Computational Analysis of the Inhibition Mechanism of NOTUM by the ONIOM Method

Abstract

Notum is a member of serine hydrolyses that cleaves the palmitoleate moiety from Wingless-related integration site (Wnt) ligands. This enzyme plays crucial functions through modulating the Wnt signaling pathway. Inhibition of Notum carries therapeutic effects against a number of maladies including osteoporosis, cancer, and Alzheimer’s disease. Recently, a class of irreversible inhibitors based on esters of 4-(indolin-1-yl)-4-oxobutanoic acid have been reported. Using the crystal structures of enzyme-4-(indolin-1-yl)-4-oxobutanoate adduct and 4-(indolin-1-yl)-4-oxobutanoic acid-enzyme complex, we studied computationally the proposed inhibition mechanism using model systems based on the own n-layered integrated molecular orbital and molecular mechanics (ONIOM) method. In the first place, model systems were formulated to investigate the transesterification between the catalytic serine residue, Ser-232, and the methyl ester of 4-(indolin-1-yl)-4-oxobutanoate. In the second place, the hydrolysis mechanism of the resultant enzyme–inhibitor adduct was studied. The energetics of these steps were analyzed using a density functional theory functional in the ONIOM method. In addition, the roles of active-site residues during these steps were highlighted. It was found that the hydrolysis of the covalent adduct is highly endergonic corroborating the irreversible inhibition mechanism. These results will shed light not only on the inhibition mechanism but also on the catalytic mechanism.

WITHDRAWN: “Stepwise or Concerted or a Hybrid Mechanism for Berberine Bridge Enzyme?”: A Computational Mechanistic Study by QM-MM and QM Methods

“…32 In our previous reports, we computationally observed this case. [7][8][9] However, for BBE this was not observed presumably due to double covalent modi cation of FAD with Cys and His residues.…”

“…We observed higher activation energies with larger basis sets for ONIOM calculations for other FAD-based amine oxidases in our previous studies. [7][8] Among three functional with 6-31G basis set, ωB97XD functional estimated lowest barrier for hydride transfer process (21.2 kcal/mol) and CAM-B3LYP estimated highest barrier (25.5 kcal/mol). These three functional estimates lower activation energy in terms of Gibbs free energy than in terms of absolute energy.…”

“…Hydride transfer mechanism is supported with many experimental and computational studies for FADbased amine oxidases. In our group, we reported computational studies for hydride transfer process for a number of enzymes such as L-aspartate oxidase, 7 Nicotine oxidoreductase, 8 and Choline oxidase 9 using ONIOM method. This method which combines quantum mechanics (QM) and molecular mechanics (MM) has emerged as an important tool to study mechanistic details of enzyme reactions.…”

A Guide to In Silico Drug Design

“…Quantum mechanical (QM) approaches provide more realistic results, often in agreement with experimental data, however at significantly greater computational cost when compared to MM [ 396 ]. QM approaches can be used to not only study the binding poses but also explore the energy landscape of natural processes or drug-receptor processes [ 397 , 398 ]. QM and MM approaches are used in two main ways to study ligand–protein interactions the first of which only utilises QM to analyse a small region of interest such as the binding site, while the second method also uses QM to analyse the region of interest while using the less computationally expensive MM approach to model the remainder of the system [ 397 , 398 ].…”

“…QM approaches can be used to not only study the binding poses but also explore the energy landscape of natural processes or drug-receptor processes [ 397 , 398 ]. QM and MM approaches are used in two main ways to study ligand–protein interactions the first of which only utilises QM to analyse a small region of interest such as the binding site, while the second method also uses QM to analyse the region of interest while using the less computationally expensive MM approach to model the remainder of the system [ 397 , 398 ]. The application of pure Density Functional Theory (DFT) or ab initio work is limited due to the expensive computational cost, and as such it is limited to small systems, or for exploring derivable properties [ 399 , 400 ].…”