Systematic characterization of proteinâ??protein interface for the development of artificial biomachinery for metabolic engineering

Cheng-Wei Ma and An-Ping Zeng
Institute of Bioprocess and Biosystems Engineering, Hamburg University of Technology, Denickestrasse 15, D-21073 Hamburg, Germany

Abstract

Proteinâ??protein interactions (PPIs) play crucial roles in many fundamental biological processes such as signal transduction, transport, cellular motion, and most regulatory mechanisms. Owing to such overwhelming biological significance, elucidating the mechanisms of the interactions presents a challenge in molecular biology. Since PPIs are locally mediated through proteinâ??protein interfaces, systematic characterization of the physico-chemical properties of interfaces through which PPIs take place will provide valuable information for the rational design of novel PPIs. In the meanwhile, the huge number of biomolecular structures stored in the Protein Data Bank (PDB) makes it possible to discover fine details about the interface that enables the interaction between proteins by systematic investigation of those molecular structures. In this study, characteristics of proteinâ??protein interfaces are analyzed based on the non-redundant database in order to obtain statistical meanings. The non-redundant database is derived from the PDB by clustering chains into groups according to their amino acid sequence similarities and selecting a representative from each of those groups. When characterizing PPI interfaces, the stereo complementarity evaluated includes interface size measured in solventâ??accessible surface area (SAS) and the volume formed among the interface. Interface residues could also be found according to the SAS change of each surface residue during the formation of the protein complex. The energetic complementarity takes into account both the contributions from Van der Waals interactions and that from electrostatic interactions. Moreover, contributions of each interface residue are also examined to find hot spots. Considering the significance of PPIs in the construction of biomachinery such as metabolic channeling and biofunctional compartmentalization, it is expected that these results could be helpful for the artificial design of novel biomachinery for metabolic engineering.