In Silico Methodology for Human Carboxylesterases 1 and 2 Isoforms Substrate Selectivity Study

Area of Science:

• Biochemistry and Medicinal Chemistry
• Computational Chemistry and Molecular Modeling

Background:

• Human carboxylesterases (CES), specifically CES1 and CES2, are key enzymes in drug hydrolysis.
• Understanding CES isoform substrate specificity is vital for drug development, but exceptions to general rules exist.

Purpose of the Study:

• To elucidate the substrate selectivity of CES1 and CES2 using computational simulations.
• To support experimental enzymatic assays by providing mechanistic insights.

Main Methods:

• Utilized stepwise methodologies combining classical molecular mechanics (MM) and hybrid quantum mechanics/molecular mechanics (QM/MM) simulations.
• Employed MM strategies including molecular docking, molecular dynamic simulations (MD), and free-energy analyses to assess binding affinity (KM).
• Applied QM/MM-MD simulations to model hydrolytic reaction coordinates and enzymatic turnover rates (kcat).

Main Results:

• Computational methods were applied to investigate CES1 and CES2 substrate selectivity.
• MM simulations assessed substrate binding affinity (KM).
• QM/MM-MD simulations modeled the enzymatic hydrolysis mechanism and turnover rate (kcat).

Conclusions:

• The study demonstrates the utility of combined MM and QM/MM simulations in elucidating CES enzyme substrate specificity.
• These computational approaches provide valuable insights to complement experimental data in medicinal chemistry.
• This work aids in understanding and predicting drug metabolism by CES isoforms.