Downloads provided by UsageCounts
Part of the BioExcel Virtual Workshop on Best Practices in QM/MM Simulation of Biomolecular Systems Video recording available at https://www.youtube.com/watch?v=aQdjC-W9Wy4 Abstract In this webinar, I discuss our approach to performing QM/MM calculations [1, 2], emphasizing three aspects of QM/MM calculations we have developed in our group. The first is the combination of QM/MM calculations with experimental raw data in the form of X-ray or neutron crystallography, NMR or EXAFS measurements [3–6]. This has turned out to be a powerful approach to improve structures, determine what is really seen in the structures and settle protonation and oxidation states [7–10]. The second is the bigQM approach, in which we try to converge the energies with respect to the size of the QM system by performing single-point energy calculations including all residues within 4.5–6 Å of a minimal QM system, all buried charges in the protein and moving cut bonds at least three residues away from the active site, in total typically ~1000 atoms [11, 12]. The third is to calculate QM/MM free energies without actually performing QM/MM molecular dynamics simulations with the reference-potential approach [13, 14]. References [1] Ryde U (2016) QM/MM Calculations on Proteins. Methods Enzymol 577:119–158. https://doi.org/10.1016/bs.mie.2016.05.014 [2] Cao L, Ryde U (2018) On the difference between additive and subtractive QM/MM calculations. Front Chem 6:89. https://doi.org/10.3389/fchem.2018.00089 [3] Ryde U, Olsen L, Nilsson K (2002) Quantum chemical geometry optimizations in proteins using crystallographic raw data. J Comput Chem 23:1058–1070. https://doi.org/10.1002/jcc.10093 [4] Hsiao Y, Drakenberg T, Ryde U (2005) NMR structure determination of proteins supplemented by quantum chemical calculations: Detailed structure of the Ca2+ sites in the EGF34 fragment of protein S. J Biomol NMR 31:97–114. https://doi.org/10.1007/s10858-004-6729-7 [5] Hsiao Y, Tao Y, Shokes JE, et al (2006) EXAFS structure refinement supplemented by computational chemistry. Phys Rev B 74:214101. https://doi.org/10.10.1103/PhysRevB.74.214101 [6] Caldararu O, Manzoni F, Oksanen E, et al (2019) Refinement of protein structures using a combination of quantum-mechanical calculations with neutron and X-ray crystallographic data. Acta Crystallogr Sect D Biol Crystallogr 75:368–380 [7] Ryde U, Nilsson K (2003) Quantum Chemistry Can Locally Improve Protein Crystal Structures. J Am Chem Soc 125:14232–14233. https://doi.org/10.1021/ja0365328 [8] Nilsson K, Ryde U (2004) Protonation status of metal-bound ligands can be determined by quantum refinement. J Inorg Biochem 98:1539–1546. https://doi.org/10.1016/j.jinorgbio.2004.06.006 [9] Söderhjelm P, Ryde U (2006) Combined computational and crystallographic study of the oxidised states of [NiFe] hydrogenase. J Mol Struct THEOCHEM 770:199–219. https://doi.org/10.1016/j.theochem.2006.06.008 [10] Cao L, Caldararu O, Rosenzweig AC, Ryde U (2018) Quantum Refinement Does Not Support Dinuclear Copper Sites in Crystal Structures of Particulate Methane Monooxygenase. Angew Chemie – Int Ed 57:162–166. https://doi.org/10.1002/anie.201708977 [11] Hu L, Söderhjelm P, Ryde U (2013) Accurate reaction energies in proteins obtained by combining QM/MM and large QM calculations. J Chem Theory Comput 9:640–649. https://doi.org/10.1021/ct3005003 [12] Sumner S, Söderhjelm P, Ryde U (2013) Effect of Geometry Optimizations on QM-Cluster and QM/MM Studies of Reaction Energies in Proteins. J Chem Theory Comput 9:4205–4214. https://doi.org/10.1021/ct400339c [13] Rod TH, Ryde U (2005) Accurate QM/MM free energy calculations of enzyme reactions: Methylation by catechol O-methyltransferase. J Chem Theory Comput 1:1240–1251. https://doi.org/10.1021/ct0501102 [14] Olsson MA, Ryde U (2017) Comparison of QM/MM Methods To Obtain Ligand-Binding Free Energies. J Chem Theory Comput 13:2245–2253. https://doi.org/10.1021/acs.jctc.6b01217
BioExcel Virtual Workshop on Best Practices in QM/MM Simulation of Biomolecular Systems, QM/MM
BioExcel Virtual Workshop on Best Practices in QM/MM Simulation of Biomolecular Systems, QM/MM
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 10 | |
| downloads | 12 |

Views provided by UsageCounts
Downloads provided by UsageCounts