Structure-templated predictions of novel protein interactions from sequence information

PLoS Comput Biol. 2007 Sep;3(9):1783-9. doi: 10.1371/journal.pcbi.0030182.

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 types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Amino Acid Sequence
  • Binding Sites
  • Computer Simulation
  • Conserved Sequence
  • Feasibility Studies
  • Models, Chemical*
  • Models, Molecular
  • Molecular Sequence Data
  • Protein Binding
  • Protein Interaction Mapping / methods*
  • Protein Structure, Tertiary
  • Sequence Alignment / methods*
  • Sequence Analysis, Protein / methods*
  • Structure-Activity Relationship