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.