Motif‐directed redesign of enzyme specificity

Abstract

Computational protein design relies on several approximations, including the use of fixed backbones and rotamers, to reduce protein design to a computationally tractable problem. However, allowing backbone and off-rotamer flexibility leads to more accurate designs and greater conformational diversity. Exhaustive sampling of this additional conformational space is challenging, and often impossible. Here, we report a computational method that utilizes a preselected library of native interactions to direct backbone flexibility to accommodate placement of these functional contacts. Using these native interaction modules, termed motifs, improves the likelihood that the interaction can be realized, provided that suitable backbone perturbations can be identified. Furthermore, it allows a directed search of the conformational space, reducing the sampling needed to find low energy conformations. We implemented the motif-based design algorithm in Rosetta, and tested the efficacy of this method by redesigning the substrate specificity of methionine aminopeptidase. In summary, native enzymes have evolved to catalyze a wide range of chemical reactions with extraordinary specificity. Computational enzyme design seeks to generate novel chemical activities by altering the target substrates of these existing enzymes. We have implemented a novel approach to redesign the specificity of an enzyme and demonstrated its effectiveness on a model system.

Coupling Protein Side-Chain and Backbone Flexibility Improves the Re-design of Protein-Ligand Specificity

“…Previous work on applying computational methods to design specificity has focused largely on interactions between proteins, although there are examples of applications to enzymes [ 9 – 11 ]. Computational methods to re-engineer protein–protein specificity have typically employed a “second-site suppressor” strategy, in which a mutation is made on one protein to destabilize its interaction with a binding partner, and a second compensating mutation is made on the binding partner to re-stabilize the interaction [ 12 ].…”

Optimization of rotamers prior to template minimization improves stability predictions made by computational protein design

“…Computational protein design (CPD) algorithms have been successfully applied to the prediction of protein sequences exhibiting desired properties such as increased stability, altered specificity, and novel enzymatic activity . Traditionally, CPD calculations are performed using a single‐state design (SSD) approach whereby sequences are evaluated in the context of a single fixed protein backbone template, which is typically a high‐resolution crystal structure that may be energy‐minimized to alleviate steric clashes present in the deposited coordinates.…”

Computer‐aided design of a catalyst for Edman degradation utilizing substrate‐assisted catalysis

“…These three mutations [Fig. (A)] were inspired by commonly occurring, favorable interactions involving the chemical moieties found in our small molecule model, a strategy that previously allowed us to reengineer the specificity of methionine aminopeptidase . A mutation of leucine to tyrosine at position 157 is intended to introduce a favorable “ring‐to‐edge” interaction between the tyrosine side chain and the phenyl group on the substrate .…”