Researchers show how biomolecule mixtures interact with their environment and communicate with it.

A post-doctoral researcher at the Advanced Science Research Center at CUNY Graduate Center has made an important breakthrough in understanding how complex mixtures biomolecular building blocks create self-organized patterns.

The journal published a new paper detailing the discovery. ChemAnkit Jain, a member CUNY ASRC Nanoscience Initiative Direct Rein Ulijn’s laboratory, wrote the article. It provides new knowledge about adaptive biological function, which could prove crucial in designing novel materials or technologies with similar capabilities 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 molecules interact with each other and form self-organizing patterns could help us understand how biology creates functionality. This knowledge could also lead to new ways of creating materials or technologies that incorporate life processes, such as adapting and growing, healing, and developing additional properties as required.

Jain applied a novel, synthetic approach in order to understand how complex biomolecule combinations interact and adapt to changes in the environment. He created mixtures that could interact and react, rather than trying to unravel molecular organization in the existing systems such as those found within biological cells. Jain observed how biomolecules formed spontaneously in response to changes in their environment and tracked them.

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. We also discovered that systems with many variables exhibit a stochastic behavior. This means that while the overall pattern formation may look similar when you run multiple experiments, the details of two independent experiments are quite different.”

Jain started his experiment by mixing a selection of dipeptides. These are minimalic protein-like compounds that consist of just two amino acids. These dipeptides, chosen for their ability to interact and aggregate, also contained a catalyst which allowed them to dynamically recombine and create peptides that have more complex interaction patterns. The most complex system in this paper was comprised of 15 different dipeptides that reversibly combine to create 225 unique Tetrapeptides. 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 are relevant to life is possible by understanding molecular self-organization using hierarchical patterns of covalent and noncovalent interactions. Researchers can now use the new bottom-up approach to understand ensemble characteristics and provide molecular resolution. The research shows that simple molecules show spontaneous sequence selection. This may help to understand the chemical origins for biological function. 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.