Schüller Andreas, Goh Garrett Benjamin, Kim Hanjo, Lee Jun-Seok, Chang Young-Tae
Duke-NUS Graduate Medical School, Program in Emerging Infectious Diseases, 8 College Road, Singapore 169857.
Medicinal Chemistry Programme, National University of Singapore, 3 Science Drive 3, Singapore 117543.
Mol Inform. 2010 Oct 11;29(10):717-29. doi: 10.1002/minf.201000089. Epub 2010 Oct 18.
A quantitative structure-fluorescence property relationship (QSPR) analysis of a large 288-membered library based on a single fluorescent BODIPY scaffold is presented for the first time. BODIPY is a versatile fluorescent scaffold with outstanding photophysical properties. Absorption (λabs ) and fluorescence emission (λem ) wavelength maxima were modeled with help of stepwise multiple linear regression (MLR) and support vector regression (SVR). The models were rigorously validated by 10-times 10-fold cross-validation (CV), y-scrambling CV and with an external validation set. Non-linear SVR models (R(2) =0.92 and Q(2) =0.71 for λabs ; R(2) =0.89 and Q(2) =0.69 for λem ) performed significantly better than linear models. A small root mean squared error (RMSE) of 5.62 nm and 11.07 nm was achieved for λabs and λem , respectively, and confirmed by external validation. A novel intramolecular charge transfer descriptor was developed based on the QSPR analysis and its inclusion in the modeling significantly improved models of λem . We conclude that QSPR is a useful tool for modeling λabs and λem of BODIPY fluorophores and suggest QSPR as an ideal partner for the design of compounds with tailored fluorescence properties in a diversity-oriented fluorescence library approach (DOFLA).
首次提出了基于单个荧光硼二吡咯（BODIPY）支架的288个成员的大型文库的定量结构-荧光性质关系（QSPR）分析。BODIPY是一种具有出色光物理性质的通用荧光支架。借助逐步多元线性回归（MLR）和支持向量回归（SVR）对吸收（λabs）和荧光发射（λem）波长最大值进行了建模。通过10次10倍交叉验证（CV）、y-打乱CV和外部验证集对模型进行了严格验证。非线性SVR模型（λabs的R(2)=0.92，Q(2)=0.71；λem的R(2)=0.89，Q(2)=0.69）的性能明显优于线性模型。λabs和λem的均方根误差（RMSE）分别为5.62 nm和11.07 nm，并通过外部验证得到证实。基于QSPR分析开发了一种新型分子内电荷转移描述符，将其纳入建模显著改善了λem模型。我们得出结论，QSPR是用于对BODIPY荧光团的λabs和λem进行建模的有用工具，并建议将QSPR作为一种理想的伙伴，以多样性导向荧光文库方法（DOFLA）设计具有定制荧光性质的化合物。
