Predicting recombinant protein expression experiments using molecular dynamics simulation

Abstract

<p>Soluble expression of de novo-designed proteins in <i>Escherichia coli</i> (<i>E. coli</i>) remains empirical. For given experimental conditions expression success is determined in part by protein primary sequence. This has been previously explored with varying success using a variety of statistical solubility prediction tools though without taking fold stability into account. In the present study, the three-dimensional structure of proteins in molecular dynamics (MD) simulations is used to predict expression as a new approach with a set of four-helix bundles. Stability-related parameters for ten structures were determined in a thermal unfolding MD simulation and used to build statistical models with a support vector machine (SVM) classifier. The most accurate models were identified by their performance on five independent four-helix bundle sequences. The final model provided accurate classification prediction for this test set and was successfully applied in a model challenge with two newly designed sequences.</p>