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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Parametric models to compute tryptophan fluorescence wavelengths from classical protein simulations

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Lopez, Alvaro J. [1, 2] ; Martinez, Leandro [1, 2]
Total Authors: 2
[1] Univ Estadual Campinas, Inst Chem, Campinas, SP - Brazil
[2] Univ Estadual Campinas, Ctr Computat Engn & Sci, Campinas, SP - Brazil
Total Affiliations: 2
Document type: Journal article
Source: Journal of Computational Chemistry; v. 39, n. 19, p. 1249-1258, JUL 15 2018.
Web of Science Citations: 1

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. (c) 2018 Wiley Periodicals, Inc. (AU)

FAPESP's process: 13/05475-7 - Computational methods in optimization
Grantee:Sandra Augusta Santos
Support type: Research Projects - Thematic Grants
FAPESP's process: 10/16947-9 - Correlations between dynamics, structure and function in protein: computer simulations and algorithms
Grantee:Leandro Martinez
Support type: Regular Research Grants
FAPESP's process: 13/08293-7 - CCES - Center for Computational Engineering and Sciences
Grantee:Munir Salomao Skaf
Support type: Research Grants - Research, Innovation and Dissemination Centers - RIDC