Based on in vitro data on α-amylase, an in-house library of 39 ligands (including acarbose as the standard ligand) was created to screen a potential HPA inhibitor. Supplementary data contains information about the ligands (S1 Table ). The ligand structures were sketched in Maestro’s 2D sketcher and converted to a low-energy 3D state using Schrödinger’s LigPrep module [13 ]. The OPLS4 force field was employed to generate a low-energy state structure [14 (link)]. Additionally, at pH 7.0 ± 2.0, Epik produced tautomeric and ionization states and generated a maximum of 32 conformers per ligand.
Ligprep module
Manufactured by Schrödinger
Sourced in United States
The LigPrep module is a computational tool that generates 3D molecular structures from 2D chemical structures. It performs a series of operations, including structure conversion, ionization, tautomer generation, and conformer production, to prepare ligand molecules for further analysis and drug discovery applications.
Automatically generated - may contain errors
Lab products found in correlation
Protein preparation wizard, by Schrödinger (22 mentions)
Ligprep, by Schrödinger (16 mentions)
Glide module, by Schrödinger (13 mentions)
Protein preparation wizard module, by Schrödinger (11 mentions)
Maestro, by Schrödinger (11 mentions)
Prime module, by Schrödinger (7 mentions)
Maestro 10, by Schrödinger (7 mentions)
Macromodel, by Schrödinger (4 mentions)
Opls 2005, by Schrödinger (4 mentions)
Prepwiz module, by Schrödinger (3 mentions)
Maestro suite, by Schrödinger (3 mentions)
Receptor grid generation module, by Schrödinger (3 mentions)
Maestro software, by Schrödinger (3 mentions)
Suite 2020 3, by Schrödinger (2 mentions)
Glide xp, by Schrödinger (2 mentions)
Opls3e, by Schrödinger (2 mentions)
Qikprop, by Schrödinger (2 mentions)
Marvinsketch 5, by ChemAxon (2 mentions)
Epik module, by Schrödinger (2 mentions)
Schrodinger software, by Schrödinger (2 mentions)
236 protocols using ligprep module
1
HPA Inhibitor Screening Protocol
2
Molecular Docking of Phytochemicals against SARS-CoV-2
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The ligands used were metabolites of Cymbopogon citratus, Kaempferia galangal, Curcuma longa, Curcuma xanthorrhiza, and Zingiber officinale. Plant metabolites that had a history of antiviral testing were also used as ligands. All compounds were obtained from http://www.knapsackfamily.com . Screening using SwissADME (http://www.swissadme.ch/index.php ) according to the five Lipinski rules was performed on 240 metabolites. The ligand structure was formed using JChem software and optimized using the LigPrep module from Schrödinger's software (Schrödinger LLC, New York, NY, USA). Atomic protonation was adjusted to pH 7.0 with Epik software (Schrödinger LLC), and geometry optimization used OPLS_2005 Force Field software (Schrödinger LLC).
Protein structures targeted for docking were obtained from the Protein Data Bank (https://www.rcsb.org/ ). The proteins used were 3CLpro (PDB ID: 6M2N chain A), RdRp (PDB ID: 6M71 chain A), and spike glycoprotein (PDB ID: 6VXX chain B). Protein preparation was performed using AutoDockTools version 1.5.6. Protein validation for 3CLpro was performed by calculating the root mean square deviation (RMSD) of the protein with its co-crystalline ligand using PyMOL software version 2.3.4 (Schrödinger LLC).
Protein structures targeted for docking were obtained from the Protein Data Bank (
3
Molecule Optimization and Characterization
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A total of 40 molecules were built on Maestro Molecule Builder of Schrödinger and optimized using OPLS_2005 force field in LigPrep module of Schrödinger software 2017-1.36 All the possible protomers and ionization states were enumerated for ligands at a pH of 7.4 using Ionizer. The tautomeric states were generated for chemical groups with possible prototropic tautomerism.
4
Computational Modeling of Small Molecule Docking
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Three-dimensional models of compounds were built using the LigPrep module of Schrödinger software [38 ]. Input chiralities were retained, protonation states were generated with Epik at a physiological pH 7.4 [39 (link)], and the resulting structures were optimized using the OPLS4 force-field.
A docking receptor grid was generated centering the docking box at the centroid of the following residues: Arg877, Trp931, and Ser933. The size of the docking box was set to 30 × 30 × 30 Å. The hydroxyl group of Ser933 and the thiol group of Cys961 were allowed to rotate during docking.
Compounds were docked with the standard precision (SP) Glide docking methodology [40 (link)]. Ligands were docked flexibly, while the protein was kept rigid. Sampling of the ligand conformational space was enhanced by four times, 50,000 poses per ligand were retained after the rough scoring stage and 1000 poses per ligand were kept for energy minimization. Following final docking, 100 poses per ligand were passed to post-docking minimization, and the top ten scoring poses were inspected manually.
A docking receptor grid was generated centering the docking box at the centroid of the following residues: Arg877, Trp931, and Ser933. The size of the docking box was set to 30 × 30 × 30 Å. The hydroxyl group of Ser933 and the thiol group of Cys961 were allowed to rotate during docking.
Compounds were docked with the standard precision (SP) Glide docking methodology [40 (link)]. Ligands were docked flexibly, while the protein was kept rigid. Sampling of the ligand conformational space was enhanced by four times, 50,000 poses per ligand were retained after the rough scoring stage and 1000 poses per ligand were kept for energy minimization. Following final docking, 100 poses per ligand were passed to post-docking minimization, and the top ten scoring poses were inspected manually.
5
Structural Preparation of HDAC Protein for Docking
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The crystal structure of HDAC was retrieved from Protein Data Bank (PDB) with PDB ID: 4LXZ (Lauffer et al., 2013) (Figure 2). The structure was downloaded in pdb format and was further prepared for docking process. The protein was prepared using the PrepWiz module of Schrodinger suite, 2013 (Schrodinger. LLC, New York, NY). In the preparation procedure, the protein was first preprocessed by assigning the bond orders and hydrogens, creating zero order bonds to metals and adding disulphide bonds. The missing side chains and loops were filled using Prime Module of Schrodinger. Further all the water molecules were deleted beyond 5 Å from hetero groups. Once the protein structure was preprocessed, H bonds were assigned which was followed by energy minimization by OPLS 2005 force field (Jorgensen et al., 2005) . The final structure obtained was saved in.pdb format for further studies. All the ligands were optimized through OPLS 2005 force field algorithm embedded in the LigPrep module of Schrodinger suite. The ionizations of the ligand were retained at the original state and were further desalted. The structures thus optimized were saved in sdf format for docking procedures.
6
Protein Structure Modeling and Docking
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The crystal structure of the protein, was obtained from RCSB (PDB ID: 2JK6) [29] (link) and was used for modeling purposes. ProteinPrep wizard of the Schrodinger program [30] was used to prepare protein for docking studies. Since the receptor contains cognate ligand therefore a grid was generated for docking purposes by creating a box centroid at the cognate ligands of the TRyR. The ligand was drawn in Maestro workspace using the builder module [31] , hydrogens were added and ligand was saved in three dimensional geometry for further use. The ligand was prepared using the Ligprep module offered by Schrodinger program [32] , and was used for further molecular docking studies. The Glide standard precision (Glide-SP) module was used for docking simulations [24] .
7
Small Molecule IC50 Data Optimization and Alignment
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The small molecules used in this study were taken from the literature with their IC50 value [27 (link)] shown in Supplementary Table S1 . A total of 36 compounds were retrieved from PubChem (https://pubchem.ncbi.nlm.nih.gov/ as accessed on 15 July 2023) database. Compounds’ 2D structures were optimized using the LigPrep module offered by Schrodinger 2023-2 [50 (link)]. However, the optimization method used default settings, with the OPLS4e force field applied and ionization states neutralized. The intrinsic stereoisomerism of each ligand including its critical chirality was preserved throughout this optimization process. Following optimization, the structures were aligned using the ligand alignment tool. Since every structure is a congeneric series, the software algorithm was used to automatically determine the reference scaffold for the alignment. This is helpful because the program identifies the best scaffold, which serves as a guide. Meanwhile, the biological activity values (IC50) were converted into pIC50 using the above-mentioned Equation (1 ). Finally, the prepared structures were employed for 3D-QSAR and pharmacophore modeling.
8
Compound Preparation and Protein Docking
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Compound preparation; The 2D structure of the compound was drawn in Marvin Sketch software, and the 2D structure was transformed into the 3D structure. Save the treated compound in *.mol2 format. Import the *.Mol2 le of the compound into the Ligprep module in the Schrodinger package for ligand preparation, that is, ionization (pH: 7.0+/-2.0), desalination, generation of tautomers, etc. The ligand was optimized using the same force eld (OPLS 2005) as in the receptor optimization process. Other parameters were software default values.
Protein preparation; according to the target information obtained by virtual screening, the protein structures were downloaded from the PDB protein database (https://www.rcsb.org/)) for molecular docking.
Protein preparation; according to the target information obtained by virtual screening, the protein structures were downloaded from the PDB protein database (https://www.rcsb.org/)) for molecular docking.
9
Geometric Optimization and Ionization of Selective MEL Ligand
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A functionally selective small-molecule MEL (an agonist in MT1 and an antagonist in MT2 (ref. 23 (link))) was downloaded from Pubchem Database (https://pubchem.ncbi.nlm.nih.gov/ ). The LigPrep module in the Schrodinger suite was introduced for geometric optimization by using the OPLS_2005 force field. Ionization states of ligands were calculated with the Epik tool29 (link) employing Hammett and Taft methods in conjunction with ionization and tautomerization tools.
10
Computational Screening of Approved Drugs and Natural Products Against SARS-CoV-2 Mpro
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3D structure of Mpro was obtained from RCSB Protein Data Bank (PDB code: 6LU7) [24 ], prepared to ensure structural correctness for hydrogen consistency, bond orders, steric clashes and charges using protein preparation wizard [22 ] in Schrodinger Suite supported by OPLS3e force field. Thus, the prepared structures were used for pharmacophore model development as well as for receptor grid generation for the docking protocol. The receptor grid was generated considering the position of the co-crystallized ligand N3 in the active site.
The 3-dimensional approved drug and diagnostic agent library (approved by FDA and other world authorities) was obtained from SuperDRUG2 resource for approved drug [19 (link), 20 (link)]. A total of 4369 molecules were prepared for computational study at physiological pH condition by using LigPrep module of Schrodinger [25 ]. Asinex BioDesign library [21 ], which consists of pharmacologically important structural features from natural products in the chemical scaffolds having synthetic feasibility, was obtained from Asinex database and 175,815 molecules (database updated in early 2020) were prepared using LigPrep module [25 ].
The 3-dimensional approved drug and diagnostic agent library (approved by FDA and other world authorities) was obtained from SuperDRUG2 resource for approved drug [19 (link), 20 (link)]. A total of 4369 molecules were prepared for computational study at physiological pH condition by using LigPrep module of Schrodinger [25 ]. Asinex BioDesign library [21 ], which consists of pharmacologically important structural features from natural products in the chemical scaffolds having synthetic feasibility, was obtained from Asinex database and 175,815 molecules (database updated in early 2020) were prepared using LigPrep module [25 ].
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