Dynamic Multiscale Graph Analysis Reveals Structural Signatures of Peptide Aggregate Stability and Splitting

Abstract: Understanding the structure, dynamics, and stability of peptide aggregates formed during self-assembly is crucial for designing functional biomaterials. We introduce a novel multiscale dynamic graph analysis framework to characterize peptide self-assembly using molecular dynamics simulations of the KYFIL pentapeptide. Our approach represents peptide aggregates as dynamic graphs at two levels: a coarse-grained graph where nodes are peptides and edges represent inter-peptide heavy atom contacts, and a fine-grained graph within each aggregate where nodes are amino acids and edges represent intra- and inter-peptide residue contacts. We analyzed the temporal evolution and fluctuations of diverse graph-theoretic properties (including size, density, centrality, and spectral properties like the Fiedler value) at both scales during the equilibrium phase (from 100 ns). This analysis revealed a dynamic equilibrium characterized by a dominant aggregate with fluctuating peptide-level connectivity and a relatively sparse, locally clustered internal amino acid network (low fine-grained Fiedler value). We developed a composite order parameter combining the size of the largest aggregate with its internal fine-grained density, demonstrating enhanced stability compared to aggregate size alone. Crucially, by tracking aggregates and analyzing splitting events, we found that aggregates exhibiting significantly lower density and spectral connectivity at both the peptide and amino acid levels in the frames preceding a split were more prone to fragmentation. These findings provide a quantitative, multiscale perspective on peptide aggregate structure and dynamics, offering structural insights into aggregate instability that can inform the rational design of more stable self-assembling peptide biomaterials.

Subjects:	q-bio.BM; physics.chem-ph
Cite as:	PX:2508.00028