New QSPR study for the prediction of aqueous solubility of drug-like compounds.
Solubility has become one of the key physicochemical screens at early stages of the drug development process. Solubility prediction through Quantitative Structure-Property Relationships (QSPR) modeling is a growing area of modern pharmaceutical research, being compatible with both High Throughput Screening technologies and limited compound availability characteristic of early stages of drug development. We resort to the QSPR theory for analyzing the aqueous solubility exhibited by 145 diverse drug-like organic compounds (0.781 being the average Tanimoto distances between all possible pairs of compounds in the training set). An accurate and generally applicable model is derived, consisting on a linear regression equation that involves three DRAGON molecular descriptors selected from more than a thousand available. Alternatively, we apply the linear QSPR to other 21 commonly employed validation compounds, leading to solubility estimations that compare fairly well with the performance achieved by previously reported Group Contribution Methods.
Duchowicz
Pablo R
PR
Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas INIFTA (UNLP, CCT La Plata-CONICET), Diag. 113 y 64, C.C. 16, Suc.4, La Plata 1900, Argentina. pduchowicz@gmail.com
Talevi
Alan
A
Bruno-Blanch
Luis E
LE
Castro
Eduardo A
EA
D003198:Computer Simulation; D016208:Databases, Factual; D015195:Drug Design; D016014:Linear Models; D015394:Molecular Structure; D009930:Organic Chemicals / Q000737:chemistry*; D004364:Pharmaceutical Preparations / Q000737:chemistry*; D011237:Predictive Value of Tests; D021281:Quantitative Structure-Activity Relationship; D015203:Reproducibility of Results; D012995:Solubility; D013237:Stereoisomerism; D013678:Technology, Pharmaceutical / Q000379:methods*; D014867:Water / Q000737:chemistry
D009930:Organic Chemicals; D004364:Pharmaceutical Preparations; D014867:Water