Virtual Screening and In Silico Interactions Studies for Potential Antivirals and Diagnostics against the Spike protein from the Novel Coronavirus SARS-Cov-2

COVID-19 is a newly-emerged respiratory disease that is caused by the SARS-CoV-2, the seventh known Coronaviruses strain that has struck a global pandemic. The sharp increase in the number of positive cases worldwide necessitates highly-sensitive diagnostics kits and effective antiviral drugs to be developed for the populations. One of the antigens that is targeted for antibody neutralisation is the coronavirus Spike protein that consists of the S1 and S2 subunits, which mediated the entry pathway into the host’s cell. Thus, the Spike protein has been suggested as a potential target for Covid-19 diagnostics and drug design. This study aims to evaluate the interactions between the SARS-CoV-2 Spike protein and the known monoclonal antibodies from Coronaviruses and to screen for potential Spike protein inhibitors. Virtual screening was conducted based on two compounds, N‐acetyl‐D‐glucosamine (NAG) and Hesperetin, which is a small molecule that binds to the SARS-CoV-2 Spike protein structure and a natural compound that has prophylactic agents against SARS-CoV-2 infection as it binds to Spike protein, respectively. Protein-protein interaction studies were conducted by using the STRING webserver, prior to performing rigid docking using SWISSDOCK and visualised using USCF Chimera. Meanwhile, ligand-based screening was conducted through Ultrafast Shape Recognition Virtual Screening Database (USR-VS), and structure-based screening was performed via AutoDock4 software. The toxicity of the compounds was predicted using ProTox-II database. Possible interactions have been observed between the known monoclonal antibodies with the SARS-CoV-2 Spike protein, where M396 monoclonal antibody has shown the strongest interaction with a binding energy of -8.50 kcal/mol. Meanwhile, virtual screening has yielded several compounds that indicate the possibility to inhibit the SARS-CoV-2 Spike protein, where Tamarixetin has shown the strongest binding energy of -7.93 kcal/mol. These findings have potentials to be further evaluated in the future for the development of improved diagnostic kits and potential therapeutic drugs that specifically target the Spike protein of SARS-CoV-2.

The Mechanical Basis of Memory – the MeshCODE Theory

One of the major unsolved mysteries of biological science concerns the question of where and in what form information is stored in the brain. I propose that memory is stored in the brain in a mechanically encoded binary format written into the conformations of proteins found in the cell-extracellular matrix (ECM) adhesions that organise each and every synapse. The MeshCODE framework outlined here represents a unifying theory of data storage in animals, providing read-write storage of both dynamic and persistent information in a binary format. Mechanosensitive proteins that contain force-dependent switches can store information persistently, which can be written or updated using small changes in mechanical force. These mechanosensitive proteins, such as talin, scaffold each synapse, creating a meshwork of switches that together form a code, the so-called MeshCODE. Large signalling complexes assemble on these scaffolds as a function of the switch patterns and these complexes would both stabilise the patterns and coordinate synaptic regulators to dynamically tune synaptic activity. Synaptic transmission and action potential spike trains would operate the cytoskeletal machinery to write and update the synaptic MeshCODEs, thereby propagating this coding throughout the organism. Based on established biophysical principles, such a mechanical basis for memory would provide a physical location for data storage in the brain, with the binary patterns, encoded in the information-storing mechanosensitive molecules in the synaptic scaffolds, and the complexes that form on them, representing the physical location of engrams. Furthermore, the conversion and storage of sensory and temporal inputs into a binary format would constitute an addressable read-write memory system, supporting the view of the mind as an organic supercomputer.

The Mechanical Basis of Memory - the MeshCODE Theory

One of the major unsolved mysteries of biological science concerns the question of where and in what form information is stored in the brain. I propose that memory is stored in the brain in a mechanically encoded binary format written into the conformations of proteins found in the cell-extracellular matrix adhesions that organise each and every synapse. The MeshCODE framework outlined here represents a unifying theory of data storage in animals, providing read-write storage of both dynamic and persistent information in a binary format. Mechanosensitive proteins that contain force-dependent switches can store information persistently, which can be written or updated using small changes in mechanical force. These mechanosensitive proteins, such as talin, scaffold each synapse, creating a meshwork of switches that together form a code, the so-called MeshCODE. Large signalling complexes assemble on these scaffolds as a function of the switch patterns and these complexes would both stabilise the patterns and coordinate synaptic regulators to dynamically tune synaptic activity. Synaptic transmission and action potential spike trains would operate the cytoskeletal machinery to write and update the synaptic MeshCODEs, thereby propagating this coding throughout the organism. Based on established biophysical principles, such a mechanical basis for memory would provide a physical location for data storage in the brain, with the binary patterns, encoded in the information-storing mechanosensitive molecules in the synaptic scaffolds, and the complexes that form on them, representing the physical location of engrams. Furthermore, the conversion and storage of sensory and temporal inputs into a binary format would constitute an addressable read-write memory system, supporting the view of the mind as an organic supercomputer.

Protonic conductor: better understanding neural resting and action potential

The newly formulated action potential equation provides biophysical insights for neuron electrophysiology, which may represent a complementary development to the classic Goldman–Hodgkin–Katz equation. The nonlinear curve of the localized protons/cations charge density in the real-time domain of an action potential spike appears as an inverse mirror image to the action potential. The biological significance of axon myelination is now elucidated as to provide protonic insulation and prevent any ions from interfering with action potential signal.

Simulating Notch-Dome Morphology of Action Potential of Ventricular Cell: How the Speeds of Positive and Negative Feedbacks on Transmembrane Voltage Can Influence the Health of a Cell?

Ventricular action potential is well-known because of its plateau phase with a spike-notch-dome morphology. As such, the morphology of action potential is necessary for ensuring a correct heart functioning. Any distraction from normal notch-dome morphology may trigger a circus movement reentry in the form of lethal ventricular fibrillation. When the epicardial action potential dome propagates from a site where it is maintained to regions where it has been lost, it gives rise to the proposed mechanism for the Brugada syndrome. Despite the impact of notch-dome dynamics on the heart function, no independent and explicit research has been performed on the simulation of notch-dome dynamics and morphology. In this paper, using a novel mathematical approach, a three-state variable model is proposed; we show that our proposed model not only can simulate morphology of action potential of ventricular cells but also can propose a biological reasonable tool for controlling of the morphology of action potential spike-notch-dome. We show that the processes of activation and inactivation of ionic gating variables (as positive or negative feedbacks on the voltage of cell membrane) and the ratio of their speeds (time constants) can be treated as a reasonable biological tool for simulating ventricular cell notch-dome. This finding may led to a new insight to the quantification of the health of a ventricular cell and may also propose a new drug therapy strategy for cardiac diseases.

The Mechanical Basis of Memory - the MeshCODE Theory

The MeshCODE framework outlined here represents a unifying theory of data storage in animals, providing read/write storage of both dynamic and persistent information in a binary format. Mechanosensitive proteins, that contain force-dependent switches, can store information persistently which can be written/updated using small changes in mechanical force. These mechanosensitive proteins, such as talin, scaffold each and every synapse creating a meshwork of switches that forms a code, a MeshCODE. Synaptic transmission and action potential spike trains would operate the cytoskeletal machinery to write and update the synaptic MeshCODEs, propagating this coding throughout the brain and to the entire organism. Based on established biophysical principles, a mechanical basis for memory provides a physical location for data storage in the brain. Furthermore, the conversion and storage of sensory and temporal inputs into a binary format identifies an addressable read/write memory system supporting the view of the mind as an organic supercomputer.

In Silico Screening of Potential Spike Glycoprotein Inhibitors of SARS-CoV-2 with Drug Repurposing Strategy

COVID-19 has globally spread and has become a new pandemic, but there are still no effective drugs or vaccines to treat or prevent this disease. SARS-CoV-2 invades human cells through its spike proteins interacting with human ACE2 receptors, which may cause severe respiratory syndrome. One strategy to prevent the virus from entering cells is the interruption of the viral spike protein interacting with human ACE2. Facing such an urgent situation, drug repurposing is a promising strategy for rapid drug development. Here, we selected approximately 15000 molecular candidates, including FDA-approved drugs from DrugBank and natural compounds from TCMSP, to perform virtual screening for potential molecules that can target viral spike proteins, which may potentially interrupt the interaction between the human ACE2 receptor and viral spike protein. We found that digitoxin, a cardiac glycoside in DrugBank and bisindigotin, which is extracted from indigo naturalis and polygoni tinctorii foliu, in TCMSP had the highest docking scores. Note that indigo naturalis and the other herbs we found have been applied to prevent infectious diseases in traditional Chinese medicine. We also found that raltegravir, an HIV integrase inhibitor, has a relatively high binding affinity. All the docking results are presented in this article. Based on these docking results, further work will continue to identify potential molecules to prevent the spike protein from binding with the ACE2 receptor.Authors Tianzi Wei and Hao Wang contributed equally to this work.

in silico Screening of Potential Spike Glycoprotein Inhibitors of SARS-CoV-2 with Drug Repurposing Strategy

COVID-19 has globally spread and has become a new pandemic, but there is still no effective drugs or vaccines to treat or prevent this disease. SARS-Cov-2 invades human cells through its spike proteins interacting with human ACE2 receptors. One strategy to prevent the virus from entering cells is the interruption of the viral spike protein interacting with ACE2. In such an emergent situation, drug repurposing is a promising method for rapid drug development. Here, we selected around 15000 molecular candidates including FDA-approved drugs from DrugBank and natural compounds from TCMSP to perform virtual screening for potential molecules that can target viral spike protein based on its crystal structure. In this article, we present the top 20 molecules with high binding affinity with spike protein, of which, digitoxin, a cardiac glycoside in DrugBank and bisindigotin in TCMSP, extracted from indigo naturalis and polygoni tinctorii foliu, have the highest docking scores. In addition, we also found that raltegravir, an HIV integrase inhibitor, has a relatively high binding score. Those molecules with high binding capacity to spike glycoprotein might be used by other researchers for further anti-COVID-19 drug development.