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Updated: Jan 20, 2026

Dissecting Mechanoenzymatic Properties of Processive Myosins with Ultrafast Force-Clamp Spectroscopy
Published on: July 1, 2021
Ultrafast nonadiabatic dynamics probed by nitrogen K-edge absorption spectroscopy
T Northey1, J Norell2, A E A Fouda3
1Chemistry-School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK. tom.penfold@ncl.ac.uk.
Abstract:
The emergence of X-ray free electron lasers (X-FELs) has made it possible to probe structural dynamics on the femtosecond timescale. This extension of experimental capabilities also calls for a simultaneous development in theory to help interpret the underlying structure and dynamics encoded within the experimental observable. In the ultrafast regime this often requires a time-dependent theoretical treatment that describes nuclear dynamics beyond the Born-Oppenheimer approximation. In this work, we perform quantum dynamics simulations based upon time-evolving Gaussian basis functions (GBFs) and simulate the ultrafast X-ray Absorption Near-Edge Structure (XANES) spectra of photoexcited pyrazine including two strongly coupled electronically excited states and four normal mode degrees of freedom. Two methods to simulate the excited state XANES spectra are applied, the first is based upon the multi-configurational second order perturbation theory restricted active space (RASPT2) method and the second uses a combination of the maximum overlap method (MOM) and time-dependent density functional theory (TDDFT). We demonstrate that despite the simplicity of the MOM/TDDFT method, it captures several qualitative features of the RASPT2 simulations at much reduced computational effort. However, features such as the conical intersection are a particular exception as they require a multi-configurational treatment. For the nuclear dynamics, we demonstrate that even a small number of GBFs can provide reasonable description of the spectroscopic observable. This work provides perspectives for computationally efficient approaches important for addressing larger systems.
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