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Moe 2019

Manufactured by Chemical Computing Group
Sourced in Canada

MOE 2019.01 is a computational chemistry software suite developed by Chemical Computing Group. It is designed to assist researchers and scientists in the analysis and modeling of chemical compounds and biological systems. The software provides a range of tools for tasks such as molecular modeling, structure-based drug design, and computational chemistry calculations.

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41 protocols using moe 2019

1

Molecular Docking of Compounds 1 and 25

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Compound 1, and 25 were docked using Gold (Cambridge Crystallographic Data Center; www.ccdc.cam.ac.uk) and Protein Data Bank entry 5LAB. The docking preparation for both protein and ligands were performed using MOE 2019.0101 (Chemical Computing Group). The surface representations were prepared using MOE 2019.0101 (Chemical Computing Group).
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2

Covalent and Non-Covalent Docking of Inhibitors

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Covalent docking of compounds in Figure 1, was obtained using Gold (Cambridge Crystallographic Data Center; www.ccdc.cam.ac.uk) (compound 1) or by non-covalent docking followed by manual bond formation and energy minimization of the covalent adduct (SYBYL-X 2.1.1; Certara, Princeton, NJ; compound 2) using Protein Data Bank entries 3HL5, 3UW4, and 2UVL for XIAP, cIAP1 and cIAP2, respectively. The docking preparation for both protein and ligands was performed using SYBYL-X 2.1.1 (Certara, Princeton, NJ) and MOE 2019.0101 (Chemical Computing Group). The figures were generated using MOE 2019.0101 (Chemical Computing Group). The coordinates for models of compound 2 in complex with the BIR3 domains are provided as supplementary information.
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3

Isoelectric Point Determination of Fab and scFv

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The isoelectric points were measured or calculated as described previously [20 (link)]. The pI of each the Fab and scFv was calculated from the primary sequences using algorithm in Molecular Operating Environment (MOE2019) (Chemical Computing Group, Montreal, Canada) and outlined by Sillero and colleagues [21 (link)].
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4

Molecular Docking of HDAC Inhibitors

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The known crystal complexes of HDAC1, HDAC6, HDAC8 and their ligand (PDB code: 5ICN, 5EDU, 4RN0) were obtained from PDB (http://www.rcsb.org). Molecular docking simulations in the HDACs were run using the MOE 2019 (Molecular Operating Environment, Chemical Computing Group, Montreal, Quebec, Canada) due to its universality and very fast speed. Ligands were prepared with the ChemBio3D Ultra 14.0 (PerkinElmer, Waltham, MA, USA), followed by MM2 energy minimization. Protein structures were also prepared with the MOE, which could automatically add hydrogen atoms to proteins by explicitly considering the protonation state of histidine and optimize the force field. All crystal water, small ligands and cofactors except HEM were removed. After this step, the binding sites were deduced from the known crystal complexes and the ligands were docked to the prepared proteins through flexible docking mode. Top scoring function poses were selected as representative of the simulations and were displayed with Open-Source PyMOLTM 1.8X software (Schrödinger, Ltd, New York, NY, USA).
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5

Molecular Docking of ACE Receptor

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Molecular docking is a computer simulation method to explain the binding patterns and interaction mechanisms between biomolecules at the atomic level. The crystal structure of the ACE receptor protein (1O8A) obtained from the PDB database was used as the target protein. MOE2019 (Chemical Computing Group ULC., Montreal, BC, Canada) was used to optimize the energy and structure of the ACE receptor and construct the 3D structure database of undecapeptides. Combining the critical amino acid residue (ALA354, GLU384, TYR523, GLN281, HIS353, HIS513, LYS511, TYR520, GLU162) in functional pockets (S1, S2, S1′) of the ACE receptor reported in the literature [5 (link)], the docking scoring value, the number of bonds formed, and the docking energy of undecapeptides to the ACE receptor were used as indicators to select the tightly bound undecapeptide–receptor complexes. Molecular docking was performed with 3 replications to verify the stability of the molecular simulation results. The Site Finder computed and applied the docking sites in the ACE receptor. The London dG score and number of poses were defaulted in MOE. MOE analyzed the interaction modes of the undecapeptides and the ACE receptor.
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6

In silico Characterization and Docking

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In silico prediction of logP, total polar surface area (TPSA), and drug likeness (Lipinski Rule of 5) were determined using the SwissADME server [33 (link)]. Docking studies were performed using MOE 2019 (Chemical Computing Group). The protein structure referenced for MAO-B was 2v5z.pdb and for AChE 4ey7.pdb. In the MAO-B enzyme file two chains are crystalized and chain B was deleted before docking was carried out. Protein was prepared before docking by protonation of amino acids at pH 7.4. The binding site was identified as the area where co-crystallized ligand was located. Since MOE recognizes FAD as a part of the ligand set, we first designated the true ligand as so that MOE could use it in the docking run. Only the top-returned binding pose (most negative binding energy) of each ligand was further evaluated. The induced-fit binding mode was used to study the ligand-protein interaction, and solvent was allowed part of the docking calculation. As control docking experiment, the root-square mean deviation (RMSD) was calculated for each of the two enzymes. A RSMD < 2 Å was considered adeqote for our studies [34 (link)].
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7

SL Receptor Binding Affinity Evaluation

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Molecules were drawn with ChemBioDraw Ultra 13.0 software and minimized with MOE 2019 (Chemical Computing Group Inc., Montreal, QC, Canada). The SL receptor OsD14 (PDB: 5DJ5) and ShHTL7 (PDB: 7SNU) downloaded from Protein Data Bank (https://www.rcsborg accessed on 2 April 2023) were prepared by the process of deleting water, adding hydrogen, adding Gasteiger charges, merging nonpolar hydrogen and so on by AutodockTools-1.5.6 (Scripps, La Jolla, CA, USA). Docking was operated by MOE 2019 after setting method (placement: triangle matcher, refinement: rigid receptor), score (placement: London dG, refinement: GBVI/WSA dG) and poses (placement: 300, refinement: 5). The lowest binding energy for the docked conformations was chosen from 300 conformations as the representative binding energy to evaluate the potential of the corresponding compounds. The best docking poses were selected for analyzing the interactions between SL receptor and target compounds.
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8

Molecular Docking of Antiviral Compounds

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Molecular docking was performed using the Molecular Operating Environment software (MOE 2019) (Chemical Computing Group, Montreal, Canada). The crystal structure of the CACTD-SP1 Gag fragment (PDB ID: 5I4T) was obtained from the RCSB Protein Data Bank. The structure file was subjected to the QuickPrep procedure of MOE. The BVM structure was taken from the PubChem database. The 3D structure of DSC was generated using Chem3D software 2018. Multiple conformations of small molecules in the format of mol2 were generated as ligand libraries using Frog2.14 program (https://bioserv.rpbs.univ-paris-diderot.fr/services/Frog2/, accessed on 7 October 2021). The partial charges of all protein and ligand atoms were calculated using the implemented Amber10: EHT force field. For both ligands, all poses were located inside the cavity formed by the 6HB with different positions or orientations. Docking simulation was carried out choosing the triangle matcher for placement of the ligand in the binding site and ranked with the London dG scoring function. The best 30 poses were passed to refinement and energy minimization using the rigid receptor method and then rescored with the GBVI/WSA dG scoring function.
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9

Molecular Dynamics of Protein-Ligand Docking

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Modeling, simulations and structural visualizations were performed using MOE 2019 (Chemical Computing Group ULC, Montreal, CA) based on RCSB Protein Data Bank structure 2I66.72 (link) The protein was protonated at T = 310 K, pH 7.0, salt at 200 mM using GB/VI electrostatics. Docking simulations used flexible receptor and flexed the ligand, while docking targeted the active site. For each docking simulation initial placement calculated 50 poses using triangle matching with London dG scoring, the top 5 poses were refined using forcefield Amber10:ETH and Affinity dG scoring (Escore2). The top pose was used then refined using molecular dynamics. Molecular dynamics used the NPA algorithm and the Amber10:ETH forcefield. Solvent was a water droplet with 0.1 M NaCl and used 9518 solvent molecules. Simulation protocol was an equilibrium step for 100 ps at 300 K and a production step for 500 ps at 300 K with a step time of 0.5 ps.
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10

Virtual Screening of MERS-CoV PLpro Inhibitors

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The MOE program was employed to perform docking studies for all the screened compounds. The model of MERS-CoV PLpro (Protein Data Bank [PDB] ID: 4RNA, chains A) was utilized for a docking process (Lee et al., 2015 (link)). Protonation was performed on the crystal structure of the protein of interest utilizing the Protonate 3D technique (Labute 2009 (link)), and energy minimization was achieved with the help of the MOE-applied AMBER12 force field. The active site was identified using the site finder module of Molecular Operating Environment (MOE) 2019 (Chemical Computing Group, Montreal, Canada). As a method of placement during the docking procedure, the triangle matcher algorithm was also employed. The generalized Born volume integral/weighted surface area dG rescoring function and the London dG scoring function were also utilized in this study. Each compound was docked to its respective interaction binding site. Following this, the interaction of vital residues between compounds and proteins was fingerprinted using a protein–ligand interaction fingerprint (PLIF). (Da and Kireev 2014 (link)). Further binding positions were examined visually by MOE 2019.
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