Predicting the effects of microbial engineering in KBase
Engineering living cells to optimize unnatural functions, such as producing biofuel, often results in trial-and-error processes to identify and manipulate genes. To improve and expedite this process, a user-friendly computational pipeline was developed by scientists at Pacific Northwest National Laboratory (PNNL) and is now available within KBase.
New tools for dynamic modeling
Data scientist Neeraj Kumar led a team at PNNL that developed a thermodynamic computational modeling pipeline, coined CompMol_Thermo. This workflow automatically processes data from the biochemistry and modeling database, ModelSEED, created by a team of KBase scientists from Argonne National Laboratory led by Sam Seaver. The biochemical data goes through NWChem, a quantum-chemistry-based software developed at Environmental Molecular Sciences Laboratory, which predicts the thermodynamics of a given biochemical reaction in the database. Finally, NWChem connects back to the ModelSEED database to store results and further optimize predictions. All of these quantum-chemistry computations require significant compute power to run. Shane Cannon, a KBase scientist at Berkeley National Laboratory, stepped up to help provide the needed compute power from the National Energy Research Scientific Computing Center.
KBase Developer Spotlight
Sam Seaver – ModelSEED
Using CompMol_Thermo in KBase
The entire workflow is available as a user-friendly and free tool within KBase. Step-by-step information on how to use the CompMol_Thermo workflow is available in a tutorial Narrative, accessible with a free KBase login. The tutorial demonstrates how to set up parameters for running the NWChem Computational Chemistry Calculations Thermodynamics App, including how to add reaction data to your Narrative, running the App, and how to read the data output. This capability complements and enables the structural biology, metabolic modeling, and cheminformatics workflows already available on the KBase platform.
Rajendra P. Joshi, Andrew McNaughton, Dennis G. Thomas, Christopher S. Henry, Shane R. Canon, Lee Ann McCue, and Neeraj Kumar. Quantum Mechanical Methods Predict Accurate Thermodynamics of Biochemical Reactions. ACS Omega 2021 6(14), 9948-9959. DOI: 10.1021/acsomega.1c00997
PNNL, Accelerating Microbial Engineering with Thermodynamic Calculations (Sarah Wong)