A theoretical method to compute sequence dependent configurational properties in charged polymers and proteins.

Area of Science:

• Biophysics
• Computational Biology
• Polymer Physics

Background:

• Proteins and heteropolymers possess complex configurational properties influenced by charge and excluded volume interactions.
• Understanding these properties is crucial for predicting protein behavior and function, especially in their unfolded states.

Purpose of the Study:

• To develop a general analytical formalism for computing configurational properties of heteropolymers, explicitly considering sequence charge distribution and excluded volume.
• To predict the average distance between monomers and the relative sizes of polymer chains based on their sequence characteristics.

Main Methods:

• A variational approach is used to develop an analytical model.
• The model's predictions are benchmarked against all-atom Monte Carlo simulations of synthetic polyampholyte sequences.
• The model is applied to analyze the unfolded state dimensions of thermophilic and mesophilic proteins.

Main Results:

• The analytical model accurately captures the strong sequence dependence of the radius of gyration for synthetic polyampholytes (R(2) = 0.9) without fitting parameters.
• Thermophilic proteins exhibit a statistically significant more compact disordered ensemble compared to their mesophilic counterparts when considering only sequence-encoded electrostatic effects.

Conclusions:

• The developed formalism provides a powerful, parameter-free tool for predicting heteropolymer configurational properties, highlighting the critical role of sequence charge patterning.
• The findings suggest intrinsic differences in the disordered states of thermophilic and mesophilic proteins, with implications for protein evolution and function.
• This analytical method enables high-throughput analysis for broad applications in proteomics and other heteropolymeric systems.