TML&TDL-BP/RI-Score/GOLD/AUTODOCK-VINA
Schrodinger, GOLD, AUTODOCK VINA, R-TDA, Javaplex, Scikit-learn
PHE211 and PHE70 are set as flexible in docking.
Ligands are prepared by Schrodinger. Docking is done by using GOLD. Poses are selected by plp and autodock vina scores. Binding free energy is predicted by topology based machine learning method.
No
Align_target/Schrodinger
Schrodinger
(prepwizard) -propka_pH 7.0
(prepwizard) -fillsidechains -s # fillsidechains for target protein
(ligprep) -adjust_itc -ph
Use Homology Modeling in Maestro to build protein structure from given sequence. Maestro's prepwizard was used to optimize the protein with a standard pH value and fillsidechains option. Maestro's ligprep was used to generate optimized 3d structure of ligands from 2d structure. Binding site is determined by using the ligand's position in the reference protein ultilized in structure prediction procedure.
Solvation model = VSGB
Force field = OPLS3
Refine atoms within 10.0 \AA of ligand
Sampling algorithm = Local optimization
Each target ligand is aligned to its most similar structure available in Protein Data Bank. The algined ligand is optimized to the binding site of the receptor using Prime in Schrodinger.
No
Yes