ArticleThe journal of physical chemistry letters2025
Improved Description of Environment and Vibronic Effects with Electrostatically Embedded ML Potentials.
Article in The journal of physical chemistry letters, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Enabling Biomolecular Simulations with Neural Network Potentials in GROMACS.Journal of chemical theory and computation · 2026Article
- Simulating enzyme catalysis with electrostatically embedded machine learning potentials.Chemical science · 2026Article
- Multiscale Machine Learning Prediction of Infrared Spectra of Solvated Molecules.Journal of chemical theory and computation · 2026Article
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Authors and funding
2 authors.
Funding
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Abstract
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. Our protocol provides highly accurate results that faithfully reproduce their
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