During pretreatment, acid, water, and heat work to remove non-cellulosic biomass from plant material. Lignin, however, sticks around, clustering into aggregates around the cellulose and impeding enzymes from reaching cellulose.
To accurately model this crowded environment, Smith's team used experimental data to create a representative sample of pretreated biomass and enzymes. The model took into account details such as the ratio of cellulose to lignin, type of lignin, and relative amount of enzymes. In total, the simulation tracked nine cellulose fibers, 468 lignin molecules, and 54 enzyme molecules in a rectangular water box.
The team built the model using a molecular dynamics code called GROMACS under an allocation awarded through the Innovative and Novel Computational Impact on Theory and Experiment, or INCITE, program. With a complete model, the team turned to the Cray XK7 Titan, America's fastest supercomputer, to supply the necessary computing power to observe the system in action.
During its largest runs, the biomass simulation scaled to nearly 4,000 of Titan's 18,666 nodes, producing roughly 45 nanoseconds of simulation time in one day. Over the course of a year, the team amassed 1.3 microseconds of simulation time, a significant length of time in the world of computational biophysics.
"There's nowhere else in the world where we could have run this simulation," Petridis said.
In addition to lending insight to the challenges of next-generation biofuels, the team's simulation pointed toward potential pathways that could help mitigate lignin's impact. Specifically, the simulation demonstrated that lignin does not bind as much to less-ordered, or amorphous, cellulose fibers, meaning it competes less with the enzymes there.
"Industrialists knew amorphous cellulose is more easily broken down by enzymes, but what we show is that it's not only the inherent properties of amorphous cellulose that makes it easier for the enzymes but also that lignin is less of a pest," Petridis said.