Inferring a weighted elastic network from partial unfolding with coarse-grained simulations

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.

Small Neutral Crowding Solute Effects on Protein Folding Thermodynamic Stability and Kinetics

Molecular crowding is a ubiquitous phenomenon in biological systems, with significant consequences on protein folding and stability. Small compounds, such as the osmolyte trimethylamine N-oxide (TMAO), can also present similar effects. To analyze the effects arising from these solute-like molecules, we performed a series of crowded coarse-grained folding simulations. Two well-known proteins were chosen, CI2 and SH3, modeled by the alpha-carbon-structure-based model. In the simulations, the crowding molecules were represented by low-sized neutral atom beads in different concentrations. The results show that a low level of the volume fraction occupied by neutral agents can change protein stability and folding kinetics for the two systems. However, the kinetics were shown to be unaffected in their respective folding temperatures. The faster kinetics correlates with changes in the folding route for systems at the same temperature, where non-native contacts were shown to be relevant. The transition states of the two systems with and without crowders are similar. In the case of SH3, there are differences in the structuring of two strands, which may be associated with the increase in its folding rate, in addition to the destabilization of the denatured ensemble. The present study also detected a crossover in the thermodynamic stability behavior, previously observed experimentally and theoretically. As the temperature increases, crowders change from destabilizing to stabilizing agents.

PathMolD-AB: Spatiotemporal pathways of protein folding using parallel molecular dynamics with a coarse-grained model

Solving the protein folding problem (PFP) is one of the grand challenges still open in computational biophysics. Globular proteins are believed to evolve from initial configurations through folding pathways connecting several thermodynamically accessible states in a free energy landscape until reaching its minimum, inhabited by the stable native structures. Despite its huge computational burden, molecular dynamics (MD) is the leading approach in the PFP studies by preserving the Newtonian temporal evolution in the canonical ensemble. Non-trivial improvements are provided by highly parallel implementations of MD in cost-effective GPUs, concomitant to multiscale descriptions of proteins by coarse-grained minimalist models. In this vein, we present the PathMolD-AB framework, a comprehensive software package for massively parallel MD simulations using the canonical ensemble, structural analysis, and visualization of the folding pathways using the minimalist AB-model. It has, also, a tool to compare the results with proteins re-scaled from the PDB. We simulate and analyze, as case studies, the folding of four proteins: 13FIBO, 2GB1, 1PLC and 5ANZ, with 13, 55, 99 and 223 amino acids, respectively. The datasets generated from simulations correspond to the MD evolution of 3500 folding pathways, encompassing 35×106 states, which contains the spatial amino acid positions, the protein free energies and radii of gyration at each time step. Results indicate that the speedup of our approach grows logarithmically with the protein length and, therefore, it is suited for most of the proteins in the PDB. The predicted structures simulated by PathMolD-AB were similar to the re-scaled biological structures, indicating that it is promising for the study of the PFP study.

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.

Quantifying Nonnative Interactions in the Protein-Folding Free-Energy Landscape

Protein folding is a central problem in biological physics. Energetic roughness is an important aspect that controls protein-folding stability and kinetics. The roughness is associated with conflicting interactions in the protein and is also known as frustration. Recent studies indicate that an addition of a small amount of energetic frustration may enhance folding speed for certain proteins. In this study, we have investigated the conditions under which frustration increases the folding rate. We used a Cα structure-based model to simulate a group of proteins. We found that the free-energy barrier at the transition state (ΔF) correlates with nonnative-contact variation (ΔA), and the simulated proteins are clustered according to their fold motifs. These findings are corroborated by the Clementi-Plotkin analytical model. As a consequence, the optimum frustration regime for protein folding can be predicted analytically.

NTL9 Folding at Constant pH: The Importance of Electrostatic Interaction and pH Dependence

The folding process of the N-terminal domain of ribosomal protein L9 (NTL9) was investigated at constant-pH computer simulations. Evaluation of the role of electrostatic interaction during folding was carried out by including a Debye-Hückel potential into a Cα structure-based model (SBM). In this study, the charges of the ionizable residues and the electrostatic potential are susceptible to the solution conditions, such as pH and ionic strength, as well as to the presence of charged groups. Simulations were performed under different pHs, and the results were validated by comparing them with experimental values of pKa and with denaturation experiment data. Also, the free energy profiles, Φ-values, and folding routes were calculated for each condition. It was shown how charges vary along the folding under different pH, which is subject to different scenarios. This study reveals how simplified models can capture essential physical features, reproducing experimental results, and presenting the role of electrostatic interactions before, during, and after the transition state.