Q-Chem is a state-of-the-art commercial computational quantum chemistry program that has aided about 60,000 users in their modeling of molecular processes in a wide range of disciplines, including biology, chemistry, and materials science. In this proposal, we seek to significantly reduce the computational time (now around 500,000 CPU hours) required to obtain accurate free energy profiles of enzymatic reactions. Specifically, we propose to use a multiple time step (MTS) simulation method, where a low-level (and less accurate) quantum chemistry method is used to propagate the system (i.e. move all atoms) at each time step (usually 0.5 or 1 fs), and then a high-level (i.e. more accurate and expensive) quantum chemistry method is used to correct the force on the atoms at longer time intervals. In this way, the simulation can be performed at the high-level energy surface in a fraction of time, compared with simulations performed only using the high-level quantum chemical method. In the Phase I proposal, our goal is to allow the high-level force update only once every 40?50 fs by identifying appropriate lower-level theories (Aim 1) and incorporating machine-learning techniques (Aim 2). This will accelerate accurate free energy simulations by 20?25 fold, reducing the overall computer time to around 25,000 CPU hours. Thus, our new MTS simulation method will make it feasible to routinely perform computational studies on enzymatic reaction mechanism. The addition of these new tools will also further strengthen Q-Chem's position as a global leader in the molecular modeling software market, making our program the most efficient and reliable computational quantum chemistry package for simulating large, complex chemical/biological systems.

Public Health Relevance

In this project, we seek to significantly reduce the computational time (ca. 500,000 CPU hours) required to obtain accurate free energy profiles of enzymatic reactions to ca. 25,000 CPU Hours. Building upon sophisticated quantum mechanics, this can lead to reliable and quick predictions of enzyme activities.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Small Business Innovation Research Grants (SBIR) - Phase I (R43)
Project #
1R43GM133270-01
Application #
9778517
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Lyster, Peter
Project Start
2019-04-01
Project End
2020-03-31
Budget Start
2019-04-01
Budget End
2020-03-31
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Q-Chem, Inc.
Department
Type
DUNS #
837635556
City
Pleasanton
State
CA
Country
United States
Zip Code
94588