Residue frequencies and pairing preferences at protein-protein interfaces

Fabian Glaser, David M. Steinberg, Ilya A. Vakser, Nir Ben-Tal*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


We used a nonredundant set of 621 protein-protein interfaces of known high-resolution structure to derive residue composition and residue-residue contact preferences. The residue composition at the interfaces, in entire proteins and in whole genomes correlates well, indicating the statistical strength of the data set. Differences between amino acid distributions were observed for interfaces with buried surface area of less than 1,000 Å2 versus interfaces with area of more than 5,000 Å2. Hydrophobic residues were abundant in large interfaces while polar residues were more abundant in small interfaces. The largest residue-residue preferences at the interface were recorded for interactions between pairs of large hydrophobic residues, such as Trp and Leu, and the smallest preferences for pairs of small residues, such as Gly and Ala. On average, contacts between pairs of hydrophobic and polar residues were unfavorable, and the charged residues tended to pair subject to charge complementarity, in agreement with previous reports. A bootstrap procedure, lacking from previous studies, was used for error estimation. It showed that the statistical errors in the set of pairing preferences are generally small; the average standard error is ≈0.2, i.e., about 8% of the average value of the pairwise index (2.9). However, for a few pairs (e.g., Ser-Ser and Glu-Asp) the standard error is larger in magnitude than the pairing index, which makes it impossible to tell whether contact formation is favorable or unfavorable. The results are interpreted using physicochemical factors and their implications for the energetics of complex formation and for protein docking are discussed.

Original languageEnglish
Pages (from-to)89-102
Number of pages14
JournalProteins: Structure, Function and Genetics
Issue number2
StatePublished - 1 May 2001


  • Knowledge-based potentials
  • Molecular recognition
  • Protein docking
  • Protein modeling
  • Statistical energy functions


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