Accessible and predictable QM-cluster model building for enzymes with the Residue Interaction Network Residue Selector
Abstract
Quantum mechanical (QM) modeling is a useful tool for understanding and supplementing experimental observations of enzyme mechanisms and structures. The QM-cluster approach uses truncated models containing only a selected region of the active site; the remainder of the protein structure is deleted and its polarization effects are represented indirectly. While there have been numerous successful studies utilizing QM-cluster models, the field suffers from an abundance of oversimplified models which contradict experimental observations and a general lack of standardization and reproducibility. Selecting which amino acid residues to include in the model has historically required a high level of expertise, prior knowledge of the enzyme, and hands-on effort. This review describes how these issues have motivated the development and usage of the Residue Interaction Network ResidUe Selector (RINRUS) software package. RINRUS simplifies the QM-cluster model building process by automating the selection, truncation and capping of the chemical components of an enzyme active site. With RINRUS, reliable and predictable QM-cluster models can be made in seconds by new and experienced computational enzymologists alike.
Publication Title
Annual Reports in Computational Chemistry
Recommended Citation
Wappett, D., & DeYonker, N. (2024). Accessible and predictable QM-cluster model building for enzymes with the Residue Interaction Network Residue Selector. Annual Reports in Computational Chemistry, 20, 131-155. https://doi.org/10.1016/bs.arcc.2024.10.002
