Energy Landscaping - On the Relationship between Functionality and Sequence Mutations for Multifunctional Biomolecules

Abstract

The process of protein and RNA folding has been understood in general terms through the principle of minimal frustration, and is usually thought of as being guided by a folding funnel on the energy landscape, which is based around the native structure. However, more recently, various biomolecules have been associated with multifunnel energy landscapes, where each funnel exhibits a distinct structural ensemble and function.

This work explores how the principle of minimal frustration may be extended to multifunnel energy landscapes that are associated with multifunctional biomolecules. To achieve this aim, the computational potential energy landscape framework is employed to analyse four example systems. Additionally, this study analyses mutants for all four systems, where the mutations are chosen to change properties of the systems without destabilising the native sequence ensemble entirely.

The first system considered is a two-state coiled-coil. It is shown how mutations fundamentally change the energy landscape from the minimal frustrated organisation necessary to fulfil biological function. These changes can introduce alternative pathways for folding, as well as new structural ensembles.

Similar effects are observed for ubiquitin. In addition, the landscape exploration allows us to calculate a number of experimentally determined properties for this protein, which exhibit excellent agreement, and we characterise folding at an atomistic level of detail.

Next we consider the hormones oxytocin and vasopressin, which are themselves mutants of each other, along with a number of other mutants for both molecules. Again, the frustration in the landscape increases due to mutations, and a greater variety in the resulting structural ensembles is observed, leading to changes in binding affinities.

Finally, the HP1 loop of RNA 7SK is analysed, revealing that the principles established for the energy landscapes of proteins extend to nucleic acids.

Overall, the results indicate that sequences have evolved to exhibit the minimum number of funnels on the energy landscape to support multiple functions, extending the principle of minimal frustration to multifunnel energy landscapes.