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Updated: May 29, 2026

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow
Published on: October 17, 2025
Design of native-like proteins through an exposure-dependent environment potential
Samuel DeLuca1, Brent Dorr, Jens Meiler
1Departments of Chemistry, Pharmacology, and Biomedical Informatics, Center for Structural Biology, Institute for Chemical Biology, Vanderbilt University, Nashville, Tennessee 37212, United States.
Abstract:
We hypothesize that the degree of surface exposure of amino acid side chains within a globular, soluble protein has been optimized in evolution, not only to minimize the solvation free energy of the monomeric protein but also to prevent protein aggregation. This effect needs to be taken into account when engineering proteins de novo. We test this hypothesis through addition of a knowledge-based, exposure-dependent energy term to the RosettaDesign solvation potential [Lazaridis, T., and Karplus, M. (1999) Proteins 35, 133-152]. Correlation between amino acid type and surface exposure is determined from a representative set of experimental protein structures. The amino acid solvent accessible surface area (SASA) is estimated with a neighbor vector measure that increases in accuracy compared to the neighbor count measure while remaining pairwise decomposable [Durham, E., et al. (2009) J. Mol. Model. 15, 1093-1108]. Benchmarking of this potential in protein design displays a 3.2% improvement in the overall sequence recovery and an 8.5% improvement in recovery of amino acid types tolerated in evolution.
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