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Tuesday, February 12, 2019 at 4:00pm
ABSTRACT: The rapid aging of the global human population is leading to a startling rise in noncommunicable diseases that are becoming more severe and burdensome for communities who can least afford treatments for these diseases. To dramatically improve the prevention and treatment of noncommunicable diseases, smart biomaterials must be developed at a low cost for drug delivery vehicles with specific targeting mechanisms, environmentally sensitive implants for tissue engineering, or dynamic health monitoring. Multiscale computational design of protein-based biomaterials can address this problem by rationally tailoring the biomaterials’ physical and chemical properties to achieve multifarious stimuli-responses. Three key bio-inspirations can be utilized for designing stimuli-responsive biomaterials: strong and lightweight silk from silkworms, structurally mutable elastin from the human skin, and reflectin and crystallin in squid’s chromatophores that help produce dynamic coloration. Multiscale molecular dynamics simulations, in combination with advanced sampling methods, can effectively and rapidly capture the structural transitions in silk and silk-elastin proteins that are subjected to solvent processing or high temperatures. Crosslinking silk-elastin proteins at high concentrations inhibits de-swelling by constraining their ability to remodel their structure. Homology modeling coupled with molecular docking simulations and the analysis of electrostatic properties unveil the importance of site-specific localization of reflectin and crystallin in the chromatophores of squid’s skin. Crystallin forms granules that serve as protective repositories for the pigment molecules for robust pigmentary coloration while reflectin confers iridescence, and this combination of mechanisms give squids their complex and adaptive coloration. These three bio-inspirations provide crucial design principles to guide the way towards truly rational computational design of multi-stimuli responsive biomaterials.
BIOGRAPHICAL SKETCH: Jingjie Yeo is a research scientist in Singapore’s Institute of High Performance Computing, A*STAR. He has extensive experience in multiscale computational modelling of biological or bio-inspired materials and processes to characterize and predict the structure-function relationships of natural and synthetic proteins, graphene, and complex fluid mixtures. He is prolifically collaborative and interdisciplinary in both basic and applied research, leading to 30 peer-reviewed publications with numerous collaborators in multiple countries, 20 conference presentations, 3 book chapters, and an h-index of 10. He is a co-PI in a USD$900K project funded by A*STAR to develop silk-based cosmeceuticals with novel biochemical properties. Yeo is a member of the Early Career Editorial Advisory Board for the journal, ACS Biomaterials Science & Engineering, and he serves on the editorial boards of two other journals, IJCMSE and method. He is also on the scientific advisory committees of several international conferences, including the annual International Conference on Computational Methods. Yeo is a co-instructor in the nonprofit education institution, Station1, and the mentor of two Ph.D. students in Nanyang Technological University (NTU). Prior, he was an A*STAR-funded Postdoctoral Fellow at the Massachusetts Institute of Technology (MIT), Department of Civil and Environmental Engineering, as well as a postdoctoral scholar at Tufts University in the Department of Biomedical Engineering. Yeo received his B.Eng. in 2010 from NTU, majoring in Aerospace Engineering with a minor in Business. He received his Ph.D. in 2014 from the School of Mechanical and Aerospace Engineering, NTU, after obtaining the A*STAR Graduate Scholarship. His Ph.D. research focused on the Modeling and Simulation of the Thermal and Mechanical Properties of Ultralight Materials.