https://www.scienceopen.com/hosted-document?doi=10.15212/bioi-2025-0071
Announcing a new article publication for
BIO Integration journal. Extended tight-binding (xTB) methods offer a computationally efficient alternative to classical force fields and ab initio quantum methods in modeling molecular systems. In the context of end-point free energy calculations, integrating xTB with implicit solvation models provides a promising route for enhanced accuracy. However, systematic benchmarking of xTB-based protocols remains limited, particularly in diverse host-guest systems.
We investigated the integration of xTB Hamiltonians (GFN0, GFN1, and GFN2) with post-simulation implicit-solvent models [Poisson−Boltzmann (PB), generalized Born (GB), and the most recent CPCM-X] for end-point free energy calculations. A total of over 250 host-guest complexes were used, covering cucurbiturils, octa acids, and pillararenes. Both single-trajectory and three-trajectory sampling protocols were applied. Entropic contributions were estimated via MM-based normal mode analysis and xTB-based statistical approximations. We evaluated predictive performance using Kendall τ, Pearson r, and predictive index.
The three-trajectory protocol consistently outperformed the single-trajectory counterpart across Hamiltonians and solvent models. Among all configurations, the GFN2-xTB/PB combination showed the best predictive accuracy, although it fell short of the top-performing MM/GBOBCSA ΔG method. Notably, in challenging systems like sulfur-substituted pillararenes, xTB methods exhibited superior performance, whereas MM/GBSA failed due to inadequate error cancellation. The use of CPCM-X did not further enhance accuracy, possibly due to unsuccessful error cancellation.
While MM/GBSA remains the most robust protocol for general use, the GFN2-xTB/PB ΔH method emerges as a viable alternative for cases where MM-based methods perform poorly. These findings highlight the value of xTB-based multiscale approaches for receptor-ligand binding, especially in complex or chemically diverse systems.
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ISSN 2712-0074
eISSN 2712-0082
Xiaohui Wang, Sai Li and Zuoyuan Zhang et al. Multiscale End-point Screening with Extended Tight-binding Hamiltonians.
BIOI. 2025. Vol. 6(1). DOI: 10.15212/bioi-2025-0071
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