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Protein-ligand interactions are crucial in many biochemical processes and biomedical applications, yet accurately calculating the binding free energy of the interactions still remains challenging. In this work, we systematically investigate the performance of a generic force field GFN-FF and some semi-empirical quantum mechanical (SQM) methods (GFN

Accurate calculation of protein-protein binding free energy is of great importance in biological and medical science, yet it remains a hugely challenging problem. In this work, we develop a new strategy in which a screened electrostatic energy (i.e., adding an exponential damping factor to the Coulombic interaction energy) is used within the framework of the molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) method. Our results show that the Pearson correlation coefficient in the modified MM/PBSA is over 0.70, which is much better than that in the standard MM/PBSA, especially in the Amber14SB force field. In particular, the performance of the standard MM/PBSA is very poor in a system where the proteins carry like charges. Moreover, we also calculated the mean absolute error (MAE) between the calculated and experimental ΔG values and found that the MAE in the modified MM/PBSA was indeed much smaller than that in the standard MM/PBSA. Furthermore, the effect of the dielectric constant of the proteins and the salt conditions on the results was also investigated. The present study highlights the potential power of the modified MM/PBSA for accurately predicting the binding energy in highly charged biosystems.

Accurate calculation of the binding free energies between a protein and a ligand is the primary objective of structure-based drug design, but it still remains a challenging problem. In this work, we apply the screening molecular mechanics/Poisson Boltzmann surface area (MM/PBSA) method to calculate the binding affinity of protein-ligand interactions. Our results show that the performance of the screening MM/PBSA is better than that of the standard MM/PBSA, especially in a charged-ligand system. In addition, we also investigate the effect of the solute dielectric constant on the results, and find that the optimal solute dielectric constants are different between the neutral-ligand system and the charged-ligand system. Moreover, we also evaluate the effect of the atomic-charge methods on the performance of the screening MM/PBSA. The present study demonstrates that the screening MM/PBSA should be a reliable method for calculating binding energy of biosystems.

The outbreak of the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has become a worldwide public health crisis. When the SARS-CoV-2 enters the biological fluids in the human body, different types of biomolecules (in particular proteins) may adsorb on its surface and alter its infection ability. Although great efforts have recently been devoted to the interaction of specific antibodies with the SARS-CoV-2, it still remains largely unknown how the other serum proteins affect the infection of the SARS-CoV-2. In this work, we systematically investigate the interaction of serum proteins with the SARS-CoV-2 RBD by molecular docking and all-atom molecular dynamics simulations. It is found that non-specific immunoglobulins (Ig) indeed cannot effectively bind to the SARS-CoV-2 RBD while human serum albumin (HSA) may have some potential in blocking its infection (to ACE2). More importantly, we find that the RBD can cause significant structural changes in Apolipoprotein E (ApoE), by which SARS-CoV-2 may hijack the metabolic pathway of ApoE to facilitate its cell entry. The present study enhances the understanding of the role of protein corona in the bio-behaviors of SARS-CoV-2, which may aid the more precise and personalized treatment for COVID-19 infection in the clinic.

The molecular mechanics/Poisson–Boltzmann surface area (MM/PBSA) method has been widely used in predicting the binding affinity among ligands, proteins, and nucleic acids. However, the accuracy of the predicted binding energy by the standard MM/PBSA is not always good, especially in highly charged systems. In this work, we take the protein–nucleic acid complexes as an example, and showed that the use of screening electrostatic energy (instead of Coulomb electrostatic energy) in molecular mechanics can greatly improve the performance of MM/PBSA. In particular, the Pearson correlation coefficient of dataset II in the modified MM/PBSA (i.e., screening MM/PBSA) is about 0.52, much better than that (< 0.33) in the standard MM/PBSA. Further, we also evaluate the effect of solute dielectric constant and salt concentration on the performance of the screening MM/PBSA. The present study highlights the potential power of the screening MM/PBSA for predicting the binding energy in highly charged bio-systems.

The spread of the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has become a global health crisis. The binding affinity of SARS-CoV-2 (in particular the receptor binding domain, RBD) to its receptor angiotensin converting enzyme 2 (ACE2) and the antibodies is of great importance in understanding the infectivity of COVID-19 and evaluating the candidate therapeutic for COVID-19. In this work, we propose a new method based on molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) to accurately calculate the free energy of SARS-CoV-2 RBD binding to ACE2 and antibodies. The calculated binding free energy of SARS-CoV-2 RBD to ACE2 is -13.3 kcal/mol, and that of SARS-CoV RBD to ACE2 is -11.4 kcal/mol, which agrees well with experimental result (-11.3 kcal/mol and -10.1 kcal/mol, respectively). Moreover, we take two recently reported antibodies as the example, and calculate the free energy of antibodies binding to SARS-CoV-2 RBD, which is also consistent with the experimental findings. Further, within the framework of the modified MM/PBSA, we determine the key residues and the main driving forces for the SARS-CoV-2 RBD/CB6 interaction by the computational alanine scanning method. The present study offers a computationally efficient and numerically reliable method to evaluate the free energy of SARS-CoV-2 binding to other proteins, which may stimulate the development of the therapeutics against the COVID-19 disease in real applications., 18 pages, 5 figures