Probing the Energy Landscape of Spectrin R15 and R16 and the Effects of Non-native Interactions.

Understanding the details of a protein folding mechanism can be a challenging and complex task. One system with an interesting folding behavior is the α-spectrin domain, where the R15 folds three-orders of magnitude faster than its homologues R16 and R17, despite having similar structures. The molecular origins that explain these folding rate differences remain unclear, but our previous work revealed that a combined effect produced by non-native interactions could be a reasonable cause for these differences. In this study, we explore further the folding process by identifying the molecular paths, metastable states, and the collective motions that lead these unfolded proteins to their native state conformation. Our results uncovered the differences between the folding pathways for the wild-type R15 and R16 and an R16 mutant. The metastable ensembles that speed down the folding were identified using an energy landscape visualization method (ELViM). These ensembles correspond to similar experimentally reported configurations. Our observations indicate that the non-native interactions are also associated with secondary structure misdocking. This computational methodology can be used as a fast, straightforward protocol for shedding light on systems with unclear folding or conformational traps.

Effects of pH and Salt Concentration on Stability of a Protein G Variant Using Coarse-Grained Models.

The importance of charge-charge interactions in the thermal stability of proteins is widely known. pH and ionic strength play a crucial role in these electrostatic interactions, as well as in the arrangement of ionizable residues in each protein-folding stage. In this study, two coarse-grained models were used to evaluate the effect of pH and salt concentration on the thermal stability of a protein G variant (1PGB-QDD), which was chosen due to the quantity of experimental data exploring these effects on its stability. One of these coarse-grained models, the TKSA, calculates the electrostatic free energy of the protein in the native state via the Tanford-Kirkwood approach for each residue. The other one, CpHMD-SBM, uses a Coulomb screening potential in addition to the structure-based model Cα. Both models simulate the system in constant pH. The comparison between the experimental stability analysis and the computational results obtained by these simple models showed a good agreement. Through the TKSA method, the role of each charged residue in the protein's thermal stability was inferred. Using CpHMD-SBM, it was possible to evaluate salt and pH effects throughout the folding process. Finally, the computational pKa values were calculated by both methods and presented a good level of agreement with the experiments. This study provides, to our knowledge, new information and a comprehensive description of the electrostatic contribution to protein G stability.