Structure-based deep learning for binding site detection in nucleic acid macromolecules.

ABSTRACT: Structure-based drug design (SBDD) targeting nucleic acid macromolecules, particularly RNA, is a gaining momentum research direction that already resulted in several FDA-approved compounds. Similar to proteins, one of the critical components in SBDD for RNA is the correct identification of the binding sites for putative drug candidates. RNAs share a common structural organization that, together with the dynamic nature of these molecules, makes it challenging to recognize binding sites for small molecules. Moreover, there is a need for structure-based approaches, as sequence information only does not consider conformation plasticity of nucleic acid macromolecules. Deep learning holds a great promise to resolve binding site detection problem, but requires a large amount of structural data, w

SUBMITTER: Kozlovskii I 

PROVIDER: S-EPMC8633674 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature