Unraveling Intermolecular Interactions Effects On Peptide Folding Using Ensemble Reweighting

Molecular Dynamics (MD) simulations are widely used to understand the key interactions in biological processes such as protein folding in solvent mixtures. Common strategies to study these problems include varying the concentration of cosolvents and mutating protein structures. In some cases, increasing the cosolvent concentration favors both the folded state of a protein and direct protein-cosolvent contacts. However, these interactions cannot be directly correlated with enhanced folding, as folding may result from cosolvent-solvent interactions. Here, we present an ensemble reweighting algorithm to address the key effects of numerous molecular interactions in the folding equilibrium of a peptide. We applied the method to a simulation composed of a peptide model (AAQAA)₃ in solutions of trifluoroethanol (TFE) at 50% v/v to investigate how the alcohol stabilizes α-helices. Minimum-Distance Distribution Functions were used to parametrize perturbation functions applied to the most favorable interactions between peptide and solvent mixture, which yielded the energies involved in effectively enhancing or weakening the interactions in the original ensemble. This set of energies was then used to reweight each simulation frame and recalculate the average helical content of the peptide. Our findings reveal that water-peptide and TFE-backbone interactions are detrimental to helical structures, consistent with previous work, whereas interactions between glutamine side chains and cosolvent correlate with increased folding. These observations imply that stabilization by TFE might be partially due to direct interactions with polar side chains of the helical peptide, while TFE prevents water from interacting with the protein structure. Here, we show how the methodology can dissect the molecular contributions of solvation in protein folding. Further applications include studying conformational changes in enzymes upon substrate binding and antigen-antibody key interactions, contributing to drug and protein design.