Despite force field improvements over the past decades, we still encounter situations where simulation results disagree with experiments due to force field inaccuracies. Such situations provide opportunities to improve force fields. In this study, we introduce a novel framework for optimizing force fields using experimental data. The unique feature of this framework is that it aims to optimize force fields to match experiments while minimizing the perturbation made to the original force field. To achieve this, we combine ensemble reweighting techniques with the potential contrasting method. Ensemble reweighting is used to reweight an ensemble of conformations generated using an existing force field to match experimental data while minimizing the perturbation to the original ensemble. Potential contrasting is then utilized to optimize force field parameters to reproduce the reweighted ensemble. We demonstrate the framework's effectiveness by optimizing a coarse-grained force field for intrinsically disordered proteins using experimental radius of gyration data.
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http://dx.doi.org/10.1021/acs.jpcb.4c02147 | DOI Listing |
Adv Sci (Weinh)
January 2025
Department of Chemistry, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.
Machine learning interatomic potentials (MLIPs) promise quantum-level accuracy at classical force field speeds, but their performance hinges on the quality and diversity of training data. An efficient and fully automated approach to sample chemical reaction space without relying on human intuition, addressing a critical gap in MLIP development is presented. The method combines the speed of tight-binding calculations with selective high-level refinement, generating diverse datasets that capture both equilibrium and reactive regions of potential energy surfaces.
View Article and Find Full Text PDFJ Phys Chem Lett
January 2025
Departament de Farmàcia i Tecnologia Farmacèutica, i Fisicoquímica, Facultat de Farmàcia i Ciències de l'Alimentació, Universitat de Barcelona (UB), 08028 Barcelona, Spain.
Incorporation of environment and vibronic effects in simulations of optical spectra and excited state dynamics is commonly done by combining molecular dynamics with excited state calculations, which allows to estimate the spectral density describing the frequency-dependent system-bath coupling strength. The need for efficient sampling, however, usually leads to the adoption of classical force fields despite well-known inaccuracies due to the mismatch with the excited state method. Here, we present a multiscale strategy that overcomes this limitation by combining EMLE simulations based on electrostatically embedded ML potentials with the QM/MMPol polarizable embedding model to compute the excited states and spectral density of 3-methyl-indole, the chromophoric moiety of tryptophan that mediates a variety of important biological functions, in the gas phase, in water solution, and in the human serum albumin protein.
View Article and Find Full Text PDFNano Lett
January 2025
Jiangxi Provincial Key Laboratory of Green Hydrogen and Advanced Catalysis, College of Physics, Communication and Electronics, Jiangxi Normal University, 99 Ziyang Avenue, Nanchang 330022, Jiangxi, China.
studies of the relationship between surface spin configurations and spin-related electrocatalytic reactions are crucial for understanding how magnetic catalysts enhance oxygen evolution reaction (OER) performance under magnetic fields. In this work, 2D FeSe nanosheets with rich surface spin configurations are synthesized via chemical vapor deposition. magnetic force microscopy and Raman spectroscopy reveal that a 200 mT magnetic field eliminates spin-disordered domain walls, forming a spin-ordered single-domain structure, which lowers the OER energy barrier, as confirmed by theoretical calculations.
View Article and Find Full Text PDFJ Mol Model
January 2025
School of Chemical and Environmental Engineering, China University of Mining and Technology-Beijing, Haidian District, Ding No.11 Xueyuan Road, Beijing, 100083, People's Republic of China.
Context: Understanding the structural characteristics of coal at the molecular level is fundamental for its effective utilization. To explore the molecular structure characteristic, the long-flame coal from Daliuta (DLT), coking coal from Yaoqiao (YQ), and anthracite from Taixi (TX) were investigated using various techniques such as elemental analysis, Fourier transform infrared spectroscopy, solid-state C nuclear magnetic resonance spectroscopy, and X-ray photoelectron spectroscopy. Based on the structural parameters, the coal molecular model was constructed and optimized.
View Article and Find Full Text PDFJ Mol Model
January 2025
College of Electronics and Information, Xi'an Polytechnic University, Xian, People's Republic of China.
Context: The two-dimensional graphene/MoTe heterostructure holds extensive potential applications in optoelectronic devices, sensors, and catalysts. To expand its optical applications, this study systematically investigates the adsorption stability of metal atoms (Au, Pt, Pd, and Fe) on the graphene/MoTe and their influence on its optoelectronic properties employing first-principles methods. The findings indicate that after the adsorption of Au and Pd, the structure retains its direct bandgap properties, while the adsorption of Pt and Fe exhibits indirect bandgap characteristics.
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