Study of alternating DNA GC sequences by different time-resolved spectroscopies has provided fundamental information on the interaction between UV light and DNA, a process of great biological importance. Multiple decay paths have been identified, but their interplay is still poorly understood. Here, we characterize the photophysics of GC-DNA by integrating different computational approaches, to study molecular models including up to 6 bases described at a full quantum mechanical level. Quantum dynamical simulations, exploiting a nonadiabatic linear vibronic coupling (LVC) model, coupled with molecular dynamics sampling of the initial structures of a (GC) DNA duplex, provide new insights into the photophysics in the sub-picosecond time-regime. They indicate a substantial population transfer, within 50 fs, from the spectroscopic states towards G → C charge transfer states involving two stacked bases (CT), thus explaining the ultrafast disappearance of fluorescence. This picture is consistent with that provided by quantum mechanical geometry optimizations, using time dependent-density functional theory and a polarizable continuum model, which we use to parametrize the LVC model and to map the main excited state deactivation pathways. For the first time, the infrared and excited state absorption signatures of the various states along these pathways are comprehensively mapped. The computational models suggest that the main deactivation pathways, which, according to experiment, lead to ground state recovery on the 10-50 ps time scale, involve CT followed by interstrand proton transfer from the neutral G to C. Our calculations indicate that CT is populated to a larger extent and more rapidly in GC than in CG steps and suggest the likely involvement of monomer-like and interstrand charge transfer decay routes for isolated and less stacked CG steps. These findings underscore the importance of the DNA sequence and thermal fluctuations for the dynamics. They will also aid the interpretation of experimental results on other sequences.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11206432PMC
http://dx.doi.org/10.1039/d4sc00910jDOI Listing

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