Authors:  Matthew L Landry; James J Crawford
Journal:  ACS Med Chem Lett       Date:  2019-12-11       Impact factor: 4.345

9.  Predicting the relative binding affinity of mineralocorticoid receptor antagonists by density functional methods.

Authors:  Katarina Roos; Anders Hogner; Derek Ogg; Martin J Packer; Eva Hansson; Kenneth L Granberg; Emma Evertsson; Anneli Nordqvist
Journal:  J Comput Aided Mol Des       Date:  2015-11-16       Impact factor: 3.686

Review 10.  Five Years of the KNIME Vernalis Cheminformatics Community Contribution.

Authors:  Stephen D Roughley
Journal:  Curr Med Chem       Date:  2020       Impact factor: 4.530

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