High-Throughput Molecular Dynamics-Based Alchemical Free Energy Calculations for Predicting the Binding Free Energy Change Associated with the Selected Omicron Mutations in the Spike Receptor-Binding Domain of SARS-CoV-2

Abstract

The ongoing pandemic caused by SARS-CoV-2 has gone through various phases. Since the initial outbreak, the virus has mutated several times, with some lineages showing even stronger infectivity and faster spread than the original virus. Among all the variants, omicron is currently classified as a variant of concern (VOC) by the World Health Organization, as the previously circulating variants have been replaced by it. In this work, we have focused on the mutations observed in omicron sub lineages BA.1, BA.2, BA.4 and BA.5, particularly at the receptor-binding domain (RBD) of the spike protein that is responsible for the interactions with the host ACE2 receptor and binding of antibodies. Studying such mutations is particularly important for understanding the viral infectivity, spread of the disease and for tracking the escape routes of this virus from antibodies. Molecular dynamics (MD) based alchemical free energy calculations have been shown to be very accurate in predicting the free energy change, due to a mutation that could have a deleterious or a stabilizing effect on either the protein itself or its binding affinity to another protein. Here, we investigated the significance of five spike RBD mutations on the stability of the spike protein binding to ACE2 by free energy calculations using high throughput MD simulations. For comparison, we also used conventional MD simulations combined with a Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) based approach, and compared our results with the available experimental data. Overall, the alchemical free energy calculations performed far better than the MM-GBSA approach in predicting the individual impact of the mutations. When considering the experimental variation, the alchemical free energy method was able to produce a relatively accurate prediction for N501Y, the mutant that has previously been reported to increase the binding affinity to hACE2. On the other hand, the other individual mutations seem not to have a significant effect on the spike RBD binding affinity towards hACE2.

Development and Evaluation of Novel Encapsulated Isoeugenol-Liposomal Gel Carrier System for Methicillin-Resistant Staphylococcus aureus

“…Using Desmond 6.1 molecular dynamics (MD) simulation computations, the thermodynamic behavior and stability of the best-ranked conformation of isoeugenol in a complex with penicillin-binding protein 2a were studied [ 43 , 44 ]. The isoeugenol-protein complex was placed inside an orthorhombic box with 10 buffer regions between protein atoms and box sides and filled with 30,294 molecules of water.…”

Bioinformatics insights into CENP‐T and CENP‐W protein‐protein interaction disruptive amino acid substitution in the CENP‐T‐W complex

“…The binding free energy of the WT and mutant protein‐protein complex was determined from the trajectory file obtained after 250 ns long MD simulation using prime MM‐GBSA approach employing the VSGB2.1 implicit solvation model and the OPLS4 force field to calculate the binding free energy 26–28 . The binding free energy () was computed using the previously established equation described in our protocol 29 : where is the free energy of the CENP‐T‐W complex, is the free energy of the CENP‐T and is the free energy of the CENP‐W protein. ∆G bind is calculated for each mutated CENP‐W in this way.…”

“…The binding free energy of the WT and mutant protein-protein complex was determined from the trajectory file obtained after 250 ns long MD simulation using prime MM-GBSA approach employing the VSGB2.1 implicit solvation model and the OPLS4 force field to calculate the binding free energy. [26][27][28] The binding free energy ( G bind ∆ ) was computed using the previously established equation described in our protocol 29 :…”