De novo self-assembling collagen heterotrimers using explicit positive and negative design

Area of Science:

• Biochemistry
• Computational Biology
• Protein Engineering

Background:

• Collagen is abundant and vital in biological processes, yet fibrous proteins are underrepresented in computational design.
• Collagens consist of three polypeptide chains forming triple helices.

Purpose of the Study:

• To computationally design model collagen peptides that specifically associate as heterotrimers.
• To explore the application of computational design to fibrous proteins like collagen.

Main Methods:

• Developed a discrete computational model for designing heterotrimer-forming collagen-like peptides.
• Employed a combined positive and negative design approach targeting stability and specificity.
• Optimized sequences of 30-residue peptides (A, B, C) for ABC heterotrimer formation, disfavoring other oligomers.
• Synthesized peptides and characterized them using circular dichroism and NMR.

Main Results:

• A unique A:B:C heterotrimer species was not successfully formed.
• Negative design showed partial success, with competing A + B and B + C mixtures observed.
• Analysis provided insights into the roles of electrostatics and secondary-structure propensities in collagen stability.

Conclusions:

• Computational design of specific collagen heterotrimers remains challenging.
• Experimental validation revealed limitations in achieving precise heterotrimer assembly.
• Findings offer crucial insights for refining future computational designs of collagenous structures.