Recent Advances on Aqueous Solubility Prediction

被引:94
|
作者
Wang, Junmei [1 ]
Hou, Tingjun [2 ,3 ]
机构
[1] Univ Texas SW Med Ctr Dallas, Dept Pharmacol, Dallas, TX 75390 USA
[2] Soochow Univ, Inst Funct Nano & Soft Mat Lab FUNSOM, Suzhou 215123, Jiangsu, Peoples R China
[3] Soochow Univ, Jiangsu Key Lab Carbon Based Funct Mat & Devices, Suzhou 215123, Jiangsu, Peoples R China
关键词
Solubility; solubility challenge; in silico modeling; drug design; DRUG-LIKE COMPOUNDS; ELECTROTOPOLOGICAL STATE INDEXES; ORGANIC-COMPOUNDS; DIVERSE SET; MOLECULAR-STRUCTURE; WATER SOLUBILITY; ADME PROPERTIES; MELTING-POINT; QSAR MODELS; QSPR MODELS;
D O I
10.2174/138620711795508331
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:328 / 338
页数:11
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