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Updated: Dec 8, 2025

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
Published on: January 26, 2024
Rosetta-Enabled Structural Prediction of Permissive Loop Insertion Sites in Proteins
Joseph G Plaks1, Jeff A Brewer1, Nicole K Jacobsen1
1Department of Chemical and Biological Engineering, University of Colorado, Boulder, Boulder, Colorado 80309, United States.
Abstract:
While loop motifs frequently play a major role in protein function, our understanding of how to rationally engineer proteins with novel loop domains remains limited. In the absence of rational approaches, the incorporation of loop domains often destabilizes proteins, thereby requiring massive screening and selection to identify sites that can accommodate loop insertion. We developed a computational strategy for rapidly scanning the entire structure of a scaffold protein to determine the impact of loop insertion at all possible amino acid positions. This approach is based on the Rosetta kinematic loop modeling protocol and was demonstrated by identifying sites in lipase that were permissive to insertion of the LAP peptide. Interestingly, the identification of permissive sites was dependent on the contribution of the residues in the near-loop environment on the Rosetta score and did not correlate with conventional structural features (e.g., B-factors). As evidence of this, several insertion sites (e.g., following residues 17, 47-49, and 108), which were predicted and confirmed to be permissive, interrupted helices, while others (e.g., following residues 43, 67, 116, 119, and 121), which are situated in loop regions, were nonpermissive. This approach was further shown to be predictive for β-glucosidase and human phosphatase and tensin homologue (PTEN), and to facilitate the engineering of insertion sites through in silico mutagenesis. By enabling the design of loop-containing protein libraries with high probabilities of soluble expression, this approach has broad implications in many areas of protein engineering, including antibody design, improving enzyme activity, and protein modification.
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