Recognition of a tandem lesion by DNA bacterial formamidopyrimidine glycosylases explored combining molecular dynamics and machine learning

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