Computational Design of Miniprotein Inhibitors Targeting SARS-CoV-2 Spike Protein

Effect of quercetin on the protein-substrate interactions in SIRT6: Insight from MD simulations

SIRT6 is of interest for its promising effect in the treatment of aging-related diseases. Studies have shown quercetin (QUE) and its derivatives have varying degrees of effect on the catalytic effect of SIRT6. In the research, the effect of QUE on the protein-substrate interaction in the SIRT6-mediated mono-ADP ribosylation system was investigated by conventional molecular dynamics (MD) simulations combined with MM/PBSA binding free energy calculations. The results show that QUE can bind stably to SIRT6 with the binding energy of -22.8 kcal/mol and further affect the atomic interaction between SIRT6 and NAD+ (or H3K9), resulting in an increased affinity between SIRT6-NAD+ and decreased SIRT6-H3K9 binding capacity. At the same time, the binding of QUE can also alter some structural characteristics of the protein, with large shifts occurring in the residue regions involving the N-terminal (residues 1-27), Rossmann fold regions (residues 55-92), and ZBD (residues 164-179). Thus, QUE shows great potential as a scaffold for the design of novel potent SIRT6 modulators.

4D-QSAR, ADMET properties, and molecular dynamics simulations for designing N-substituted urea/thioureas as human glutaminyl cyclase inhibitors

Human glutaminyl cyclase (hQC) inhibitors have great potential to be used as anti- Alzheimer's disease (AD) agents by reducing the toxic pyroform of β-amyloid in the brains of AD patients. The four-dimensional quantitative structure activity relationship (4D-QSAR) model of N-substituted urea/thioureas was established with satisfying predictive ability and statistical reliability (Q2 = 0.521, R2 = 0.933, R2prep = 0.619). By utilizing the developed 4D-QSAR model, a set of new N-substituted urea/thioureas was designed and evaluated for their Absorption Distribution Metabolism Excretion and Toxicity (ADMET) properties. The results of molecular dynamics (MD) simulations, Principal component analysis (PCA), free energy landscape (FEL), dynamic cross-correlation matrix (DCCM) and molecular mechanics generalized Born Poisson-Boltzmann surface area (MM-PBSA) free energy calculations, revealed that the designed compounds were remained stable in protein binding pocket and compounds b ∼ f (-35.1 to -44.55 kcal/mol) showed higher binding free energy than that of compound 14 (-33.51 kcal/mol). The findings of this work will be a theoretical foundation for further research and experimental validation of urea/thiourea derivatives as hQC inhibitors.

Discovery of small molecule entry inhibitors targeting the linoleic acid binding pocket of SARS-CoV-2 spike protein

Spike glycoprotein has a significant role in the entry of SARS-CoV-2 to host cells, which makes it a potential drug target. Continued accumulation of non-synonymous mutations in the receptor binding domain of spike protein poses great challenges in identifying antiviral drugs targeting this protein. This study aims to identify potential entry inhibitors of SARS-CoV-2 using virtual screening and molecular dynamics (MD) simulations from three distinct chemical libraries including Pandemic Response Box, Drugbank and DrugCentral, comprising 6971 small molecules. The molecules were screened against a binding pocket identified in the receptor-binding domain (RBD) region of the spike protein which is known as the linoleic acid binding pocket, a highly conserved motif among several SARS-CoV-2 variants. Through virtual screening and binding free energy calculations, we identified four top-scoring compounds, MMV1579787 ([2-Oxo-2-[2-(3-phenoxyphenyl)ethylamino]ethyl]phosphonic acid), Tretinoin, MMV1633963 ((2E,4E)-5-[3-(3,5-dichlorophenoxy)phenyl]penta-2,4-dienoic acid) and Polydatin, which were previously reported to have antibacterial, antifungal or antiviral properties. These molecules showed stable binding on MD simulations over 100 ns and maintained stable interactions with TYR365, PHE338, PHE342, PHE377, TYR369, PHE374 and LEU368 of the spike protein RBD that are found to be conserved among SARS-CoV-2 variants. Our findings were further validated with free energy landscape, principal component analysis and dynamic cross-correlation analysis. Our in silico analysis of binding mode and MD simulation analyses suggest that the identified compounds may impede viral entrance by interacting with the linoleic acid binding site of the spike protein of SARS-CoV-2 regardless of its variants, and they thus demand for further in vitro and in vivo research.Communicated by Ramaswamy H. Sarma.

Exploring the disruption of SARS-CoV-2 RBD binding to hACE2

The COVID-19 pandemic was declared due to the spread of the novel coronavirus, SARS-CoV-2. Viral infection is caused by the interaction between the SARS-CoV-2 receptor binding domain (RBD) and the human ACE2 receptor (hACE2). Previous computational studies have identified repurposed small molecules that target the RBD, but very few have screened drugs in the RBD-hACE2 interface. When studies focus solely on the binding affinity between the drug and the RBD, they ignore the effect of hACE2, resulting in an incomplete analysis. We screened ACE inhibitors and previously identified SARS-CoV-2 inhibitors for binding to the RBD-hACE2 interface, and then conducted 500 ns of unrestrained molecular dynamics (MD) simulations of fosinopril, fosinoprilat, lisinopril, emodin, diquafosol, and physcion bound to the interface to assess the binding characteristics of these ligands. Based on MM-GBSA analysis, all six ligands bind favorably in the interface and inhibit the RBD-hACE2 interaction. However, when we repeat our simulation by first binding the drug to the RBD before interacting with hACE2, we find that fosinopril, fosinoprilat, and lisinopril result in a strongly interacting trimeric complex (RBD-drug-hACE2). Hydrogen bonding and pairwise decomposition analyses further suggest that fosinopril is the best RBD inhibitor. However, when lisinopril is bound, it stabilizes the trimeric complex and, therefore, is not an ideal potential drug candidate. Overall, these results reveal important atomistic interactions critical to the binding of the RBD to hACE2 and highlight the significance of including all protein partners in the evaluation of a potential drug candidate.

The molecular mechanism of non-covalent inhibitor WU-04 targeting SARS-CoV-2 3CLpro and computational evaluation of its effectiveness against mainstream coronaviruses

There is an urgent need for highly effective therapeutic agents to interrupt the continued spread of SARS-CoV-2. As a pivotal protease in the replication process of coronaviruses, the 3CLpro protein is considered as a potential target of drug development to stop the spread and infection of the virus. In this work, molecular dynamics (MD) simulations were used to elucidate the molecular mechanism of a novel and highly effective non-covalent inhibitor, WU-04, targeting the SARS-CoV-2 3CLpro protein. The difference in dynamic behavior between the apo-3CLpro and the holo-3CLpro systems suggests that the presence of WU-04 inhibits the motion amplitude of the 3CLpro protein relative to the apo-3CLpro system, thus maintaining a stable conformational binding state. The energy calculations and interaction analysis show that the hot-spot residues Q189, M165, M49, E166, and H41 and the warm-spot residues H163 and C145 have a strong binding capacity to WU-04 by forming multiple hydrogen bonds and hydrophobic interactions, which stabilizes the binding of the inhibitor. After that, the resistance of WU-04 to the six SARS-CoV-2 variants (Alpha, Beta, Gamma, Delta, Lambda, and Omicron) and two other mainstream coronavirus (SARS-CoV and MERS-CoV) 3CLpro proteins was further investigated. Excitingly, the slight difference in energy values relative to the SARS-CoV-2 system indicates that WU-04 is still highly effective against the coronaviruses, which becomes crucial evidence that WU-04 is a pan-inhibitor of the 3CLpro protein in various SARS-CoV-2 variants and other mainstream coronaviruses. The study will hopefully provide theoretical insights for the future rational design and improvement of novel non-covalent inhibitors targeting the 3CLpro protein.

Computational Protein Design for COVID-19 Research and Emerging Therapeutics

As the world struggles with the ongoing COVID-19 pandemic, unprecedented obstacles have continuously been traversed as new SARS-CoV-2 variants continually emerge. Infectious disease outbreaks are unavoidable, but the knowledge gained from the successes and failures will help create a robust health management system to deal with such pandemics. Previously, scientists required years to develop diagnostics, therapeutics, or vaccines; however, we have seen that, with the rapid deployment of high-throughput technologies and unprecedented scientific collaboration worldwide, breakthrough discoveries can be accelerated and insights broadened. Computational protein design (CPD) is a game-changing new technology that has provided alternative therapeutic strategies for pandemic management. In addition to the development of peptide-based inhibitors, miniprotein binders, decoys, biosensors, nanobodies, and monoclonal antibodies, CPD has also been used to redesign native SARS-CoV-2 proteins and human ACE2 receptors. We discuss how novel CPD strategies have been exploited to develop rationally designed and robust COVID-19 treatment strategies.

Investigation on the interaction mechanism of different SARS-CoV-2 spike variants with hACE2: insights from molecular dynamics simulations

Since the COVID-19 pandemic caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), SARS-CoV-2 has evolved by acquiring genomic mutations, resulting in the recent emergence of several SARS-CoV-2 variants with improved transmissibility and infectivity relative to the original strain. An underlying mechanism may be the increased ability of the mutants to bind the receptor proteins and infect the host cell. In this work, we implemented all-atom molecular dynamics (MD) simulations to study the binding and interaction of the receptor binding domain (RBD) of the SARS-CoV-2 spike protein singly (D614G), doubly (D614G + L452R and D614G + N501Y), triply (D614G + N501Y + E484K), and quadruply (D614G + N501Y + E484K + K417T) mutated variants with the human angiotensin-converting enzyme 2 (hACE2) receptor protein in the host cell. A combination of multiple analysis approaches elucidated the effects of mutations and the extent of molecular divergence from multiple perspectives, including the dynamic correlated motions, interaction patterns, dominant motions, free energy landscape, and charge distribution on the electrostatic potential surface between the hACE2 and all RBD variants. Moreover, free energy calculations using the MM/PBSA method evaluated the binding affinity between these RBD variants and hACE2. The results showed that the D614G + N501Y + E484K variant possessed the lowest free energy value (highest affinity) compared to the D614G + N501Y + E484K + K417T, D614G + L452R, D614G + N501Y, and D614G mutants. The residue-based energy decomposition also indicated that the energy contribution of residues at the mutation site to the total binding energy was highly variable. The interaction mechanisms between the different RBD variants and hACE2 elucidated in this study will provide some insights into the development of drugs targeting the new SARS-CoV-2 variants.