The Emergence of Novel Versus Known Three-Dimensional Structures from Random Sequences.

Area of Science:

• * Computational biology and bioinformatics
• * Molecular evolution and protein design

Background:

• * Random protein sequences are generally unlikely to fold into stable, functional structures.
• * The hypothesis suggests repeated sequences may overcome this limitation, impacting protein evolution.

Purpose of the Study:

• * To investigate the foldability of protein sequences composed of repeating random segments.
• * To explore the structural diversity and stability of these predicted protein folds.
• * To validate computational predictions with experimental methods.

Main Methods:

• * Employed protein structure prediction algorithms to analyze 120-residue sequences with varying lengths of random repeats (5-60 residues).
• * Investigated the impact of insertions and deletions (INDELs) on predicted protein structures.
• * Utilized circular dichroism (CD) spectroscopy and X-ray crystallography for experimental validation of novel structures.

Main Results:

• * Sequences with repeats <30 residues showed high folding confidence (1-12%).
• * Observed common folds like β-solenoids and helical bundles, including novel α-helical screw structures.
• * Experimental validation confirmed the stability and structure of a novel super-secondary structure.

Conclusions:

• * Protein structure prediction tools can identify folds outside their training data distribution.
• * Repeated sequences significantly increase the likelihood of protein folding compared to random sequences.
• * Findings support the theory of protein evolution through the repetition and assortment of short peptide sequences and have implications for protein design.