Abstract
The relationship between protein structure and information complexity is fundamental to both the origins of life and modern cellular processes. Evidence shows that many biomolecules exist in multiple conformational states rather than a single, rigid structure. In particular, biomolecular condensates formed via liquid-liquid phase separation create concentrated microenvironments that contain a conformational ensemble of intrinsically disordered peptides. The dense liquid phases have conformationally limited states that can be templated to create ordered nuclei which assemble into higher-order supramolecular structures. This two-phase nucleation mechanism underpins normal physiological processes, such as collagen fibrillogenesis, and pathological processes like amyloid aggregation in neurodegenerative diseases. The first project builds a curated database using sequence-based bioinformatics tools—ANuPP and mebipred—to train a Hidden Markov model that traces the evolutionary history of metal-binding amyloid sequences. These metal–amyloid co-assemblies not only can exhibit enzymatic functionality, but also reveal pathways for the evolution of complex chemical systems marked by compartmentalization, metabolism, and information transfer. The second project investigates a minimal NPG-CHO peptide network that was engineered to mimic collagen properties. Collagen, a key structural protein in the dynamic physical and chemical network of the extracellular matrix, is essential for cellular integrity and migration. Through molecular modeling and molecular dynamics simulations, this study examines atomistic interactions that underpin triple helical formation and explores strategies to incorporate specific functional motifs into the synthetic collagen framework.
Table of Contents
This table of contents is under embargo until 22 May 2027
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