PhD Scientific Days 2021

PH_II_P: Pharmaceutical Sciences II. Posters

On the correlation between cysteine NMR chemical shifts in peptides and the thiolate acid-base/redox character

Text of the abstract

Aims
The imbalance between oxidants and antioxidants can lead to a disruption of redox signaling by the reactive oxygen/nitrogen species. Although these species have some essential role against infectious agents and in cellular signaling systems, their effects are favorable just if they are presented in low or moderate concentrations.
The fundamental amino acid targeted by these reactive species is the sulfur-containing cysteine. Despite being a pivotal regulator of redox homeostasis and signaling, not all residues of cysteine present in proteins are likely to be oxidized, it will depend on the solvent accessibility, pKa, and polarity of nearby residues.
Our aim was to extend the observed correlation between chemical shifts values and acid-base/redox character of the thiolate to more cysteine containing peptides and, in the forthcoming, making possible to predict thiolate basicities and redox potentials in larger proteins using NMR parameters.

Method
The measurements were carried out on a Varian Unity Inova DDR spectrometer (599.9 MHz for 1H) with a 5 mm 1H{13C/31P-15N} pulse field gradient triple resonance probehead at 298.15±0.1 K. The solvent was H2O:D2O 95:5 (V/V), ionic strength was adjusted to 0.15 mol/L.

Results
The 1H and 1H-13C HSQC NMR spectra of the compounds were recorded at pH values that correspond to plateaus on the charged state of the compounds. These data afforded the species-specific chemical shift values of the major microspecies. The species-specific chemical shifts of the minor protonation microspecies were determined using Sudmeier-Reilly type equations. A linear regression model was used to find correlation between the chemical shift and the previously determined species-specific protonation constants.

Conclusion
Since protonation constant values correlate with redox potentials, this method can in principle be used to predict the redox behavior of redox enzymes based on chemical shift data alone.

Funding
Supported by the ÚNKP-20-4-II-SE-3 New National Excellence Program of the Ministry for Innovation and Technology from the source of the National Research, Development and Innovation Fund.

University and Doctoral School

Semmelweis University, Doctoral School of Pharmaceutical Sciences