Physical Biomodeling and Foldable, Coarse-Grained Physical Model of Polypeptide Chain
Sunday, 15 February 2015: 8:30 AM-11:30 AM
Room 230C (San Jose Convention Center)
is a new area of exploration at the interface of computer science and the biological systems. While tremendous advances have been made in computational biology, the cutting-edge 3D printing provides unprecedented opportunities for a third angle into the landscape, thus uncovering this new computational space for modeling that has remained unexplored so far. We tie together these concepts of form-specific physical-digital interfaces. With these principles, a new computational paradigm emerges for physical-digital interfaces for studying of biological phenomenon (e.g. protein folding timesteps) that focuses on shape and dynamics. We define 3 categories, and 6 processes connecting these 3 categories. These categories and processes together form the basis of the philosophy behind the field of Physical Biomodeling
. Through exploring Processes 1-6, we see that a relationship-triangle exists between the experimental data from natural systems (N), the computational models for biosystems (C), and scaled, accurate physical models of biosystems (P). Processes 1 and 2 have already existed in the literature for a long time. Physical Biomodeling
brings forth Processes 3-6 that will provide a new way to look at the old problems in biology. We arrive at a computational space at the intersection of N, C and P that has so far remained unexplored because of the difficulty in designing and fabricating accurate, scaled physical models of biosystems.
As a first step towards building computer-augmented physical polypeptide chain model that may have applications in structural biology and drug design, we have designed, fabricated and validated a dimensionally accurate, physical model of the polypeptide chain (called Peppytide), that has a flexible backbone where the dihedral bonds are rotationally constrained to match their molecular counterparts. Biological systems involve complex phenomena, and encapsulating these characteristics within a physical body is thought to be difficult. For example, representing the polypeptide chain, a generalized protein chain, along with its complex degrees-of-freedom, by a physical scaled model that will fold dimensionally-accurately, was thought to be quite difficult before the Peppytide project proved otherwise. It opens up new possibilities and challenges with guiding principles that can be extended to build other form-specific physical bio-models. Now with 3D-printing technologies, and possibilities for CAD-cum-biocomputation platforms, we are poised to explore this new domain of study.