Structure-templated predictions of novel protein interactions from sequence information Academic Article uri icon

Overview

MeSH Major

  • Algorithms
  • Models, Chemical
  • Protein Interaction Mapping
  • Sequence Alignment
  • Sequence Analysis, Protein

abstract

  • The multitude of functions performed in the cell are largely controlled by a set of carefully orchestrated protein interactions often facilitated by specific binding of conserved domains in the interacting proteins. Interacting domains commonly exhibit distinct binding specificity to short and conserved recognition peptides called binding profiles. Although many conserved domains are known in nature, only a few have well-characterized binding profiles. Here, we describe a novel predictive method known as domain-motif interactions from structural topology (D-MIST) for elucidating the binding profiles of interacting domains. A set of domains and their corresponding binding profiles were derived from extant protein structures and protein interaction data and then used to predict novel protein interactions in yeast. A number of the predicted interactions were verified experimentally, including new interactions of the mitotic exit network, RNA polymerases, nucleotide metabolism enzymes, and the chaperone complex. These results demonstrate that new protein interactions can be predicted exclusively from sequence information.

publication date

  • September 2007

Research

keywords

  • Academic Article

Identity

Language

  • eng

PubMed Central ID

  • PMC1988853

Digital Object Identifier (DOI)

  • 10.1371/journal.pcbi.0030182

PubMed ID

  • 17892321

Additional Document Info

start page

  • 1783

end page

  • 9

volume

  • 3

number

  • 9