Enhancing the population of the encounter complex affects protein complex formation efficiency

FEBS Journal, vol. 289, pp. 535–548

Abstract

Optimal charge distribution is considered to be important for efficient formation of protein complexes. Electrostatic interactions guide encounter complex formation that precedes the formation of an active protein complex. However, disturbing the optimized distribution by introduction of extra charged patches on cytochrome c peroxidase does not lead to a reduction in productive encounters with its partner cytochrome c. To test whether a complex with a high population of encounter complex is more easily affected by suboptimal charge distribution, the interactions of cytochrome c mutant R13A with wild-type cytochrome c peroxidase and a variant with an additional negative patch were studied. The complex of the peroxidase and cytochrome c R13A was reported to have an encounter state population of 80%, compared to 30% for the wild-type cytochrome c. NMR analysis confirms the dynamic nature of the interaction and demonstrates that the mutant cytochrome c samples the introduced negative patch. Kinetic experiments show that productive complex formation is fivefold to sevenfold slower at moderate and high ionic strength values for cytochrome c R13A but the association rate is not affected by the additional negative patch on cytochrome c peroxidase, showing that the total charge on the protein surface can compensate for less optimal charge distribution. At low ionic strength (44 mm), the association with the mutant cytochrome c reaches the same high rates as found for wild-type cytochrome c, approaching the diffusion limit.

Authors 4

1. Antonella Di Savino Aachen Institute of Chemistry Leiden University The Netherlands Institute of Chemistry, Leiden University

   Leiden University

   Affiliation as printed

   Institute of Chemistry Leiden University The Netherlands

   Institute of Chemistry, Leiden University, The Netherlands

2. Johannes M. Foerster

   University of Bayreuth

   Affiliation as printed

   Computational Biochemistry University of Bayreuth Germany

   Computational Biochemistry, University of Bayreuth, Germany

3. G. Matthias Ullmann

   University of Bayreuth

   Affiliation as printed

   Computational Biochemistry University of Bayreuth Germany

   Computational Biochemistry, University of Bayreuth, Germany

4. Marcellus Ubbink corresponding Aachen Institute of Chemistry Leiden University The Netherlands Institute of Chemistry, Leiden University

   Leiden University

   Affiliation as printed

   Institute of Chemistry Leiden University The Netherlands

   Institute of Chemistry, Leiden University, The Netherlands