A Benchmark for Homomeric Enzyme Active Site Structure Prediction Highlights the Importance of Accurate Modeling of Protein Symmetry
Accurate prediction and modeling of an enzyme’s active site are critical for engineering efforts as well as providing insight into an enzyme’s naturally occurring function. Previous efforts demonstrated that the integration of constraints enforcing strict geometric orientations between catalytic res...
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Veröffentlicht in: | ACS omega 2019-12, Vol.4 (27), p.22356-22362 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Accurate prediction and modeling of an enzyme’s active site are critical for engineering efforts as well as providing insight into an enzyme’s naturally occurring function. Previous efforts demonstrated that the integration of constraints enforcing strict geometric orientations between catalytic residues significantly improved the modeling accuracy for the active sites of monomeric enzymes. In this study, a similar approach was explored to evaluate the effect on the active sites of homomeric enzymes. A benchmark of 17 homomeric enzymes with known structures and a bound ligand relevant to the established chemistry were identified from the protein data bank. The enzymes identified span multiple classes as well as symmetries. Unlike what was observed for the monomeric enzymes, upon the application of catalytic geometric constraints, there was no significant improvement observed in modeling accuracy for either the active site of the protein structure or the accuracy of the subsequently docked ligand. Upon further analysis, it is apparent that the symmetric interface being modeled is inaccurate and prevented the active sites from being modeled at atomic-level accuracy. This is consistent with the challenge others have identified in being able to predict de novo protein symmetry. To further improve the accuracy of active site modeling for homomeric proteins, new methodologies to accurately model the symmetric interfaces of these complexes are needed. |
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ISSN: | 2470-1343 2470-1343 |
DOI: | 10.1021/acsomega.9b02636 |