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 their OPLS-AA van der Waals and atomic partial charge parameters are required. The key advantage of the new pipeline lies in its fast, highly parallelized in-memory computations without slow I/O operations, which make it possible to thoroughly process comparatively large numbers of (more than a hundred) monomer molecules within acceptable time frames (hours and days): Compared to an analogous, more versatile, and comprehensive approach, the new computational scheme delivers comparable results while being more than two orders of magnitude faster. For locally estimating the required OPLS-AA force field parameters with the LigParGen and BOSS software packages, a user-friendly graphical user interface for the Windows operating system is provided.
Scientific contribution
Rapid calculation of mutual intermolecular energies for a set of monomer molecules based on the widely used OPLS-AA force field enables a considerable expansion of this type of calculation for practical purposes. The performance improvement can be used to achieve significant improvements of interaction energy averages as well as considerable expansions in the size of the monomer molecule set.
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 values from six different proteins that involve Zn2+, Fe3+, or Fe4+. We employ two different density functional theory (DFT) methods (TPSS and B3LYP), two basis sets (def2-SV(P) and def2-TZVPD), QM regions of three different sizes (∼40, ∼100, and ∼350 atoms), relaxed or fixed surroundings, and three different values of the dielectric constant of the continuum-solvation model (ε = 4, 20, or 80). The results clearly show that QM-cluster+continuum-solvation is much better than QM/MM. In general, the most accurate results are obtained with ε = 80 and the minimal QM region. The two DFT methods, the two basis sets, and relaxing or fixing the surroundings give similar results. The best-performing method is TPSS with the minimal QM region, def2-TZVPD, relaxed surroundings, and ε = 80, yielding a mean absolute deviation (after removal of a systematic error of 11.6 pK a units, pu) of 2.0 pu and a maximum deviation of 5.0 pu. The coefficient of determination (R 2) and Kendall’s τ with respect to the experimental pK a values are both 0.64, while Spearman’s rank correlation coefficient is 0.78. This level of accuracy should be sufficient to reliably determine the protonation states of metal-bound ligands in QM-based studies of enzymatic reaction mechanisms.
Maryam Haji Dehabadi, Mehdi Irani, S. Jafari et al.· Journal of Chemical Theory a...· 0 citations