CMV terminase subunit UL89 in complex with α,γ-diketoacid analogue inhibitor and two Mn2+ ions was retrieved from Protein DataBank under the accession code of 6EY7 [29 (link)]. Since there were no conserved water molecules reported, all the water molecules were deleted. The crystal structure was subjected to geometry correction process which entails assigning the correct bond order, terminal capping and addition of missing atoms followed by protonation. Moreover, the missing loops were modeled using the Loop Modeler module of MOE v.2019.01 (Chemical Computing Group, QC, Canada). Afterwards, the energy minimization was carried out by using AMBER10:EHT force field. Finally, the structure was saved into pdb format for further processing.
Moe v 2019
Manufactured by Chemical Computing Group
Sourced in Canada
MOE v.2019.01 is a software package designed for computational chemistry and molecular modeling. It provides a range of tools for molecular structure, visualization, and analysis.
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Lab products found in correlation
4 protocols using moe v 2019
1
Structural Characterization of CMV UL89 Inhibitor Complex
2
Molecular Docking of Alkaloids
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Molecular Operating Environment (MOE, v2019.01, Chemical Computing Group, Montreal, Canada) was used to simulate the interaction between selected alkaloids and targets (Tian et al., 2022 (link)). The 2D structures of peak 5 (magnoflorine), 19 (berberine), 21 (chelerythrine), and the positive control (rofecoxib and nordihydroguaiaretic acid [NDGA]) were imported to establish a compound database. Then, 3D conformations were prepared to obtain a stereo-structure database. Crystallized structures of the enzymes were downloaded from RCSB PDB (COX-2 PDB: 5KIR; 5-LOX PDB: 6N2W) based on previous studies (Orlando and Malkowski, 2016 (link); Gilbert et al., 2020 (link)). After removing water and adding hydrogen, one chain containing a ligand was kept and optimized for minimum energy conformation. Molecular docking was conducted in the active pocket. London dG scores were produced by using the Triangle Matching method to dock at 30 preferential poses. In addition to energy scores, the interactions of residues, energy, and bonds were displayed, compared, and discussed to evaluate the ligand–target interactions.
3
Empirical Energy Functions for Molecular Docking
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In the
DivCon Discovery Suite v.DEV.671-b4608, we provide two empirical energy
functions: the GARF statistical potential70 (link) and the AMBERff14 functional potential63 (link),71 (link) optimized for the MT method. The holo-protein:ligand complex binding
modes can be either generated using the “built-in” MTDock protein:ligand docking module55 (link) or provided from other sources such as molecular simulations or
alternative protein:ligand docking protocols. In order to compare
the MT protocol performances with different settings, we applied both
the GARF potential function and the AMBERff14 force field for the
partition function calculation, and we used both MTDock and the industry-standard Molecular Operating Environment (MOE)
v.2019.0102 from Chemical Computing Group, Inc. to generate contrasting
protein:ligand complex poses. For MTDock and optionally
for the MOE interface (in the “three-step workflow”
discussed below), ligand conformers were generated using MTCS.59 (link) The MTCS method was used
in all cases to calculate the unbound partition function.Figure 4 depicts a flowchart to aid in understanding
how the various MT parts work together (and with third-party methods)
to complete and generate the MT scores.
DivCon Discovery Suite v.DEV.671-b4608, we provide two empirical energy
functions: the GARF statistical potential70 (link) and the AMBERff14 functional potential63 (link),71 (link) optimized for the MT method. The holo-protein:ligand complex binding
modes can be either generated using the “built-in” MTDock protein:ligand docking module55 (link) or provided from other sources such as molecular simulations or
alternative protein:ligand docking protocols. In order to compare
the MT protocol performances with different settings, we applied both
the GARF potential function and the AMBERff14 force field for the
partition function calculation, and we used both MTDock and the industry-standard Molecular Operating Environment (MOE)
v.2019.0102 from Chemical Computing Group, Inc. to generate contrasting
protein:ligand complex poses. For MTDock and optionally
for the MOE interface (in the “three-step workflow”
discussed below), ligand conformers were generated using MTCS.59 (link) The MTCS method was used
in all cases to calculate the unbound partition function.
how the various MT parts work together (and with third-party methods)
to complete and generate the MT scores.
4
Molecular Docking of BBR with Nlrp3
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The 3D structure of BBR was transformed from 2D version by Molecular Operating Environment (MOE v2019.0102, Chemical Computing Group Inc., Montreal, QC, Canada) through energy minimization. The Nlrp3 protein structure data was downloaded from the protein database (RCSB Protein Data Bank-RCSB PDB, www.pdb.org ), and the structure ID was 6NPY. Before docking, the force field of AMBER10: EHT and the implied solvation model of Reaction Field (R-field) were selected. Docking follows the theory of “induced fit,” that is, the conformation of ligand and receptor will change during molecular docking, which is not completely rigid. Small molecule ligands are placed on the active site of the receptor, followed by ligand orientation and conformation search. MOE Dock provides a database of dynamically generated conformations, which are then refined using force field-based methods. The number of docking poses is set to 20. The scoring functions used in this experiment are London dG and generalized born volume integral/weighted surface area (GBVI/WSA) dG scoring functions based on the force field. GBVI/WSA dG, a forcefield-based scoring function, determines the binding free energy (kcal/mol) of the ligand from a given pose. The conformation with the lowest free energy of binding was selected as the most plausible binding mode. Molecular docking result image processing using MOE.
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