AI Article Synopsis
- The study explores how proteins can be designed to maintain stability across multiple different shapes or conformations while being thermodynamically favorable.
- It demonstrates that the ability of a protein to remember various forms is linked to the diversity of amino acids used, specifically growing with the logarithm of the number of amino acid types.
- The research also delves into how these conformations can relate to each other, suggesting a fixed limit to how much we can manipulate the protein's energy landscape, influencing factors like how "deep" or "broad" the energy wells are within its structure.
Article Abstract
We consider the design of proteins to be simultaneously thermodynamically stable in multiple independent and correlated conformations. We first show that a protein can be trained to fold to multiple independent conformations and calculate its capacity. The number of configurations that it can remember is proportional to the logarithm of the number of amino acid species A, independent of chain length. Next we investigate the recognition of correlated conformations, which we apply to funnel design around a single configuration. The maximum basin of attraction, as parametrized in our model, also depends on the number of amino acid species as ln A. We argue that the extent to which the protein energy landscape can be manipulated is fixed, effecting a trade off between well breadth, well depth, and well number. This emerging picture motivates a clearer understanding of the scope and limits of protein and heteropolymer function.
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| http://dx.doi.org/10.1103/PhysRevE.66.031902 | DOI Listing |
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