Efficient calculation of protein-ligand binding free energy using GFN methods: the power of the cluster model.

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, = 0, 1, 2) in terms of the accuracy of the calculated binding free energy. It is found that the performance of the GFN-FF method is quite good in a neutral-ligand system since the Pearson correlation coefficient () is 0.

Assessing the Performance of Screening MM/PBSA in Protein-Ligand Interactions.

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.

Interaction of serum proteins with SARS-CoV-2 RBD.

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.

Improving the Performance of MM/PBSA in Protein-Protein Interactions via the Screening Electrostatic Energy.

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.