Literature DB >> 23506031

In silico prediction of aqueous solubility.

John C Dearden1.   

Abstract

The fundamentals of aqueous solubility, and the factors that affect it, are briefly outlined, followed by a short introduction to quantitative structure-property relationships. Early (pre-1990) work on aqueous solubility prediction is summarised, and a more detailed presentation and critical discussion are given of the results of most, if not all, of those published in silico prediction studies from 1990 onwards that have used diverse training sets. A table is presented of a number of studies that have used a 21-compound test set of drugs and pesticides to validate their aqueous solubility models. Finally, the results are given of a test of 15 commercially available software programs for aqueous solubility prediction, using a test set of 122 drugs with accurately measured aqueous solubilities.

Year:  2006        PMID: 23506031     DOI: 10.1517/17460441.1.1.31

Source DB:  PubMed          Journal:  Expert Opin Drug Discov        ISSN: 1746-0441            Impact factor:   6.098


  12 in total

1.  Can we really do computer-aided drug design?

Authors:  Matthew Segall
Journal:  J Comput Aided Mol Des       Date:  2011-12-11       Impact factor: 3.686

2.  Deep architectures and deep learning in chemoinformatics: the prediction of aqueous solubility for drug-like molecules.

Authors:  Alessandro Lusci; Gianluca Pollastri; Pierre Baldi
Journal:  J Chem Inf Model       Date:  2013-07-02       Impact factor: 4.956

3.  Uniting cheminformatics and chemical theory to predict the intrinsic aqueous solubility of crystalline druglike molecules.

Authors:  James L McDonagh; Neetika Nath; Luna De Ferrari; Tanja van Mourik; John B O Mitchell
Journal:  J Chem Inf Model       Date:  2014-03-11       Impact factor: 4.956

4.  Novel high/low solubility classification methods for new molecular entities.

Authors:  Rutwij A Dave; Marilyn E Morris
Journal:  Int J Pharm       Date:  2016-06-24       Impact factor: 5.875

5.  Binary classification of aqueous solubility using support vector machines with reduction and recombination feature selection.

Authors:  Tiejun Cheng; Qingliang Li; Yanli Wang; Stephen H Bryant
Journal:  J Chem Inf Model       Date:  2011-01-07       Impact factor: 4.956

6.  Pushing the limits of solubility prediction via quality-oriented data selection.

Authors:  Murat Cihan Sorkun; J M Vianney A Koelman; Süleyman Er
Journal:  iScience       Date:  2020-12-17

7.  Can small drugs predict the intrinsic aqueous solubility of 'beyond Rule of 5' big drugs?

Authors:  Alex Avdeef; Manfred Kansy
Journal:  ADMET DMPK       Date:  2020-04-25

8.  Prediction of aqueous intrinsic solubility of druglike molecules using Random Forest regression trained with Wiki-pS0 database.

Authors:  Alex Avdeef
Journal:  ADMET DMPK       Date:  2020-03-04

9.  Dendritic cell immunoreceptor is a new target for anti-AIDS drug development: identification of DCIR/HIV-1 inhibitors.

Authors:  Alexandra A Lambert; Arezki Azzi; Sheng-Xiang Lin; Geneviève Allaire; Karianne P St-Gelais; Michel J Tremblay; Caroline Gilbert
Journal:  PLoS One       Date:  2013-07-09       Impact factor: 3.240

Review 10.  Predicting mammalian metabolism and toxicity of pesticides in silico.

Authors:  Robert D Clark
Journal:  Pest Manag Sci       Date:  2018-05-15       Impact factor: 4.845

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