Protein-display systems, such as phage-display, and approaches like saturation mutagenesis have demonstrated the power of simultaneously examining: stability; binding affinity; and the impact of site-specific mutations on protein properties. Unfortunately, traditional approaches to computer aided molecular design are often computationally intractable when attempting to address the accessible space of these techniques. Often, they are unable to prospectively inform chemistry at the bench due to the sheer size of the available mutation space and the time necessary to complete calculations. Furthermore, many methods choose to reduce the complexity by examining single point structures for what are ostensibly dynamic systems. Leveraging the power of MOE deployed in a cloud environment, we present a protocol able to produce predictive models in under an hour. This MOE-based methodology coupled with the power of the cloud allows modeling to be a prospective exercise, informing and influencing projects from the outset.

Protein mutagenesis and property optimization with MOE

255th National Meeting (2018)

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