Biomolecules rarely function in isolation, hence a thorough understanding of biological processes is dependent upon an examination of complexes of biomolecules, and the interactions between complexes. For example, large-scale motions occur and are often essential for biomolecule function, especially with regard to proteins. Theoretical approaches developed for folding which incorporate the interplay between energetics and configurational entropy can now be utilized to study protein function. Discovering the physical and molecular aspects of protein binding underpins the understanding of all cellular functions.
Protein recognition and binding, which result in either transient or long-lived complexes, play a fundamental role in many biological functions, but sometimes also result in pathologic aggregates. Using simplified simulation models, we survey a range of systems where two highly flexible protein chains form a homodimer. Owing to the minimal frustration principle, we find that, as in the case of protein folding, the native topology is the major factor that governs the choice of binding mechanism. In all cases, the model that corresponds to a perfectly funneled energy landscape for folding and binding, reproduces the macroscopic experimental observations on whether folding and binding are coupled in one step or whether intermediates occur. Even when the monomer is stable on its own, binding sometimes occurs fastest through unfolded intermediates thus showing the speedup envisioned in the fly-casting scenario for molecular recognition.
We focus on understanding mechanisms of protein association and the degree of protein plasticity involved in these reactions. Quantifying the capacity of a protein to bind to other specific proteins is also crucial to understand the networks of protein interaction. Deciphering the key steps in protein self-assembly has practical applications for designing medications. Instead of targeting a single molecule in the cell, more effective pharmaceuticals would eradicate a pathogen’s complete network, obstructing harmful assemblies of proteins that are the cause of many neurodegenerative diseases such as Creuzfeld-Jacob and Alzheimer.