| Popis: |
Transmembrane (TM) proteins are estimated to account for ∼20-30% of the human genome and serve as important drug targets. Despite the significant progress in experimental techniques, TM protein structure determination remains a challenge in general. Computational approaches, including de novo and comparative structure predictions, have played a significant role in structural and functional studies of membrane proteins, as well as in their structure-based drug design efforts. A major challenge of membrane protein structure prediction is to assemble individual helices into high-quality tertiary structures. Analyzing inter-residue interactions within membrane proteins is of significance to developing novel tools to tackle this challenge. In this work, we first identified four approaches for determining inter-residue interactions in protein structures and studied their correlation to individual quality measures. It was found that the best correlation was achieved by the approach focusing exclusively on favorable inter-residue interactions. Next, this best approach was applied to the analysis of multiple datasets of helical membrane protein structure models, including a dataset of homologous structure pairs with the sequence identity at the twilight zone. A simple measure was elucidated that directly correlates with the quality of these structure models. These results suggest a useful tool for computational modeling of membrane protein structures. This work was supported by the grant (1R15GM084404) from National Institute of Health. |
