CGeNArate: a sequence-dependent coarse-grained model of DNA for accurate atomistic MD simulations of kb-long duplexes

TitleCGeNArate: a sequence-dependent coarse-grained model of DNA for accurate atomistic MD simulations of kb-long duplexes
Publication TypeJournal Article
Year of Publication2024
AuthorsFarré-Gil, David, Arcon Juan Pablo, Laughton Charles A., and Orozco Modesto
JournalNucleic Acids Research
Volume52
Issue12
Pagination6791 - 6801
Date Published05/2024
ISBN Number0305-1048
Abstract

We present CGeNArate, a new model for molecular dynamics simulations of very long segments of B-DNA in the context of biotechnological or chromatin studies. The developed method uses a coarse-grained Hamiltonian with trajectories that are back-mapped to the atomistic resolution level with extreme accuracy by means of Machine Learning Approaches. The method is sequence-dependent and reproduces very well not only local, but also global physical properties of DNA. The efficiency of the method allows us to recover with a reduced computational effort high-quality atomic-resolution ensembles of segments containing many kilobases of DNA, entering into the gene range or even the entire DNA of certain cellular organelles.

URLhttps://doi.org/10.1093/nar/gkae444
Short TitleNucleic Acids Research
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