Conserved network properties of helical membrane protein structures and its implication for improving membrane...

Homology modeling techniques remain an important tool for membrane protein studies and membrane protein-targeted drug development. Due to the paucity of available structure data, an imminent challenge in this field is to develop novel computational methods to help improve the quality of the homology models constructed using template proteins with low sequence identity. In this work, we attempted to address this challenge using the network approach developed in our group. First, a structure pair dataset of 27 high-resolution and low sequence identity (7-36%) comparative TM proteins was compiled by analyzing available X-ray structures of helical membrane proteins. Structure deviation between these pairs was subsequently confirmed by calculating their backbone RMSD and comparing their potential energy per residue. Next, this dataset was further studied using the network approach. Results of these analyses indicated that the network measure applied represents a conserved feature of TM domains of similar folds with various sequence identities. Further comparison of this salient feature between high-resolution template structures and their homology models at the twilight zone suggested a useful method to utilize this property for homology model refinement. These findings should be of help for improving the quality of homology models based on templates with low sequence identity, thus broadening the application of homology modeling techniques in TM protein studies.