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Protein-protein Interfaces02:04

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Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
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Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
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Deploying synthetic coevolution and machine learning to engineer protein-protein interactions.

Aerin Yang1, Kevin M Jude1,2, Ben Lai3

  • 1Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305, USA.

Science (New York, N.Y.)
|July 27, 2023
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Summary
This summary is machine-generated.

Scientists developed a synthetic coevolution platform to engineer protein-protein interactions. This method generates diverse interacting protein pairs for applications in biotechnology and synthetic biology.

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Area of Science:

  • Biochemistry
  • Molecular Biology
  • Synthetic Biology

Background:

  • Natural protein-protein interactions evolve over time.
  • Recreating this coevolution in a lab setting is challenging.
  • Understanding molecular recognition is key for protein engineering.

Purpose of the Study:

  • To develop a synthetic platform for protein-protein coevolution.
  • To analyze molecular recognition in engineered protein pairs.
  • To expand protein interface diversity using computational methods.

Main Methods:

  • Created a synthetic protein-protein coevolution platform.
  • Isolated matched interacting mutein pairs from large libraries.
  • Performed systems-level analysis of molecular recognition.
  • Utilized pretrained protein language models for in silico expansion.

Main Results:

  • Successfully isolated diverse coevolved Z domain-affibody pairs.
  • Characterized a wide range of interaction properties (affinity, cross-reactivity, orthogonality).
  • Captured extensive coevolutionary networks.
  • Predicted remodeled protein interfaces computationally.

Conclusions:

  • The synthetic coevolution platform enables the study and engineering of protein interactions.
  • This approach generates protein complexes with tunable molecular recognition properties.
  • Integration of experimental and computational methods accelerates protein design for biotechnology.