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Protein-protein Interfaces

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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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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

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Achievements and Challenges in Computational Protein Design.

Ilan Samish^1,2

¹Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot, Israel. ilan.samish@weizmann.ac.il.

Methods in Molecular Biology (Clifton, N.J.)

|December 4, 2016

Summary

Computational protein design (CPD) engineers proteins de novo for specific functions. This review details 101 examples, highlighting achievements and challenges in this evolving field.

Keywords:

Computational protein design De novo design Directed evolution Enzyme design Inverse folding problem Negative design Protein–protein interaction Rational design Synthetic biology

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Area of Science:

Structural bioinformatics
Computational biophysics
Protein engineering

Background:

Computational protein design (CPD) is an evolving field focused on computer-aided engineering of proteins.
Designs are guided by desired structure, function, or environmental conditions.
This chapter provides a historical overview of CPD through 101 examples.

Observation:

The field integrates knowledge-based and energy-based methods.
Hierarchical approaches consider local, regional, and global motifs with varying resolution schemes.
Key aspects include hot-spot residue identification, shape complementarity, electrostatics, solvation, dynamics, and negative design.

Findings:

CPD combines diverse methodologies, including differential approaches and experimental integration.
Objective cross-assessment and ranking of designs are crucial for success.
The review emphasizes achievements and pending challenges in CPD.

Implications:

CPD enhances understanding of protein structure-function relationships.
Future challenges include software dissemination and in vivo validation.
Applications span biologics, food science, nanotechnology, and green chemistry.