A post-doctoral researcher from the Advanced Science Research Center of the CUNY Graduate Center, (CUNY ASRC), has made an important step towards understanding how complex mixtures o biomolecular building blocks can form self-organized patterns.
The discovery was detailed in a paper published in the journal ChemAnkit Jain (CUNY ASRC Nanoscience Initiative director Rein Ulijn) authored the paper. This new knowledge could be critical for designing novel materials and technologies that have similar abilities and attributes..
Jain said that all life forms start with the exact same set of building blocks. These include the 20 amino acids that make proteins. Understanding how these molecules interact and form self-organizing patterns would improve our understanding of biology’s ability to create functionality. This knowledge could lead to new technologies and materials that incorporate life processes like adapting, growing, healing, and developing new properties as needed.
Jain applied a novel, synthetic approach in order to understand how complex biomolecule combinations interact with one another and adapt to changes in the environment. Instead of trying to deconstruct molecular organization within existing systems, such those found in biological cells or other biomolecules, Jain created mixtures that can react and interact in a test tube. Jain tracked the formation of complex patterns by biomolecules in response to environmental changes and observed them evolve.
Ulijn stated that complex mixtures of interacting molecules are essential to life processes. However, they are not often studied in chemistry labs because they are messy, complicated, and difficult to understand and study. “Systematically designing and tracking the behavior of mixtures allows us to make fundamental observations on how molecules combine to form functional collectives. We were able detail how these chemical systems absorb changes from external conditions to form specific patterns. Also, we discovered that systems with multiple variables show stochastic behavior. Thus, while overall pattern formation appears similar when running multiple experiments simultaneously, the exact details of two independent experiments may be different.”
Jain began his experiment by mixing a few selected dipeptides. These are simple protein-like compounds made of two amino acids. These dipeptides were chosen based on their ability interact and aggregate. They also contained a catalyst that allowed the dipeptides dynamically recombine to form peptides with more complex interaction patterns. The paper’s most complex system was composed of 15 dipeptides which can reversibly assemble to form 225 unique tripeptides. Jain was then able to track the formation and break down of peptides from different sequences within the mixtures. He noticed that their interactions were strongly influenced by the environment.
Understanding how biological functions relevant for life emerge is crucial to understanding molecular selforganization. This can be done by identifying hierarchical patterns in both covalent as non-covalent interactions. Researchers can now use the new bottom-up approach to understand ensemble characteristics and provide molecular resolution. This work shows that simple molecules can spontaneously select for sequences, which could provide insight into the chemical origins and function of biological cells. Designing adaptive systems based upon multi-component mixtures will likely lead to the discovery of patterns that dictate the formation reconfigurable, functional materials. This could be useful for future bioinspired technology.
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