Candan Tamerler1
University of Kansas1
Synthetic biology takes the bio-based and bio-enabled approaches to a step further to enable engineering biology in designing and producing materials and processes with previously unattainable functions. Nature has been a source of inspiration in engineering solutions for many. As our understanding of biological materials and structures expanded, mimicking biological systems for innovative engineering solutions has continued with growing intensity. Our group was among the early adapters of biomimetic principles for harnessing design strategies to develop innovative materials. Mimicking the molecular recognition in biological interactions, we have been exploring the smaller protein domains, i.e., peptides as the key fundamental building blocks. Peptides offer to design hybrid biomaterials that can mimic the functions of proteins, generate biomimetic platforms and modulate microenvironment. Using synthetic biology approaches, we expanded the use of peptide-based building blocks as bioactive modules and design bio-hybrid materials with diverse functions addressing medical and industrial applications. We incorporated machine learning (ML) methods to capture distinct peptide functionalities as elements of critical modular building blocks. We adapted experimental and computational approaches demonstrated transparent ML frameworks for identifying relevant peptide structure features for targeted functions. For antimicrobial hybrid materials, we provided a method for selecting secondary structure features in related to antimicrobial peptides and expanded our predictions to design peptides for metals in biology as biocatalysts, metalation tools, and metal chelates in manufacturing and nutritional immunity. Using synthetic modular domains, we developed peptide-metal and peptide-polymer hybrids as integral of biomaterials and developed models for allosteric-dependent effects of selecting spacers to recover domain function activity. We generated knowledge-potential folded structures to discover rough set theory trends which showed to be relevant for recovering bioactivity. Our examples will include utilization of the biological activity imparted by each biomolecule toward prevention of dental and oral diseases as well as restoration of oral health. Engineered modular peptide and enzyme systems will be also provided as synthetic biohybrid material systems applicable to industrial applications. Enabling synthetic biological modular approach guided by ML algorithms offers a fascinating path to reshape our thinking in engineering and represent the functional frontiers to mimic biological systems.