Computational Modeling of Solvent Effects on Protein-Ligand Interactions Using Fully Polarizable Continuum Model and Rational Drug Design

Abstract

This is a brief review of the computational modeling of protein-ligand interactions using a recently developed fully polarizable continuum model (FPCM) and rational drug design. Computational modeling has become a powerful tool in understanding detailed protein-ligand interactions at molecular level and in rational drug design. To study the binding of a protein with multiple molecular species of a ligand, one must accurately determine both the relative free energies of all of the molecular species in solution and the corresponding microscopic binding free energies for all of the molecular species binding with the protein. In this paper, we aim to provide a brief overview of the recent development in computational modeling of the solvent effects on the detailed protein-ligand interactions involving multiple molecular species of a ligand related to rational drug design. In particular, we first briefly discuss the main challenges in computational modeling of the detailed protein-ligand interactions involving the multiple molecular species and then focus on the FPCM model and its applications. The FPCM method allows accurate determination of the solvent effects in the first-principles quantum mechanism (QM) calculations on molecules in solution. The combined use of the FPCM-based QM calculations and other computational modeling and simulations enables us to accurately account for a protein binding with multiple molecular species of a ligand in solution. Based on the computational modeling of the detailed protein-ligand interactions, possible new drugs may be designed rationally as either small-molecule ligands of the protein or engineered proteins that bind/metabolize the ligand. The computational drug design has successfully led to discovery and development of promising drugs.

Reaction pathways and free energy profiles for spontaneous hydrolysis of urea and tetramethylurea: unexpected substituent effects

“…The SVPE method is also known as the fully polarizable continuum model (FPCM), 23–24, 29–35 as it fully accounts for both surface and volume polarization effects in solute-solvent electrostatic interactions. 36–37 In the SVPE procedure, 27–28, 38 the solute cavity surface is defined as a solute electron-charge isodensity contour determined self-consistently during the SVPE interaction process, and the SVPE results converge to the exact solution of the Poisson’s equation with a given numerical tolerance. The converged SVPE results merely rely on the contour value at a given dielectric constant and a certain quantum mechanical calculation level.…”

Reaction pathway and free energy barrier for urea elimination in aqueous solution

“…The IPCM model implemented in the Gaussian program only accounts for surface polarization and completely ignores volume polarization [15,16]. It has been demonstrated that volume polarization significantly affects molecular structures [17–20], properties [21–23] and reactivity [24–27]. Hence, volume polarization must be accounted for in computational determination of solvent effects on the free energy barrier.…”

“…The SVPE method is also known as the fully polarizable continuum model (FPCM) [17,19–23,28,29], as it fully accounts for both surface and volume polarization effects in solute-solvent electrostatic interactions [24,30]. …”

Modeling in vitro inhibition of butyrylcholinesterase using molecular docking, multi-linear regression and artificial neural network approaches

“…the ESP charges, that fit to the electrostatic potential at points selected according to the Merz-Singh-Kollman scheme. 38b In addition, the single-point energy calculations were also carried out by using the surface and volume polarization for electrostatics (SVPE) 39–43 calculations at the HF/6–31G* level, which accounts for solvent effects on such molecular descriptors as the dipole moment and HOMO/LUMO energies.…”