Accelerating Whole-Cell mRNA Translation Simulations Using Dedicated FPGA Hardware (ACS Synthetic Biology, November 2021)

Intracellular biophysical simulations are essential for predicting how genetic modifications affect cellular resources. However, modeling the competition between thousands of mRNAs and ribosomes is computationally intensive and often creates synchronization bottlenecks that traditional parallel computing (CPUs and GPUs) cannot easily solve.

We developed a novel hardware-accelerated approach using Field-Programmable Gate Arrays (FPGAs) to simulate the mRNA translation process. By designing custom logic to manage ribosomal traffic and global resource allocation, we achieved simulation speeds orders of magnitude faster than equivalent software solutions.

Key Highlights:

• Breakthrough Performance: Our parallel hardware model runs up to 4,683 times faster than software, enabling simulations that would normally take months to be completed in hours.

• Biophysical Accuracy: The model accounts for codon-specific translation times, initiation rates, ribosomal footprints (traffic jams), and diffusion delays.

• Validated Predictive Power: Simulation results showed high correlations (r = 0.63-0.7) with experimental protein abundance measurements in E. coli and S. cerevisiae.

• Synthetic Biology Application: We successfully utilized the hardware to run complex optimization algorithms (Forward/Backward Gene Minimization) to reduce ribosomal traffic jams, a task that is otherwise computationally prohibitive.

This dedicated hardware approach provides a scalable foundation for whole-cell modeling, allowing researchers to navigate the vast design space of synthetic biology with unprecedented speed.

Read More:

https://pubs.acs.org/doi/10.1021/acssynbio.1c00415