# Accurate and efficient density functional theory calculations of intermolecular interactions and conformational energies

> **NIH NIH R44** · Q-CHEM, INC. · 2020 · $416,792

## Abstract

Abstract
Biophysical properties can be computer-modeled using quantum mechanics (QM). While vastly more
computationally costly than molecular mechanics (MM), QM methods are essential for bond-breaking
and/or high accuracy. Indeed, QM methods have advanced with exciting, (and ongoing) improvements in
the accuracy of density functional theory (DFT). These DFT improvements could open new applications
opportunities reliable conformational searching, molecular recognition, ligand binding, enzymology
modeling, and all the areas where QM simulations can aid biophysical chemistry. However, the latest
density functionals require very large and computationally demanding basis sets to attain their high
accuracy. Use of smaller basis sets leads to unconverged results with often unacceptable errors in relative
energies, so only small systems can be treated at present with high accuracy DFT calculations.
 This proposal addresses the unmet need to reduce the computational cost of achieving large basis
set accuracy in DFT calculations. Its first innovation is the use of minimal adaptive basis functions
(MAB) for this purpose. The MAB is a small (minimal) set of functions, adaptively formed in situ from a
traditional large basis via an atom-blocked, sparse transformation. The DFT calculation is performed in
the MAB, followed by a single-shot perturbative correction. MAB accuracy has been shown to be
virtually indistinguishable from a conventional large basis calculation on biophysically relevant examples,
while analysis suggests the potential for more than an order-of-magnitude speedup. A second innovation
to further extend the size of MAB-DFT calculations is a new MAB-based QM-in-QM method that exactly
embeds a smaller active QM region described by a large basis into a larger QM environment that is pre-
optimized in a smaller basis set. Large QM regions have been argued to be essential in QM/MM.
 The Phase II research has three principal objectives that together will bring the MAB-DFT method
up to the level of application-ready software. First, the software implementation of the MAB-DFT method
will be optimized to remove current bottlenecks, and to take full advantage of the block-sparse structure
of the MAB in order to achieve the speedups the method is capable of yielding. This requires careful
consideration of matrix element evaluation, numerical quadrature and linear algebra across all five steps
in a MAB-DFT calculation. Second, the proposed MAB-based QM-in-QM embedding model will be
implemented, using all optimizations from the first aim, as well as exact replacement of the environment
by an effective core potential-like term. Third, timings and accuracy tests of both stand-alone MAB-DFT
and QM-in-QM MAB-DFT calculations will be conducted and reported for a range of biophysically
relevant energy differences in both model and realistic systems. Additionally, some model applications
drawn from areas such drug design, enzymology and DNA/RNA chemistry will be ...

## Key facts

- **NIH application ID:** 9988434
- **Project number:** 5R44GM121126-03
- **Recipient organization:** Q-CHEM, INC.
- **Principal Investigator:** Evgeny Epifanovsky
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $416,792
- **Award type:** 5
- **Project period:** 2017-09-19 → 2022-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9988434

## Citation

> US National Institutes of Health, RePORTER application 9988434, Accurate and efficient density functional theory calculations of intermolecular interactions and conformational energies (5R44GM121126-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9988434. Licensed CC0.

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