Recognition of a Tandem Lesion by DNA Glycosylases Explored Combining Molecular Dynamics and Machine Learning

Abstract

The combination of several closely spaced DNA lesions, which can be induced by a single radical hit, constitutes a hallmark in the DNA damage landscape and radiation chemistry. The occurrence of such tandem base lesions give rise to a strong coupling with the double helix degrees of freedom and induce important structural deformations, in contrast to DNA strands containing a single oxidized nucleobase. Although such complex lesions are known to be refractory to repair by DNA glycosylases, there is still a lack of structural evidence to rationalize these phenomena. In this contribution, we explore, by numerical modeling and molecular simulations, the behavior of the bacterial glycosylase responsible for base excision repair (MutM), specialized in excising oxidatively-damaged defects such as 7,8-dihydro-8-oxoguanine (8-oxoG). The difference in lesion recognition between a simple damage and a tandem lesions featuring an additional abasic site is assessed at atomistic resolution owing to microsecond molecular dynamics simulation and machine learning postprocessing, allowing to extensively pinpoint crucial differences in the interaction patterns of the damaged bases. This work advocates for the use of such high throughput numerical simulations for exploring the complex combinatorial chemistry of tandem DNA lesions repair and more generally multiple damaged sites of the utmost significance in radiation chemistry.