Nantasenamat Chanin, Simeon Saw, Owasirikul Wiwat, Songtawee Napat, Lapins Maris, Prachayasittikul Virapong, Wikberg Jarl E S
Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok, 10700, Thailand; Department of Clinical Microbiology and Applied Technology, Faculty of Medical Technology, Mahidol University, Bangkok, 10700, Thailand.
J Comput Chem. 2014 Oct 15;35(27):1951-66. doi: 10.1002/jcc.23708. Epub 2014 Aug 12.
Green fluorescent protein (GFP) has immense utility in biomedical imaging owing to its autofluorescent nature. In efforts to broaden the spectral diversity of GFP, there have been several reports of engineered mutants via rational design and random mutagenesis. Understanding the origins of spectral properties of GFP could be achieved by means of investigating its structure-activity relationship. The first quantitative structure-property relationship study for modeling the spectral properties, particularly the excitation and emission maximas, of GFP was previously proposed by us some years ago in which quantum chemical descriptors were used for model development. However, such simplified model does not consider possible effects that neighboring amino acids have on the conjugated π-system of GFP chromophore. This study describes the development of a unified proteochemometric model in which the GFP chromophore and amino acids in its vicinity are both considered in the same model. The predictive performance of the model was verified by internal and external validation as well as Y-scrambling. Our strategy provides a general solution for elucidating the contribution that specific ligand and protein descriptors have on the investigated spectral property, which may be useful in engineering novel GFP variants with desired characteristics.
绿色荧光蛋白(GFP)因其自身荧光特性在生物医学成像中具有巨大的应用价值。为了拓宽GFP的光谱多样性,已有多篇关于通过合理设计和随机诱变获得工程突变体的报道。通过研究其构效关系可以了解GFP光谱特性的起源。几年前我们曾首次提出利用量子化学描述符进行模型开发,对GFP的光谱特性,特别是激发和发射最大值进行定量构效关系研究。然而,这种简化模型没有考虑相邻氨基酸对GFP发色团共轭π体系可能产生的影响。本研究描述了一种统一的蛋白质化学计量学模型的开发,该模型将GFP发色团及其附近的氨基酸都纳入同一个模型中。通过内部和外部验证以及Y随机化验证了该模型的预测性能。我们的策略为阐明特定配体和蛋白质描述符对所研究光谱特性的贡献提供了一个通用解决方案,这可能有助于设计具有所需特性的新型GFP变体。