Literature DB >> 21470182

Recent advances on aqueous solubility prediction.

Junmei Wang1, Tingjun Hou.   

Abstract

Aqueous solubility is one of the major physiochemical properties to be optimized in drug discovery. It is related to absorption and distribution in the ADME-Tox (Absorption, Distribution, Metabolism, Excretion, and Toxicity). Aqueous solubility and membrane permeability are the two key factors that affect a drug's oral bioavailability. Because of the importance of aqueous solubility, a lot of efforts have been spent on developing reliable models to predict this physiochemical property. Although some progress has been made and a lot of models have been constructed, it is concluded that accurate and reliable aqueous models targeted to predict solubility of drug-like molecules, have not emerged based on the outcome of an aqueous solubility prediction campaign sponsored by Goodman et al. In this review paper, we provide a snapshot of the latest development in the field. The challenges of developing high quality aqueous solubility models as well as the strategies of surmounting those challenges have been discussed. We conclude that the biggest challenge of modeling aqueous solubility is to collect more high quality, unskewed and drug-relevant solubility data which are sufficient diverse to cover most the chemical space of drugs. The second challenge is to develop good descriptors to account for the lattice energy of solvation. In order to develop accurate and predictable in silico solubility models, the key is to collect a sufficient number of high quality experimental data and the suspicious data must be verified. In addition, the molecular descriptors must be relevant to the energies in the solvation process (the lattice energy for crystal packing, the energy of forming cavity in solvent, and the solvation energy), and the models must be carefully cross-validated and evaluated using the external data sets.

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Year:  2011        PMID: 21470182     DOI: 10.2174/138620711795508331

Source DB:  PubMed          Journal:  Comb Chem High Throughput Screen        ISSN: 1386-2073            Impact factor:   1.339


  18 in total

1.  A metal-free organic-inorganic aqueous flow battery.

Authors:  Brian Huskinson; Michael P Marshak; Changwon Suh; Süleyman Er; Michael R Gerhardt; Cooper J Galvin; Xudong Chen; Alán Aspuru-Guzik; Roy G Gordon; Michael J Aziz
Journal:  Nature       Date:  2014-01-09       Impact factor: 49.962

2.  In Silico Prediction of Physicochemical Properties of Environmental Chemicals Using Molecular Fingerprints and Machine Learning.

Authors:  Qingda Zang; Kamel Mansouri; Antony J Williams; Richard S Judson; David G Allen; Warren M Casey; Nicole C Kleinstreuer
Journal:  J Chem Inf Model       Date:  2017-01-09       Impact factor: 4.956

3.  Data Sets Representative of the Structures and Experimental Properties of FDA-Approved Drugs.

Authors:  Dominique Douguet
Journal:  ACS Med Chem Lett       Date:  2018-01-29       Impact factor: 4.345

4.  Quantifying the chameleonic properties of macrocycles and other high-molecular-weight drugs.

Authors:  Adrian Whitty; Mengqi Zhong; Lauren Viarengo; Dmitri Beglov; David R Hall; Sandor Vajda
Journal:  Drug Discov Today       Date:  2016-02-15       Impact factor: 7.851

5.  Characterization of the binding of MRTX1133 as an avenue for the discovery of potential KRASG12D inhibitors for cancer therapy.

Authors:  Abdul Rashid Issahaku; Namutula Mukelabai; Clement Agoni; Mithun Rudrapal; Sahar M Aldosari; Sami G Almalki; Johra Khan
Journal:  Sci Rep       Date:  2022-10-22       Impact factor: 4.996

6.  Encapsulation and Delivery of Crystalline Hydrophobic Nutraceuticals using Nanoemulsions: Factors Affecting Polymethoxyflavone Solubility.

Authors:  Yan Li; Hang Xiao; David Julian McClements
Journal:  Food Biophys       Date:  2012-12-01       Impact factor: 3.114

7.  The Structure, Thermodynamics and Solubility of Organic Crystals from Simulation with a Polarizable Force Field.

Authors:  Michael J Schnieders; Jonas Baltrusaitis; Yue Shi; Gaurav Chattree; Lianqing Zheng; Wei Yang; Pengyu Ren
Journal:  J Chem Theory Comput       Date:  2012-04-13       Impact factor: 6.006

Review 8.  Physiologically based pharmacokinetic models: integration of in silico approaches with micro cell culture analogues.

Authors:  A Chen; M L Yarmush; T Maguire
Journal:  Curr Drug Metab       Date:  2012-07       Impact factor: 3.731

9.  Computational prediction of drug solubility in fasted simulated and aspirated human intestinal fluid.

Authors:  Jonas H Fagerberg; Eva Karlsson; Johan Ulander; Gunilla Hanisch; Christel A S Bergström
Journal:  Pharm Res       Date:  2014-09-04       Impact factor: 4.200

10.  FAF-Drugs3: a web server for compound property calculation and chemical library design.

Authors:  David Lagorce; Olivier Sperandio; Jonathan B Baell; Maria A Miteva; Bruno O Villoutreix
Journal:  Nucleic Acids Res       Date:  2015-04-16       Impact factor: 16.971

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