Jul 2026· Journal of Chemical Theory and Computation· 0 citations· 63 references
Medicine
TL;DR
This work presents a hybrid fragmentation-based approach, FragQMMM, that enables efficient and accurate force evaluation for large molecular systems, and successfully reproduces the hydrogen-bond network and preserving the underlying structure-activity relationship.
Abstract
Accurate evaluation of interatomic forces and interaction energies in large molecular systems, such as protein-ligand complexes or polymer-molecule assemblies, is essential for a wide range of applications in drug discovery and materials science. However, achieving a balance between computational efficiency and accuracy remains a major challenge: classical force fields offer high speed but limited precision, while quantum mechanical (QM) methods provide greater accuracy at the cost of poor scalability. In this work, we present a hybrid fragmentation-based approach, FragQMMM, that enables efficient and accurate force evaluation for large molecular systems. Specifically, crucial intermolecular interactions are treated at the semiempirical QM level (GFN2-xTB), while intramolecular forces are described using molecular mechanics (MM). This selective treatment greatly accelerates geometry optimization while preserving the essential interaction features. When applied to protein-ligand complexes, the method delivers a speed-up of roughly 10-100× compared to full QM calculations. The resulting geometries match the reference QM structures more closely than those obtained with pure MM, successfully reproducing the hydrogen-bond network and preserving the underlying structure-activity relationship.
A fast pipeline based on the OPLS-AA force field is presented that enables the automated calculation of non-bonding intermolecular (dimer) interaction energies derived from a set of small organic (monomer) molecules. To calculate the non-bonding contributions, optimized geometries of the monomer molecules as well as th...
Mirco Daniel, Hannah Kullik, Martin Urban et al.· Journal of Cheminformatics· 0 citations
The results demonstrated that the use of quantum algorithms can enhance the binding energy correlation value, offering potential applications in the workflow of computer-aided drug design.
Hironobu Kitajima, Carlos Bistafa, Takao Kobayashi et al.· Journal of Chemical Informat...· 0 citations
Key QM applications-torsional profiles, spectra prediction, reactivity analysis, and modeling of non-covalent interactions-highlighting their impact and limitations are reviewed, illustrating the trade-off between speed and accuracy.
C. Tautermann, M. Degroote, Benjamin Ries· Methods in molecular biology· 0 citations
We have compared the performance of 64 different computational methods, based on combined quantum mechanical (QM) and molecular mechanical (QM/MM) or QM-cluster calculations in a continuum solvent, to estimate the acid constant (pK a) of metal-bound ligands in proteins. As a calibration set, we use 12 experimental pK a...
Maryam Haji Dehabadi, Mehdi Irani, S. Jafari et al.· Journal of Chemical Theory a...· 0 citations
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