Bayesian multiple protein structure alignment

Published

Journal Article

Multiple protein structure alignment is an important tool in computational biology, with numerous algorithms published in the past two decades. However, recently literature highlights a growing recognition of the inconsistencies among alignments from different algorithms, and the instability of alignments obtained by individual algorithms under small fluctuations of the input structures. Here we present a probabilistic model-based approach to the problem of multiple structure alignment, using an explicit statistical model. The resulting algorithm produces a Bayesian posterior distribution over alignments which accounts for alignment uncertainty arising from evolutionary variability, experimental noise, and thermal fluctuation, as well as sensitivity to alignment algorithm parameters. We demonstrate the robustness of this approach on alignments identified previously in the literature as "difficult" for existing algorithms. We also show the potential for significant stabilization of tree reconstruction in structural phylogenetics. © 2014 Springer International Publishing Switzerland.

Full Text

Duke Authors

Cited Authors

  • Wang, R; Schmidler, SC

Published Date

  • January 1, 2014

Published In

Volume / Issue

  • 8394 LNBI /

Start / End Page

  • 326 - 339

Electronic International Standard Serial Number (EISSN)

  • 1611-3349

International Standard Serial Number (ISSN)

  • 0302-9743

Digital Object Identifier (DOI)

  • 10.1007/978-3-319-05269-4-27

Citation Source

  • Scopus