Optimized And Applied The Binding Free Energy Calculator Based On MM/PBSA Combined With Interaction Entropy Method

The molecular mechanics/Poisson–Boltzmann surface area(MM/PBSA)method is constantly used to calculate the binding free energy of protein–ligand complexes,and has been shown to effectively balance computational cost against accuracy.The relative binding affinities obtained by the MM/PBSA approach are acceptable,while it usually overestimates the absolute binding free energy.This paper proposes four free energy estimators based on the MM/PBSA for enthalpy change combined with interaction entropy(IE)for entropy change using different weights for individual energy terms.The?G_PBSAIE method is determined to be an optimal estimator based on its performance in terms of the correlation between experimental and theoretical values and error estimations.This approach is optimized using high-quality experimental values from a training set containing 84 protein–ligand systems,and the coefficients for the sum of electrostatic energy and polar solvation free energy,van der Waals(vd W)energy,non-polar solvation energy and entropy change are obtained by multivariate linear fitting to the corresponding experimental values.A comparison between the traditional MM/PBSA method and this method shows that the correlation coefficient is improved from 0.46to 0.72 and the slope of the regression line increases from 0.10 to 1.00.More importantly,the mean absolute error(MAE)is significantly reduced from 22.52 to 1.59 kcal/mol.Furthermore,the numerical stability of this method is validated on a test set with a similar correlation coefficient,slope and MAE to those of the training set.Based on the above advantages,the?G_PBSAIE method can be a powerful tool for a reliable and accurate estimation of binding free energy and plays a significant role in a detailed energetic investigation of protein–ligand interaction.The COVID-19 epidemic has brought a huge negative effect on human society.Unfortunately,professionals from different occupations all over the word have been fighting against it for more than a year,while there are no effective options for treatment of COVID-19 at the moment.At the end,more hopes are focused on the COIVD-19 vaccine.However,the frequent mutations of the Spike protein in the SARS-Co V-2,which is closely related to the effectiveness of the vaccine,having caused great uncertainty in the vaccine's efficacy.In the present work,we investigated three mutations of Spike proteins that have been shown to affect the infectivity of COVID-19,i.e.,R408I,N501Y,and D614G variants.The MD simulation and binding free energy calculations was applied to analyze how the mutation of Spike affect the binding mechanism between Spike protein and ACE2,which clarifies the source underlying the altered infectivity of neo-coronaviruses due to Spike mutation.Meanwhile,the interaction mechanism between the three mutation and antibody are investigated,which insights the difference in binding mode,binding free energy and interaction of hot-spot between the mutation or wild-type.This work will give the understanding of the differences in infectivity of mutant strains,prediction of the effect of vaccine effectiveness due to mutation,which helps to research and development in vaccine.