Accurate positioning of functional residues with robotics-inspired computational protein design

Proc Natl Acad Sci U S A. 2022 Mar 15;119(11):e2115480119. doi: 10.1073/pnas.2115480119. Epub 2022 Mar 7.

Abstract

SignificanceComputational protein design promises to advance applications in medicine and biotechnology by creating proteins with many new and useful functions. However, new functions require the design of specific and often irregular atom-level geometries, which remains a major challenge. Here, we develop computational methods that design and predict local protein geometries with greater accuracy than existing methods. Then, as a proof of concept, we leverage these methods to design new protein conformations in the enzyme ketosteroid isomerase that change the protein's preference for a key functional residue. Our computational methods are openly accessible and can be applied to the design of other intricate geometries customized for new user-defined protein functions.

Keywords: Rosetta; computational protein design; design of function; structure prediction.

MeSH terms

  • Algorithms
  • Amino Acids / chemistry*
  • Computational Biology / methods
  • Computer-Aided Design*
  • Isomerases / chemistry
  • Models, Molecular
  • Protein Conformation
  • Protein Engineering / methods*
  • Proteins / chemistry*
  • Proteins / genetics
  • Reproducibility of Results
  • Robotics*
  • Structure-Activity Relationship

Substances

  • Amino Acids
  • Proteins
  • Isomerases