Parametric models to compute tryptophan fluorescence wavelengths from classical protein simulations

Abstract

Fluorescence spectroscopy is an important method to study protein conformational dynamics and solvation structures. Tryptophan (Trp) residues are the most important and practical intrinsic probes for protein fluorescence due to the variability of their fluorescence wavelengths: Trp residues emit in wavelengths ranging from 308 to 360 nm depending on the local molecular environment. Fluorescence involves electronic transitions, thus its computational modeling is a challenging task. We show that it is possible to predict the wavelength of emission of a Trp residue from classical molecular dynamics simulations by computing the solvent-accessible surface area or the electrostatic interaction between the indole group and the rest of the system. Linear parametric models are obtained to predict the maximum emission wavelengths with standard errors of the order 5 nm. In a set of 19 proteins with emission wavelengths ranging from 308 to 352 nm, the best model predicts the maximum wavelength of emission with a standard error of 4.89 nm and a quadratic Pearson correlation coefficient of 0.81. These models can be used for the interpretation of fluorescence spectra of proteins with multiple Trp residues, or for which local Trp environmental variability exists and can be probed by classical molecular dynamics simulations. © 2018 Wiley Periodicals, Inc.

Role of Nickel in Microbial Pathogenesis

“…As expected, neither Hpn nor Hpnl had measurable fluorescence, while both AmiE and PepA, as pure proteins, had observable fluorescence profiles (Figure 3). The maximum fluorescence for both AmiE and PepA fell within the previously established range for Trp fluorescence maxima [211]. Upon addition of either purified Hpn or purified Hpnl, the fluorescence profile of AmiE and PepA shifted markedly (Figure 3).…”

On the Interpretation of subtilisin Carlsberg Time-Resolved Fluorescence Anisotropy Decays: Modeling with Classical Simulations

“…10−12 The emission wavelength of the crystallographic Trp113 of SC was predicted by Vivian and Callis using QM/MM models 10 and by Lopez and Marti ́nez with classical parametric models. 12 The expected maximum-emission wavelengths were 334 and 337 nm, respectively, consistent with the fact that the Trp113 is partially protected from the solvent.…”

“…9−11 Recently, our group developed empirical models to compute fluorescence emission wavelengths of Trp in proteins using classical MD simulations with the aim of providing a practical tool for the interpretation of experimental fluorescence data. 12 Here we illustrate the importance of modeling methods for the interpretation of fluorophore reorientational dynamics in proteins by a comparative analysis of experimental and computed anisotropy decay rates of the serine protease subtilisin Carlsberg (SC) protein. SC is an important enzyme for industrial applications, and its dynamics in solution has been studied with several methods, such as NMR techniques 13−15 and fluorescence spectroscopy.…”

Combining Experimental Data and Computational Methods for the Non-Computer Specialist

“…Understanding of the process at the atomic level requires the use of complex quantum mechanics calculations, which are in general very computationally demanding. Nevertheless, over the years, different theoretical-computational methods have been proposed to predict the spectra; some have used semi-empirical relation [ 114 ], classical methods [ 115 ], or mixed quantum mechanics strategies [ 116 , 117 ] to provide information on the complex absorption–structure relation.…”

“…For instance, diverse phenomenological models have been proposed to predict the fluorescence emission wavelengths of tryptophans [ 114 , 118 ] or even the decay rates [ 119 ]. Some of the models that correlate well are based on electrostatic interaction of the indole group or on the solvent-accessible surface area [ 114 ]. This type of model allows for an easy interpretation of the fluorescence spectra of proteins using computational methods.…”