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. 2017 Jun 5;38(21):1879-1886.
doi: 10.1002/jcc.24829. Epub 2017 May 11.

CHARMM-GUI ligand reader and modeler for CHARMM force field generation of small molecules

Affiliations

CHARMM-GUI ligand reader and modeler for CHARMM force field generation of small molecules

Seonghoon Kim et al. J Comput Chem. .

Abstract

Reading ligand structures into any simulation program is often nontrivial and time consuming, especially when the force field parameters and/or structure files of the corresponding molecules are not available. To address this problem, we have developed Ligand Reader & Modeler in CHARMM-GUI. Users can upload ligand structure information in various forms (using PDB ID, ligand ID, SMILES, MOL/MOL2/SDF file, or PDB/mmCIF file), and the uploaded structure is displayed on a sketchpad for verification and further modification. Based on the displayed structure, Ligand Reader & Modeler generates the ligand force field parameters and necessary structure files by searching for the ligand in the CHARMM force field library or using the CHARMM general force field (CGenFF). In addition, users can define chemical substitution sites and draw substituents in each site on the sketchpad to generate a set of combinatorial structure files and corresponding force field parameters for throughput or alchemical free energy simulations. Finally, the output from Ligand Reader & Modeler can be used in other CHARMM-GUI modules to build a protein-ligand simulation system for all supported simulation programs, such as CHARMM, NAMD, GROMACS, AMBER, GENESIS, LAMMPS, Desmond, OpenMM, and CHARMM/OpenMM. Ligand Reader & Modeler is available as a functional module of CHARMM-GUI at http://www.charmm-gui.org/input/ligandrm. © 2017 Wiley Periodicals, Inc.

Keywords: CGenFF; drug design; molecular dynamics simulation; molecular modeling; protein-ligand interactions.

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Figures

Figure 1
Figure 1
Schematic overview of Ligand Reader & Modeler.
Figure 2
Figure 2
Illustrative procedure of bond degree based maximum common subgraph algorithm using the chemical structures, the graph representations, and the convoluted graphs of (A, C, E) alanine and (B, D, F) lactic acid. (G) A product graph of (E) and (F) shows the bold nodes used for the maximum clique search whose result is shown in the connecting lines; in this example, all bold nodes are involved in the maximum clique.
Figure 3
Figure 3
Snapshot of a CSML search result for NAD. (A) The NAD structure on the sketchpad of Ligand Reader & Modeler. One can visualize (B) the 3D structures of searched molecules and (C) the shared heavy atoms between similar residues (represented by red) on a pop-up window.
Figure 4
Figure 4
Snapshot of a sketchpad drawn for the combinatorial structure generation with TIBO in PDB:1TVR.
Figure 5
Figure 5
Snapshots of (A) the structure of 5JY6.pdb, (B) 5JY6_modified.pdb that contains NAD+, and (C) a solvated system of 5JY6_modified.pdb using Quick MD Simulator. The NAD heavy atom coordinates were preserved (pink dashed squares).
Figure 6
Figure 6
Snapshots of (A) NAD in 5JY6.pdb, (B) NAD+, and (C) NADH in glyceraldehyde 3-phosphate dehydrogenase (GAPDH). The ligand heavy atom coordinates were preserved with the redox site hydrogen atoms (blue dashed squares).
Figure 7
Figure 7
(A) “CSML Search” in PDB Manipulation Options. (B) The search results for NAD in holo-GAPDA (PDB: 5JY6)
Figure 8
Figure 8
Structures of (A) PDB: 4HG6 with two lauryldimethylamine-N-oxide (LDAO) ligands, and (B) the PDB file after the PDB reading and manipulation step using “CSML Search”.
Figure 9
Figure 9
Superposition of twenty-four TIBO derivatives generated by Ligand Reader & Modeler (multiple colors) with HIV-1 RT (magenta) and the scaffold atoms (orange).

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