Understanding the α‐helix to coil transition in polypeptides using network rigidity: Predicting heat and cold denaturation in mixed solvent conditions

Abstract

Thermodynamic stability in polypeptides is described using a novel Distance Constraint Model (DCM). Here, microscopic interactions are represented as constraints. A topological arrangement of constraints define a mechanical framework. Each constraint in the framework is associated with an enthalpic and entropic contribution. All accessible topological arrangements of distance constraints form an ensemble of mechanical frameworks, each representing a microstate of the polypeptide. A partition function is calculated exactly using a transfer matrix approach, where in many respects the DCM is similar to the Lifson-Roig model. The crucial difference is that the effect of network rigidity is explicitly calculated for each mechanical framework in the ensemble. Network rigidity is a mechanical interaction that provides a mechanism for long-range molecular cooperativity and enables a proper treatment of the nonadditivity of a microscopic free energy decomposition. Accounting for (1) helix ↔ coil conformation changes along the backbone similar to the Lifson-Roig model, (2) i to i + 4 hydrogen-bond formation ↔ breaking similar to the Zimm-Bragg model, and (3) structured ↔ unstructured solvent interaction (hydration effects), a six-parameter DCM describes normal and inverted helix-coil transitions in polypeptides. Under suitable mixed solvent conditions heat and cold denaturation is predicted. Model parameters are fitted to experimental data showing different degrees of cold denaturation in monomeric polypeptides in aqueous hexafluoroisopropanol (HFIP) solution at various HFIP concentrations. By assuming a linear HFIP concentration dependence (up to 6% by mole fraction) on model parameters, all essential experimentally observed features are captured.

Interplay between desolvation and secondary structure in mediating cosolvent and temperature induced alpha-synuclein aggregation

“…For both peptides in HFIP and αS in TFE, non-monotonic helix induction curves are observed for a limited range of alcohol concentrations, which may reflect enhanced “solvophobicity” at moderate alcohol concentrations, combined with a high heat capacity for disordered states relative to helical conformations [15]. Alternatively, three-state coexistence, which may occur at moderate alcohol concentrations where α-helical structure is marginally stable, could lead to non-monotonic helix induction curves [16]. …”

Thermodynamic Stability and Flexibility Characteristics of Antibody Fragment Complexes

“…The first application of the DCM was to investigate helix–coil transitions using exact transfer matrix methods [8, 17]. Subsequently, a mean-field treatment was developed [7], making investigations of protein stability and flexibility computationally tractable [9, 11, 12, 18–22].…”

A flexible approach for understanding protein stability

“…Building upon FIRST, a computational methodology that directly relates protein stability to conformational flexibility is presented. The approach, called the Distance Constraint Model (DCM), restores the efficacy of free energy decompositions [10–12] by rigorously accounting for non‐additivity of component entropies using network rigidity [13,14]. Working directly with free energies, the DCM is more than 10 10 times faster than standard molecular dynamics simulations, but not without precedence.…”

“…The DCM has recently been applied to polypeptides undergoing normal [13] and inverted [14] α‐helix to coil transitions, where exact transfer matrix methods are employed. In this letter, the DCM is applied to proteins using a mean‐field treatment [17] akin to Landau theory.…”