Optimal design of thermally stable proteins

Motivation: For many biotechnological purposes, it is desirable to redesign proteins to be more structurally and functionally stable at higher temperatures. For example, chemical reactions are intrinsically faster at higher temperatures, so using enzymes that are stable at higher temperatures would lead to more efficient industrial processes. We describe an innovative and computationally efficient method called Improved Configurational Entropy (ICE), which can be used to redesign a protein to be more thermally stable (i.e. stable at high temperatures). This can be accomplished by systematically modifying the amino acid sequence via local structural entropy (LSE) minimization. The minimization problem is modeled as a shortest path problem in an acyclic graph with nonnegative weights and is solved efficiently using Dijkstra's method

Bioinformatic method for protein thermal stabilization by structural entropy optimization

Engineering proteins for higher thermal stability is an important and difficult challenge. We describe a bioinformatic method incorporating sequence alignments to redesign proteins to be more stable through optimization of local structural entropy. Using this method, improved configurational entropy (ICE), we were able to design more stable variants of a mesophilic adenylate kinase with only the sequence information of one psychrophilic homologue. The redesigned proteins display considerable increases in their thermal stabilities while still retaining catalytic activity. ICE does not require a three-dimensional structure or a large number of homologous sequences, indicating a broad applicability of this method. Our results also highlight the importance of entropy in the stability of protein structures