Dataset Information

Characterization of Biomolecular Helices and Their Complementarity Using Geometric Analysis.

ABSTRACT: A general method is presented to characterize the helical properties of potentially irregular helices, such as those found in protein secondary and tertiary structures and nucleic acids. The method was validated using artificial helices with varying numbers of points, points per helical turn, pitch, and radius. The sensitivity of the method was validated by applying increasing amounts of random perturbation to the coordinates of these helices; 399?360 helices in total were evaluated. In addition, the helical parameters of protein secondary structure elements and nucleic acid helices were analyzed. Generally, at least seven points were required to recapitulate the parameters of a helix using our method. The method can also be used to calculate the helical parameters of nucleic acid-binding proteins, like TALE, enabling direct analysis of their helix complementarity to sequence-dependent DNA distortions.

SUBMITTER: Hauser K

PROVIDER: S-EPMC5453303 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Characterization of Biomolecular Helices and Their Complementarity Using Geometric Analysis.

Hauser Kevin K He Yiqing Y Garcia-Diaz Miguel M Simmerling Carlos C Coutsias Evangelos E

Journal of chemical information and modeling 20170406 4

A general method is presented to characterize the helical properties of potentially irregular helices, such as those found in protein secondary and tertiary structures and nucleic acids. The method was validated using artificial helices with varying numbers of points, points per helical turn, pitch, and radius. The sensitivity of the method was validated by applying increasing amounts of random perturbation to the coordinates of these helices; 399 360 helices in total were evaluated. In addition ...[more]

PMID: 28287728

Similar Datasets

Project description:BackgroundUnderstanding interactions between mutations and how they affect fitness is a central problem in evolutionary biology that bears on such fundamental issues as the structure of fitness landscapes and the evolution of sex. To date, analyses of fitness landscapes have focused either on the overall directional curvature of the fitness landscape or on the distribution of pairwise interactions. In this paper, we propose and employ a new mathematical approach that allows a more complete description of multi-way interactions and provides new insights into the structure of fitness landscapes.ResultsWe apply the mathematical theory of gene interactions developed by Beerenwinkel et al. to a fitness landscape for Escherichia coli obtained by Elena and Lenski. The genotypes were constructed by introducing nine mutations into a wild-type strain and constructing a restricted set of 27 double mutants. Despite the absence of mutants higher than second order, our analysis of this genotypic space points to previously unappreciated gene interactions, in addition to the standard pairwise epistasis. Our analysis confirms Elena and Lenski's inference that the fitness landscape is complex, so that an overall measure of curvature obscures a diversity of interaction types. We also demonstrate that some mutations contribute disproportionately to this complexity. In particular, some mutations are systematically better than others at mixing with other mutations. We also find a strong correlation between epistasis and the average fitness loss caused by deleterious mutations. In particular, the epistatic deviations from multiplicative expectations tend toward more positive values in the context of more deleterious mutations, emphasizing that pairwise epistasis is a local property of the fitness landscape. Finally, we determine the geometry of the fitness landscape, which reflects many of these biologically interesting features.ConclusionA full description of complex fitness landscapes requires more information than the average curvature or the distribution of independent pairwise interactions. We have proposed a mathematical approach that, in principle, allows a complete description and, in practice, can suggest new insights into the structure of real fitness landscapes. Our analysis emphasizes the value of non-independent genotypes for these inferences.

Dataset Information

Characterization of Biomolecular Helices and Their Complementarity Using Geometric Analysis.

Publications

Characterization of Biomolecular Helices and Their Complementarity Using Geometric Analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets