Biovia discovery studio 4

Based on the crystal structure of the KK–EE (light chain K123, K124, heavy chain E147, K213; positions given in EU numbering) charge variant non-crossed Fab, the following intermediate charge variants were modeled: KQ–EK, KQ–KE, EK–EK and EK–EK. First, the sidechain types were exchanged where necessary. Afterwards, the sidechain conformers of residues at positions 123, 124 (light chain) and 147, 213 (heavy chain) were optimized simultaneously to attain a maximum number of favorable and a minimal number of unfavorable interactions, the latter including steric clashes. Rotamer optimization was performed using the Dunbrack rotamer library (Shapovalov and Dunbrack, 2011 (link)), plus the original rotamers as found in the crystal structure. The rotamer-optimized models were used as starting coordinates for unrestrained energy minimization using the CHARMM36 (Huang and MacKerell, 2013 (link)) force field in combination with the GBSW implicit solvent model (Im et al., 2003 (link)) and the ‘Smart Minimizer’ protocol (steepest descent followed by conjugate gradient (Luenberger, 1973 ) for 500 integration steps. All molecular modeling and simulation was done with BIOVIA Discovery Studio 4.5 (Dassault Systèmes BIOVIA Discovery Studio 4.5, San Diego).

Enantiomers of 1,3‐BDO were docked into the catalytic site of LnRCR using Discovery Studio 4.5 (Accelrys, San Diego, CA). Briefly, CDOCKER docking and interaction energies were measured, and proteins and ligands were parameterized using CHARMm force fields. Top ligand positions were clustered within a root‐mean‐square deviation of 2.0 Å and scored against the CDOCKER Interaction Energy. The resulting global structure with the lowest energy was selected for further analysis.
To investigate the role of binding pocket residues in complex stabilization, we performed computational site‐directed mutagenesis according to the ‘Calculate Mutation Energy (Binding)’ protocol available in Biovia Discovery Studio 4.5. The energy minimization of final docked complexes was performed with CHARMm using the Smart Minimizer algorithm in Discovery Studio 4.0 (Accelrys, San Diego, CA, USA). In silico mutagenesis was performed by calculating the free binding energy of the docked complex. Thus, the residues of the binding pocket were mutated into 19 different amino acids, to estimate the impact of each mutation on the binding within the complex. The mutation binding energy was finally calculated as ΔΔG_mut = ΔΔG_bind(mutant) ‐ ΔΔG_bind (wild type), where ΔΔG_mut is the mutation energy and ΔΔG_bind is the difference in the free energy between the complex and unbound states.

The ligands used for docking analysis were colochiroside A, ds-echinoside A, philinopside E, sphingosine, stichoposide C, 1-(5-chloro-2-methylphenyl)-5-(3-chlorophenyl)-2-(3-methylphenyl)-1H-imidazole-4-carboxylic acid, a tetra-substituted imidazole (an MDM2 inhibitor) and chalcone-4 (a CXCR4 inhibitor). SMILES codes of the compounds were converted to 3D structures in Protein Data Bank (PDB) format using BIOVIA Discovery Studio 4.5 (20 ). These structures were used for ligand docking. The 3D structure for chalcone-4 was obtained from the binding database (https://www.bindingdb.org/bind/index.jsp) (21 (link)) and the 3D structure for the substituted imidazole was obtained from the PDB (PDB ID, 4OQ3). The receptor structures were retrieved from the PDB for MDM2 (PDB ID, 4OQ3) and CXCR4 (PDB ID, 3OE6). The proteins then were prepared by BIOVIA Discovery Studio.