Gabr.org (Мед2000.ру)

English edition

Text from the Theories section.
Truth is not affirmed here.
Theories are an invitation to reflection.

Big data and virology.

Creation of new anti-viral medicines.

In order to cause an infectious disease, a virus needs to enter a human cell. He does this by forming a bond between the proteins of his (viral) capsid (membrane) and receptors on the cell surface.

The virus obtains this opportunity through mutations. The most striking example of such evolution is the COVID-19 epidemic, when the SARS-CoV-2 coronavirus, which bats have used for its reproduction for many millennia, acquired a mutation that allowed it to bind to ACE2 receptors on the surface of human cells.

In order to create an effective antiviral drug, you need to understand that the combination of proteins of viruses with a receptor has a number of features and even disadvantages.

The fact is that the perception of the classical "key-lock" scheme for combining antigen and antibody, neurotransmitter and receptor, viral proteins and cell receptors has a significant simplification. Counterparties (neurotransmitters, antigens) attach to the same receptor, to the same antibody with different strengths. Those, if we follow the analogy of a key-lock, then in addition to a real, ideally suitable key, several more worse keys can be suitable for the same lock, in fact - picklock.

Viral proteins, unlike human proteins, are more like picklock than keys. Their connection is less strong. The virus does not need to start any processes in the human body - it only needs to enter the cell.

However, human proteins don't bind perfectly to the receptor either. They bind enough to compete with other proteins for this receptor.
This suggests that it is possible to artificially develop and synthesize a receptor that will bind the virus capsid proteins much more strongly than the receptors of a human cell.

A drug containing such an artificial receptor will compete with the cell receptors for the viral capsid proteins. The artificial receptor will bind to the virus more tightly than the cell's receptor and take on a significant portion of the viral load, preventing the virus from infecting cells.

It is quite difficult to develop such an artificial receptor empirically. And here big data and artificial intelligence can come to the aid of scientists, which will allow them to model the most suitable receptor for the proteins of the viral capsid.

As a result of this simulation, it is possible to obtain a formula of the required substance, which will interact more actively with the virus than the cell of the body. This, in turn, will lead either to blocking the virus, or to its activation "into the void" - self-destruction of the capsid, if the artificial receptor can trigger the beginning of the release of the virus genome into the extracellular space, which in turn will lead to inactivation of the virus and the impossibility of further reproduction.

Basically, the simulation will create a false receptor that tricks the virus, preventing it from infecting the body's cells and dramatically reducing viral load.

The resulting formula will become a starting point for the chemical synthesis of an artificial receptor, after which it will be possible to test the effect of the antiviral action of artificial receptors in laboratory and clinical trials. If the effect is confirmed, it will be possible to create a wide range of new generation anti-viral medicines.

Doctor Andrey Sokolov (2336694@gmail.com)