Interfacial Water Molecules Make RBD of SPIKE Protein and Human ACE2 to Stick Together

A novel coronavirus (SARS-CoV-2; COVID-19) that initially originates from Wuhan province in China has emerged as a global pandemic, an outbreak that started at the end of 2019 which claims 431,192 (Date: 15th June 2020 (https://covid19.who.in) life till now. Since then scientists all over the world are engaged in developing new vaccines, antibodies, or drug molecules to combat this new threat. Here in this work, we performed an in-silico analysis on the protein-protein interactions between the receptor-binding (RBD) domain of viral SPIKE protein and human angiotensin-converting enzyme 2 (hACE2) receptor to highlight the key alteration that happened from SARS-CoV to SARS-CoV-2. We analyzed and compared the molecular differences between these two viruses by using various computational approaches such as binding affinity calculations, computational alanine, and molecular dynamics simulations. The binding affinity calculations show SARS-CoV-2 binds little more firmly to the hACE2 receptor than that of SARS-CoV. Analysis of simulation trajectories reveals that enhanced hydrophobic contacts or the van der Waals interaction play a major role in stabilizing the protein-protein interface. The major finding obtained from molecular dynamics simulations is that the RBD-ACE2 interface is populated with water molecules and interacts strongly with both RBD and ACE2 interfacial residues during the simulation periods. We also emphasize that the interfacial water molecules play a critical role in binding and maintaining the stability of the RBD/hACE2 complex. The water-mediated hydrogen bond by the bridge water molecules is crucial for stabilizing the RBD and ACE2 domains. The structural and dynamical features presented here may serve as a guide for developing new drug molecules, vaccines, or antibodies to combat the COVID-19 pandemic.

Repurposing of FDA-Approved Toremifene to Treat COVID-19 by Blocking the Spike Glycoprotein and NSP14 of SARS-CoV-2

The global pandemic of Coronavirus Disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to the death of more than 350,000 worldwide and over 100,000 in the United States alone. However, there are currently no proven effective pharmacotherapies for COVID-19. Here, we combine homology modeling, molecular docking, molecular dynamics simulation, and binding affinity calculations to determine potential targets for toremifene, a selective estrogen receptor modulator which we have previously identified as a SARS-CoV-2 inhibitor. Our results indicate the possibility of inhibition of the spike glycoprotein by toremifene, responsible for aiding in fusion of the viral membrane with the cell membrane, via a perturbation to the fusion core. An interaction between the dimethylamine end of toremifene and residues Q954 and N955 in heptad repeat 1 (HR1) perturbs the structure, causing a shift from what is normally a long, helical region to short helices connected by unstructured regions. Additionally, we found a strong interaction between toremifene and the methyltransferase non-structural protein (NSP) 14, which could be inhibitory to viral replication via its active site. These results suggest potential structural mechanisms for toremifene by blocking the spike protein and NSP14 of SARS-CoV-2, offering a drug candidate for COVID-19.

Repurposing of FDA-Approved Toremifene to Treat COVID-19 by Blocking the Spike Glycoprotein and NSP14 of SARS-CoV-2

The global pandemic of Coronavirus Disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to the death of more than 350,000 worldwide and over 100,000 in the United States alone. However, there are currently no proven effective pharmacotherapies for COVID-19. Here, we combine homology modeling, molecular docking, molecular dynamics simulation, and binding affinity calculations to determine potential targets for toremifene, a selective estrogen receptor modulator which we have previously identified as a SARS-CoV-2 inhibitor. Our results indicate the possibility of inhibition of the spike glycoprotein by toremifene, responsible for aiding in fusion of the viral membrane with the cell membrane, via a perturbation to the fusion core. An interaction between the dimethylamine end of toremifene and residues Q954 and N955 in heptad repeat 1 (HR1) perturbs the structure, causing a shift from what is normally a long, helical region to short helices connected by unstructured regions. Additionally, we found a strong interaction between toremifene and the methyltransferase non-structural protein (NSP) 14, which could be inhibitory to viral replication via its active site. These results suggest potential structural mechanisms for toremifene by blocking the spike protein and NSP14 of SARS-CoV-2, offering a drug candidate for COVID-19.

Large scale relative protein ligand binding affinities using non-equilibrium alchemy

Relative ligand binding affinity calculations based on molecular dynamics (MD) simulations and non-physical (alchemical) thermodynamic cycles have shown great promise for structure-based drug design.

Efficient large-scale replica-exchange simulations on production infrastructure

Replica-exchange (RE) algorithms are used to understand physical phenomena—ranging from protein folding dynamics to binding affinity calculations. They represent a class of algorithms that involve a large number of loosely coupled ensembles, and are thus amenable to using distributed resources. We develop a framework for RE that supports different replica pairing (synchronous versus asynchronous) and exchange coordination mechanisms (centralized versus decentralized) and which can use a range of production cyberinfrastructures concurrently. We characterize the performance of both RE algorithms at an unprecedented number of cores employed—the number of replicas and the typical number of cores per replica—on the production distributed infrastructure. We find that the asynchronous algorithms outperform the synchronous algorithms, even though details of the specific implementations are important determinants of performance.

THEORETICAL STUDY ON POTENCY AND SELECTIVITY OF NOVEL NONPEPTIDE INHIBITORS OF MATRIX METALLOPROTEINASES MMP-2 AND MMP-9

Two novel matrix metalloproteinase (MMP) inhibitors, myricetin (m) and kaempferol (k), were found and the inhibitory activity is both in decreased order towards MMP-2 and MMP-9. To understand the mechanism during the processes when inhibitors bind to MMP-2 and MMP-9, molecular modeling, docking, and density functional theory (DFT) calculations were performed. The calculated results indicated that the hydroxyls on benzene ring of the inhibitors control the binding modes between inhibitors and MMPs, thus play an important role on the potency and selectivity. Besides coordinating with the N atoms of three His residues, Zn also interacts with a hydroxyl group of inhibitors by O – Zn distances of 2.66–2.78 Å in all of the docked complexes, so that the hydroxyl acts as a weak zinc binding group (ZBG). The DFT calculated results support the above analysis. The binding affinity calculations between inhibitors and MMPs present the total interaction energies in the m-MMP < k-MMP order and the solvation energy of myricetin is less than that of kaempferol, which reflect the experimental inhibitory activity.