Ligand‐Induced Electronic Response Enables Predictive QM/MM Simulations

Predictive modeling of large molecular systems demands methods that combine quantum accuracy with scalability. Although hybrid quantum mechanics/molecular mechanics (QM/MM) simulations offer such a framework, their predictive power has been limited by the subjective and system-specific definition of the QM region. Here, we present an electronically informed protocol that objectively defines QM regions from ligand-induced orbital shifts and charge-redistribution, extracted in a single semiempirical fragment molecular orbital (FMO) calculation. Validated on both zeolite-guest and enzyme-inhibitor complexes, the method achieves chemical accuracy (within ∼1-2 kcal/mol on binding energies) while substantially reducing computational cost at the DFTB level. This cross-domain strategy reframes QM/MM as a transferable design principle, bridging solid-state catalysis and quantum biochemistry, and thereby providing a practical platform for predictive molecular engineering across diverse disciplines.

Authors

Institutions

Publication Details

Journal
Advanced Science
Published
2025-12-22
DOI
https://doi.org/10.1002/advs.202519137
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Ligand‐Induced Electronic Response Enables Predictive QM/MM Simulations

Nahoko Kuroki, Hiroyuki Mori, Nichika Ozawa
Advanced Science
Machine Learning in Materials Science
article

Ligand‐Induced Electronic Response Enables Predictive QM/MM Simulations

Nahoko Kuroki, Hiroyuki Mori, Nichika Ozawa
article en

Abstract

Predictive modeling of large molecular systems demands methods that combine quantum accuracy with scalability. Although hybrid quantum mechanics/molecular mechanics (QM/MM) simulations offer such a framework, their predictive power has been limited by the subjective and system-specific definition of the QM region. Here, we present an electronically informed protocol that objectively defines QM regions from ligand-induced orbital shifts and charge-redistribution, extracted in a single semiempirical fragment molecular orbital (FMO) calculation. Validated on both zeolite-guest and enzyme-inhibitor complexes, the method achieves chemical accuracy (within ∼1-2 kcal/mol on binding energies) while substantially reducing computational cost at the DFTB level. This cross-domain strategy reframes QM/MM as a transferable design principle, bridging solid-state catalysis and quantum biochemistry, and thereby providing a practical platform for predictive molecular engineering across diverse disciplines.

Advanced ScienceVol. 13(17)
Ochanomizu University (JP), Chuo University (JP)
Japan Society for the Promotion of Science, National Institutes of Natural Sciences
Openalex Percentile: Top 48%
Machine Learning in Materials Science
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.