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Illuminating the origins of spectral properties of green fluorescent proteins via proteochemometric and molecular modeling

  • Chanin Nantasenamat
  • , Saw Simeon
  • , Wiwat Owasirikul
  • , Napat Songtawee
  • , Maris Lapins
  • , Virapong Prachayasittikul
  • , Jarl E.S. Wikberg
  • Mahidol University
  • Uppsala University

Research output: Contribution to journal › Article › peer-review

4 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)1951-1966
Number of pages16
JournalJournal of Computational Chemistry
Volume35
Issue number27
DOIs
Publication statusPublished - 15 Oct 2014

Keywords

  • Chromophore
  • Data mining
  • Green fluorescent protein
  • Molecular modeling
  • Proteochemometrics

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