A QM-MD simulation approach to the analysis of FRET processes in (bio)molecular systems. A case study: complexes of E. coli purine nucleoside phosphorylase and its mutants with formycin A

Abstract

Predicting FRET pathways in proteins using computer simulation techniques is very important for reliable interpretation of experimental data. A novel and relatively simple methodology has been developed and applied to purine nucleoside phosphorylase (PNP) complexed with a fluorescent ligand — formycin A (FA). FRET occurs between an excited Tyr residue (D*) and FA (A). This study aims to interpret experimental data that, among others, suggests the absence of FRET for the PNPF159A mutant in complex with FA, based on novel theoretical methodology. MD simulations for the protein molecule containing D*, and complexed with A, are carried out. Interactions of D* with its molecular environment are accounted by including changes of the ESP charges in S1, compared to S0, and computed at the SCF-CI level. FRET probability WF depends on the inverse six-power of the D*-A distance, Rda. The orientational factor 0 < k2 < 4 between D* and A is computed and included in the analysis. Finally WF is time-averaged over the MD trajectories resulting in its mean value. The red-shift of the tyrosinate anion emission and thus lack of spectral overlap integral and thermal energy dissipation are the reasons for the FRET absence in the studied mutants at pH 7 and above. The presence of the tyrosinate anion results in a competitive energy dissipation channel and red-shifted emission, thus in consequence in the absence of FRET. These studies also indicate an important role of the phenyl ring of Phe159 for FRET in the wild-type PNP, which does not exist in the Ala159 mutant, and for the effective association of PNP with FA. In a more general context, our observations point out very interesting and biologically important properties of the tyrosine residue in its excited state, which may undergo spontaneous deprotonation in the biomolecular systems, resulting further in unexpected physical and/or biological phenomena. Until now, this observation has not been widely discussed in the literature.

Application of molecular dynamics simulations in the study of protein-ligand interactions

“…Along with the increasing of computing power, the motional phenomena of larger and more complex systems can be explored to solve meaningful problems using MD simulations. [6][7][8][9] More importantly, theoretical study on biological systems possesses great advantages on providing very detailed information of molecular motion that experiments on the actual systems may easily failed to have. As realizing its features and power, a great variety of studies on motional phenomena of biological systems, for instance nucleic acids and proteins, were explored by MD simulations.…”