title: Geometric Patterns for Neighboring Bases Near the Stacked State in Nucleic Acid Strands.
abstract: Structural variation in base stacking has been analyzed frequently in isolated double helical contexts for nucleic acids, but not as often in nonhelical geometries or in complex biomolecular environments. In this study, conformations of two neighboring bases near their stacked state in any environment are comprehensively characterized for single-strand dinucleotide (SSD) nucleic acid crystal structure conformations. An ensemble clustering method is used to identify a reduced set of representative stacking geometries based on pairwise distances between select atoms in consecutive bases, with multiple separable conformational clusters obtained for categories divided by nucleic acid type (DNA/RNA), SSD sequence, stacking face orientation, and the presence or absence of a protein environment. For both DNA and RNA, SSD conformations are observed that are either close to the A-form, or close to the B-form, or intermediate between the two forms, or further away from either form, illustrating the local structural heterogeneity near the stacked state. Among this large variety of distinct conformations, several common stacking patterns are observed between DNA and RNA, and between nucleic acids in isolation or in complex with proteins, suggesting that these might be stable stacking orientations. Noncanonical face/face orientations of the two bases are also observed for neighboring bases in the same strand, but their frequency is much lower, with multiple SSD sequences across categories showing no occurrences of such unusual stacked conformations. The resulting reduced set of stacking geometries is directly useful for stacking-energy comparisons between empirical force fields, prediction of plausible localized variations in single-strand structures near their canonical states, and identification of analogous stacking patterns in newly solved nucleic acid containing structures.
authors.affiliation: Department of Biomedical Sciences, School of Public Health, State University of New York at Albany , Albany, New York 12222, United States.
authors.forename: Ada
authors.identifier: 0000-0002-8233-3057
authors.initials: A
authors.lastname: Sedova
authors.affiliation: Laboratory of Computational and Structural Biology, Division of Genetics, Wadsworth Center, New York State Department of Health, CMS 2008, Biggs Laboratory, Empire State Plaza, P.O. Box 509, Albany, New York 12201-0509, United States.|Department of Biomedical Sciences, School of Public Health, State University of New York at Albany , Albany, New York 12222, United States.
authors.forename: Nilesh K
authors.identifier: 0000-0003-2206-7049
authors.initials: NK
authors.lastname: Banavali
mesh_terms: D020029:Base Pairing; D018360:Crystallography, X-Ray; D004247:DNA / Q000737:chemistry*; D008958:Models, Molecular; D009690:Nucleic Acid Conformation; D009711:Nucleotides / Q000737:chemistry*; D011506:Proteins / Q000737:chemistry*; D012313:RNA / Q000737:chemistry*; D013816:Thermodynamics
chemical_list: D009711:Nucleotides; D011506:Proteins; D012313:RNA; D004247:DNA