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Machine Learning-Enhanced Coarse-Grained Modelling of Telomeric G-Quadruplex Multimers: A Multiscale Study

CORDIS · observation · Publication date unknown

Machine Learning-Enhanced Coarse-Grained Modelling of Telomeric G-Quadruplex Multimers: A Multiscale Study MCG-QUAD is an integrative study of G-quadruplex (G4) multimers—noncanonical DNA structures—providing a framework to interpret experimental data and connect a microscopic view to macroscopic observables through a novel multiscale in silico approach. G4s are ubiquitous in the genomes of higher eukaryotes and are believed to play key roles in various biological processes. The presence of G4s in the telomeric region has been shown to inhibit telomerase, opening the possibility for G4-stabilizing compounds to be used as anticancer medications. Sequences that form G4s exhibit long folding timescales. G4s are highly polymorphic structures with long-living quasi-stable topologies, a complexity further compounded in multimers. Structural information on G4 multimers is limited, and existing

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award

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SIGNED

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EU

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209483.28

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EUR