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Protein network centralities as descriptor for QM region construction in QM/MM simulations of enzymes
Ist Teil von
Physical chemistry chemical physics : PCCP, 2023-08, Vol.25 (3), p.2183-2188
Ort / Verlag
England: Royal Society of Chemistry
Erscheinungsjahr
2023
Link zum Volltext
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
The construction of a suitable QM region is the most crucial step in setting up hybrid quantum mechanics/molecular mechanics (QM/MM) simulations for enzymatic reactions. The QM region should ideally include all important amino acids residues, while being as small as possible to save computational effort. Most available methods for systematic QM region construction are based either on the distance of single amino acids to the active site or on their electrostatic effect. Such approaches might miss non-electrostatic and long-range allosteric interactions. Here, we present a proof of concept study for the application of protein network analysis to tackle this problem. Specifically, we explore the use of the protein network centralities as descriptor for QM region construction. We find that protein network centralities, in particular the betweenness centrality, can be a useful descriptor for systematic QM region construction. We show that in combination with our previously developed point charge variation analysis, they can be used to identify important residues that are missed in purely electrostatic approaches.
Network analysis is applied for the construction of QM/MM models, and protein network centralities are proposed as a promising descriptor for identifying residues with a large non-electrostatic effect on the QM region.