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Award details
- Awarding agency
- Department of Health and Human Services
- Branch
- National Institutes of Health
- Recipient company
- Q-CHEM INC
- Proposal award date
- 2020-04-07
- Contract end date
- 2022-03-31
- UEI
- MXPESVR9KFE7
- Solicitation number
- PA19-272
- Topic code
- 400
Research abstract
PROJECT SUMMARY
Next Generation Methods for Advanced Condensed Phase Simulations in Q-ChemBiophysical systems exist in the condensed phase, and that is the environment in which their
properties should be computer-modeled. The correct theory to describe the electrons is using ab
initio (AI) quantum mechanics (QM), whilst nuclear motion requires molecular dynamics (MD). The
combination, AIMD, is thus the appropriate tool for biophysical simulations. While use of AIMD
is vastly more expensive than MD with empirical potentials, it is nonetheless the standard to aspire
to. AIMD enables correct treatment of bond-breaking for reactive processes, as well an accurate
description of the non-bonded interactions that determine solvation and conformational preferences.This Phase II proposal has the objective of bringing a production level AIMD code to the Q-Chem
software package. The key justification for the proposed work, and the potential value of the resulting
product is that it will bring together capabilities that are not found jointly in any other AIMD code.
The valuable synergy between the density functional theory implementation for periodic boundary
conditions (DFT-PBC), and advanced algorithms for efficiently and accurate propagating the MD is
the core innovation of this project.With regard to DFT-PBC (the first specific aim), the focus is on implementing high precision, high
efficiency algorithms for the critical components of DFT with advanced functionals. Our code will
support the latest meta-generalized gradient approximations (mGGAs), with inclusion of non-local
van der Waals density functionals, that are not available in DFT-PBC codes to date. We will addition-
ally provide support for range-separated exact exchange, with high efficiency. These capabilities will
come with energies and gradients. Our software framework can also permit all-electron calculations
as needed e.g. for NMR properties that depend on the electron density at the nucleus. Our modular
code will support efficient on-node parallelism.To propagate MD efficiently and stably (the second specific aim), we employ two innovative statis-
tical mechanics (SM) algorithms that have been proven in conventional MD, but are not yet available
in any production AIMD code. First, we are extending the inertial extended Lagrangian self-consistent
field (iEL/SCF) method to work robustly and efficiently with AIMD, building upon promising Phase
I results, by combining it with a stochastic-isokinetic integration (SII) scheme to enable a single but
larger MD time step. Second, we will explore the combination of iEL/SCF-SII with a multiple time-
stepping method in which will explore whether different components of the QM force can be updated
on different timescales in the AIMD.In final Aim 3 we test the combined DFT-PBC and iEL/SCF-SII capabilities on biophysical appli-
cations including zwitterionic glycine and valine peptides in aqueous solution and molecular crystals.
1PROJECT NARRATIVE
Next Generation Methods for Advanced Condensed Phase Simulations in Q-ChemThis project will provide improved computer-based quantum mechanical modeling of biophysical
problems in the condensed phase, by synergistic combination of periodic boundary conditions with
advanced molecular dynamics methods. The resulting capability will be valuable for applications
such as the role of solution on conformational energies, on binding and reactions at active centers,
and for validating more approximate simulation methods.
1
Technology keywords
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Other awards by this recipient
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Research funding history
48 SBIR/STTR records share this UEI (1993–2023). Reported award amounts total $20,068,274. Reported amounts are not federal obligations.
Phases: Phase I, Phase II
Agencies: Department of Health and Human Services, Department of Energy, Department of Defense, National Science Foundation
Agency intelligence
Department of Health and Human Services
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