Abstract
An efficient computational approach for modeling protein electrostatic is developed according to static point-charge model distributions based on the linear-scaling EE-GMFCC (electrostatically embedded generalized molecular fractionation with conjugate caps) quantum mechanical (QM) method. In this approach, the Electrostatic-Potential atomic charges are obtained from ab initio calculation of protein, both polarization and charge transfer effect are taken into consideration. This approach shows a significant improvement in the description of electrostatic potential and solvation energy of proteins comparing with current popular molecular mechanics (MM) force fields. Therefore, it has gorgeous prospect in many applications, including accurate calculations of electric field or vibrational Stark spectroscopy in proteins and predicting protein-ligand binding affinity. It can also be applied in QM/MM calculations or electronic embedding method of ONIOM to provide a better electrostatic environment.
Highlights
Electrostatic interaction plays a central role in many molecular processes in biological molecules[1,2,3,4,5], including protein folding[6], protein-ligand binding[7,8], protein-protein interaction[9], electron transfer[10], enzyme reaction[11,12], ion channels[13,14], etc
This originates from the fact that the point-charge model of standard force fields is mean-field-like and it does not contain protein-specific quantum mechanical information such as polarization effect, charge transfer effect, etc
We developed a charge model termed EE-GMFCC-CHG for accurately modeling the molecular electrostatic potential of proteins
Summary
Electrostatic interaction plays a central role in many molecular processes in biological molecules[1,2,3,4,5], including protein folding[6], protein-ligand binding[7,8], protein-protein interaction[9], electron transfer[10], enzyme reaction[11,12], ion channels[13,14], etc. The electron-density distribution of each amino acid in a particular protein electrostatic environment is specific due to polarization and charge transfer effect. The fragmentation approach is on the basis of the “chemical locality” of most large molecular systems, which assumes that the local region of the large system is only weakly influenced by the atoms that are far away from this region Based on this chemical intuition, the system is divided into many individual subsystems (fragments) and subsequently the properties of the whole system can be obtained by taking a linear combination of the properties of these fragments. With the goal of obtaining more accurate electronic structure properties of proteins, we have proposed a linear-scaling QM method termed EE-GMFCC (electrostatically embedded generalized molecular fractionation with conjugate caps method)[55]. The applications of the EE-GMFCC method have been extended to perform structural optimization of proteins[56] and molecular dynamics simulations with high level ab initio electronic structure theories[57]
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