Systematically Improvable and Locality Accelerated Enzymatic Reactivity Modeling: Toward Chemical Accuracy at Affordable Cost

Quantum mechanics/molecular
mechanics (QM/MM) is the
cornerstone
of computational enzymology. Herein, we address an outstanding challenge
in QM/MM, namely, simultaneous access to accurate QM methodology and
a large QM subsystem at an affordable computational cost. First, local
natural orbital (LNO)-based CCSD(T) is employed for chemically accurate
energetics and as a reference for choosing density functional theory
(DFT) models. Next, reliable hybrid DFT methods are selected, with
large QM subsystem selections suitable also for reaction barriers.
Then, quantum embedding, especially accelerated via our recent local
embedded subsystem (LESS) approach, is used to reduce the cost of
DFT calculations to a few core hours, even with large QM sizes up
to ca. 400 QM atoms. By combining these advanced methods, we propose
a Locality Accelerated (by LESS and LNO) and Systematically Improvable
(LASI) scheme for QM/MM simulations. It benefits from the strengths
of a converged QM size in its DFT component, affordability for many
configurations via quantum embedding, and, if needed, CCSD(T) accuracy
for energetics. The protocol is validated through the study of challenging,
representative, and clinically relevant enzyme-catalyzed phosphate
hydrolysis. Based on these results, we establish generally applicable
guidelines to set up the components of the LASI protocol. The flexibility
and affordability of LASI, both in large-scale QM and QM/MM contexts,
make it broadly applicable for the predictive computational description
of enzyme reactivity and beyond.