Molecular dynamics simulations for the ranking, evaluation, and refinement of computationally designed proteins.

Abstract

Computational methods have been developed to redesign proteins so that they can perform novel functions such as the catalysis of nonnatural reactions. Active sites are constructed from the inside out by stochastically exploring mutations that favor the binding of transition states, small molecule binders, and protein surfaces-depending on the task at hand. The approach allows the use of many proteins for engineering scaffolds upon which to erect the necessary functionality. Beyond being of practical value for producing proteins with new applications, the approach tests our understanding of protein chemistry. The current success rate, however, is rather modest, and so the designers have become good only at making catalysts with low catalytic efficiencies. Directed evolution can be used to enhance function and stability, while more advanced computational techniques and physics-based simulations are useful at elucidating structural flaws and at guiding the design process. Here, we summarize work that focuses on the dynamic properties of computationally designed enzymes and their directed evolution variants. We utilized in silico methods to address three questions: (1) What are the shortcomings of these designs? (2) Can they be improved? (3) Can we screen out designs that are likely to be inactive?