Mechanism of lignin inhibition. To understand better exactly how lignin persists, researchers created one of the largest biomolecular simulations to date—a 23.7-million atom system representing pretreated biomass (cellulose and lignin) in the presence of enzymes. The size of the simulation required Titan, the flagship supercomputer at the Oak Ridge Leadership Computing Facility (OLCF), a DOE Office of Science User Facility, to track and analyze the interaction of millions of atoms.

The research, led by Jeremy Smith, director of ORNL’s Center for Molecular Biophysics and a Governor’s Chair at the University of Tennessee (UT), revealed in atomistic detail why lignin is such a problem: Not only does it bind to cellulose in the preferred locations sought by enzymes, but lignin also attracts and occupies the cellulose-binding domain of the enzymes themselves.

That impedes the mechanism the enzyme has to anchor to cellulose. Thus lignin binds exactly where it is least desired for industrial purposes. This detailed knowledge of lignin behavior can guide genetic engineering of enzymes that bind less to lignin and therefore produce bioethanol more efficiently.

—ORNL staff scientist Loukas Petridis

Beyond the scientific knowledge obtained from the simulation, the team’s biomass system advances computational biophysics’ shift toward complex, multicomponent systems, a move enabled by leadership-class supercomputers.

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.

Researchers used experimental data to create a 23.7-million atom biomass model featuring cellulose (purple), lignin (brown), and enzymes (green). (Image credit: Mike Matheson, ORNL) Click to enlarge.

To model this crowded environment accurately, 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.

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.

—Loukas Petridis

To maximize their time on the OLCF’s flagship supercomputer, Smith’s team tweaked GROMACS to streamline communication across thousands of Titan’s CPU cores. Additionally, the team doubled the time interval GROMACS used to calculate the motion of the biomass system. By implementing a more computationally efficient method to track long-range interactions between atoms, the team was able to increase its timestep from 2 femtoseconds to 4 femtoseconds, or 4,000 trillionths of a second, without losing accuracy.

The resulting data was transferred to the OLCF’s High-Performance Storage System until it could be analyzed. Typically, analysis is carried out in serial, or one event a time, but growth in computing power and simulation size has created an analysis bottleneck—it just takes too much time.

To get around this constraint, Smith’s team worked to equip GROMACS with the capability to conduct analysis in parallel, meaning thousands of Titan’s processors could work in tandem to carry out analysis tasks. For example, running parallel analyses on 2,000 CPU cores, the researchers could obtain results 2,000 times faster than conventional methods. In collaboration with the ORNL team, Josh Vermaas, a graduate student at the University of Illinois at Urbana-Champaign, contributed significantly to this effort as a DOE Computational Science Graduate Fellow at ORNL.

The new capability not only helped the team reduce its time to solution, but it also paves the way for analyzing similar large-scale simulations in the future.

Analysis was one of the stumbling blocks for simulations at this scale. With parallel analysis, it’s now more feasible and will make leadership-class simulations easier.

—team member Roland Schulz, a UT postdoctoral researcher

As supercomputers allow for larger and more realistic systems, the ambitions of researchers and the realism of their biological systems continue to rise. Summit, the OLCF’s next leadership-class supercomputer, will offer at least five times the computing power of Titan. For Smith’s team, that means its biomass models have room to grow in complexity to further probe biofuel’s challenges.

We’re trying to reach the complexity that is found in nature and industrial conditions. Eventually, we would like to construct a simple model of a plant cell wall that we could process in silico, or via computer simulation, and see how it changes during pretreatment.

—Loukas Petridis

This research was supported by DOE’s Office of Science.

Pretreatment. Jeremy Smith and colleagues also used Titan to gain insight into the effectiveness of an experimental pretreatment developed by BESC researchers in California called Cosolvent Enhanced Lignocellulose Fractionation, or CELF.

Recent studies have shown CELF to be more than three times as effective as conventional dilute acid pretreatment in maple wood. To understand why, the team simulated lignin, a problematic molecule for biofuel production, in a two-component CELF solvent consisting of water and tetrahydrofuran (THF), an industrial chemical commonly used in polyvinyl chloride, or PVC, manufacturing and varnish. The simulation results, published in Green Chemistry, suggest that THF, which binds favorably with both water and lignin, acts as a barrier between the two, making the undesired, water-repelling lignin easier to remove.

In pure water, lignin adopts a globular conformation (left) that aggregates on cellulose and blocks enzymes. In a THF-water cosolvent, lignin adopts coil conformations (right) that are easier to remove during pretreatment. Click to enlarge.

With conventional pretreatment, the simulations showed that lignin clumps up because it wants to limit its interaction with water. It aggregates and binds to cellulose, the substance that is converted into ethanol, and poses a physical barrier for the enzymes, preventing them from reaching cellulose.

In the presence of THF, however, lignin opens into long coils, which can be more easily removed when the biomass is washed. Furthermore, our simulation showed that THF prefers to solvate close to the surface of lignin, meaning it likes to interact with the molecule. This helps explain why CELF is good for removing lignin—THF acts like a shield protecting lignin from water.

—Loukas Petridis

Smith’s team constructed its 250,000-atom model under an allocation on Titan, awarded through DOE’s Office of Advanced Scientific Computing Research (ASCR) Leadership Computing Challenge, or ALCC, program. The model, built using GROMACS, consisted of a 61-unit lignin polymer submerged in a 2.1-nanometer cube of the THF–water cosolvent.

GROMACS calculated the motion of the lignin–cosolvent system in time steps of 2 femtoseconds, or 2,000 trillionths of a second. At this timescale, researchers could comfortably obtain 40–50 nanoseconds of simulation time per day on Titan, a Cray XK7 with a peak performance of 27 petaflops (or 27 quadrillion calculations per second).

“That’s about 10 times faster than we could run otherwise,” said team member Micholas Smith, a postdoctoral researcher at the UT–ORNL Center for Molecular Biophysics.

The team ran the simulation for 200 nanoseconds, storing the resulting 18 terabytes of data in the OLCF’s High-Performance Storage System.

To see how lignin responds under slightly different conditions, the team tested the lignin–cosolvent system using three different THF–water solvent ratios and four different temperatures, mirroring conditions carried out in experiment. Results indicated that the cosolvent was just as effective in low temperatures as it was in high temperatures.

That’s important because high temperatures are an expensive part of pretreatment. Biofuel engineers could lower the pretreatment temperature and know that it would not be detrimental to CELF.

—Loukas Petridis

Although THF excludes much of the water from reaching lignin, the ORNL team found that it also traps water near lignin sites that are easily broken by acid.

One way is that it may make the sites more available for the acid to access and break the bonds. On top of that, THF may help facilitate the chemical reaction that cuts lignin loose. If we could work out the mechanism by which it breaks apart, maybe we could come up with a catalyst to help that.

—Micholas Smith

Testing such a hypothesis requires the simulation of chemical reactions and chemical bonding, a computationally demanding task that depends on a different kind of molecular dynamics code capable of accounting for the subatomic interactions of the lignin–cosolvent system.

Our current simulation confirms that THF facilitates lignin bond-breaking. In the future, we hope to take the next step and explore how that process works in greater detail.

—Micholas Smith

Future simulations of biomass, lignin, and pretreatment processes is being carried out on Titan under a 100-million core-hour allocation awarded to Jeremy Smith’s team as part of the 2016 Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program.

The research is funded by the BioEnergy Science Center, a DOE Bioenergy Research Center supported by DOE’s Office of Science.

Resources

• Josh V. Vermaas, Loukas Petridis, Xianghong Qi, Roland Schulz, Benjamin Linder, and Jeremy C. Smith (2015)“Mechanism of lignin inhibition of enzymatic biomass deconstruction.” Biotechnology for Biofuels 8, no. 1 doi: 10.1186/s13068-015-0379-8

• Micholas Dean Smith, Barmak Mostofian, Xiaolin Cheng, Loukas Petridis, Charles M. Cai, Charles E. Wyman, and Jeremy C. Smith (2016) “Cosolvent pretreatment in cellulosic biofuel production: Effect of tetrahydrofuran-water on lignin structure and dynamics.” Green Chemistry doi: 10.1039/C5GC01952D