Issue: It can take four to seven years to develop and test new coronavirus treatments. But millions of patients need treatment here and now. Doctors are looking for effective drugs (or combinations of drugs) blindfolded. Meanwhile, chemists can predict which existing drugs are potentially most effective.
Answer: Russian researchers have created a special method for molecular modeling called “docking from above”. They used it to examine the entire surface of a protein that is vital SARS-CoV-2 and compare it to a number of known drugs. They found that two drugs could potentially “turn off” the enzyme and stop the reproduction of the coronavirus. One is used to treat alcohol dependence and the other is for cancer.
A team of chemists from the HSE University and the Institute of Organic Chemistry in Zelinski used molecular modeling to determine that two long-known drugs could be used to fight SARS-CoV-2. These are disulfiram, which is used to treat alcoholism, and neratinib, an experimental drug used to treat breast cancer. Both drugs are potential covalent inhibitors of the main Mpro protease of the SARS-CoV-2 virus, a key enzyme responsible for the replication of SARS-CoV-2 (copying its genetic material and building new virus particles). The document for the discovery was published in the July issue of Mendeleev Communications magazine.
The coronavirus was first discovered in a patient with an acute respiratory infection long ago, in 1965, but it was not until about two decades ago that humanity encountered truly dangerous members of this family. Unfortunately, since the first SARS-CoV epidemic did not leave Asia (mostly China) in 2002-2004, and the MERS outbreak in 2012-2015 seriously affected only Saudi Arabia and Korea, the global pharmaceutical industry did not almost no effort to develop. effective treatments for coronaviruses. Tests and drugs are actively developed almost exclusively for the needs of veterinary medicine.
Medicines with a wide range of uses have been used during previous epidemics, but the experience of medics in Wuhan, China, shows that this is not enough. Clinicians around the world risk trying different experimental protocols using drugs used to treat HIV (lopinavir and ritonavir), malaria, chloroquine and hydrochloroquine) and other diseases. But they were looking for drugs to be effectively blindfolded.
The global pharmaceutical industry was unaware and did not have time to create brand new drugs. Even if potentially effective substances are found, their preclinical and clinical trials will take four to seven years. Therefore, the most sensible solution is to look among known drugs that have proven to be safe for human health. This time – a drug for rearrangement – has been used effectively for a long time. The only problem is: how do we know if they are able to fight the coronavirus?
Computer modeling can help. This approach is called silicon – similar to in vivo (in a living body) and in vitro (in a test tube). It allows the use of digital models to test hundreds of different drugs and determine their potential effectiveness and mechanism of action. Chemists from HSE University and the RAS Zelinsky Institute of Organic Chemistry have been conducting similar research for many years. In 2014, they modeled leukemia, and in 2017 – treatment of rheumatoid arthritis. With this background, researchers jumped in search of a cure for SARS-CoV-2 in 2020.
How was it studied?
The coronavirus, like many other viruses, mutates quite rapidly. Its genome contains about 30,000 nucleotides – specific “building blocks” of the genetic code. On average, one mutation or more precisely one SNP (single nucleotide polymorphism) occurs with a virus RNA once every two weeks. This means that new strains of SARS-CoV-2 appear regularly. In Russia alone, there are nine unique SARS-CoV-2 lines that are not present in other countries.
Therefore, the structural elements of the virus that are less susceptible to mutation during its evolution should be selected as a target for potential treatment. Otherwise, drugs effective against one strain would no longer be effective against another. The best candidates for this are conservative proteins, such as the basic Mpro protease of the SARS-CoV-2 virus. In addition to being resistant to mutations, Mproplays plays a major role in the replication of the coronavirus, which means that inhibiting (blocking its function) is able to slow or even completely stop its reproduction inside the body.
Typically, the docking process, as in a port and a ship entering it, is used for molecular modeling in simple cases. Two molecules are involved in docking. One is called a ‘ligand’ (here it is a drug) and the other is a ‘receptor’ (or active site) of the target protein, such as Mpro, which can be used for ‘binding’. The effective drug binds to the active site through covalent bonds, which makes the enzyme dysfunctional or destroys it.
To simulate docking, researchers need to know the exact spatial structure of the drug molecule (they are available in special databases) and the exact configuration of the active site of the target protein. Here, researchers may face the first challenges: there may be dozens or even hundreds of such sites and they are not fixed in space. Therefore, classical docking does not work in SARS-CoV-2.
To overcome this problem, chemists at HSE University and the Zelinski Institute decided to use “docking”, which they invented shortly before the pandemic. They decided not to focus on the active site described above, but to study the entire surface of Mproprotein with many drugs, hoping that the large computing forces would return useful “docking”.
The researchers used the SARS-CoV-2 Mprocreate spatial model in January 2020 from the PDB database (ID 6LU7). Potential drugs are taken from the database of drugs approved by the US Food and Drug Administration (FDA). The research team’s own algorithms were used for modeling.
What were the results?
Model data show that sulfur-containing drugs show unusually high ligand efficacy at the active site of the SARS-CoV-2 basic Mpro protease, but only disulfiram 4 retains stable interactions.
Today, it is most commonly used to treat alcoholism because disulfiram inhibits the enzyme acetaldehyde dehydrogenase. As a result, the conversion of ethanol to the liver stops at the acetaldehyde stage. Its concentration in the body increases, leading to acute intoxication, accompanied by illness, vomiting and severe pain. As a result, alcohol addicts acquire a conditioned reflex of aversion to the smell and taste of alcoholic beverages. This means that if the effectiveness of disulfiram against the new coronavirus is confirmed, it would help solve two problems in Russia at once, while reducing alcohol addiction among the population.
Disulfiram fights SARS-CoV-2 in two ways. First, as previously shown in vitro with coronaviruses of SARS and MERS, it is a covalent inhibitor. He also fights COVID-19 symptoms such as a significant reduction in reduced glutathione, which is an important antioxidant. This deficiency can lead to severe manifestations of the disease.
In addition to disulfiram, Russian chemists were the first to predict the potential efficacy of neratinib, an irreversible tyrosine kinase inhibitor, against SARS-CoV-2. Most recently, in 2017, the FDA approved neratinib as an adjunct treatment for breast cancer.
How can this be used?
Modeling has shown that both potential core coronavirus protease (Mpro) inhibitors are likely to be covalent. For example, disulfiram is likely to block Mpro enzyme activity by a thiol disulfide exchange reaction, whereas binding of neratinib suggests the possibility of a covalent interaction similar to covalent peptide inhibitors.
It is important to clarify that any modeling can only predict such interactions, but not prove their presence. The research cycle consists of at least three stages: modeling, synthesis of potentially active structures and biological (pharmaceutical) testing of the required activity – real, not calculated efficacy of the drug. Modeling itself, like any other theoretical study, means nothing without subsequent experimental confirmations. That is why now is the time for extensive practical work on validating the results obtained as part of ‘docking at the top’.
Tests performed on July 27, 2020 at Reaction Biology Corp., a certified laboratory in the United States, showed that disulfiram did inhibit Mpro at a 100 nm concentration, which confirmed the simulation results. Unfortunately, the second substance – neratinib – has shown activity on Mpro, but is not sufficient for clinical use. On September 1, 2020, clinicians will begin trials for in vitro and experimental treatments of patients with SARS-Cov-2.
Chinese biochemists simultaneously and independently of Russian researchers conducted a mass experimental search for active structures. They also found potential activity of disulfiram for the main Mpro protease of the SARS-CoV-2 virus. Unfortunately, they did it two weeks earlier than Russian chemists, so the publication in nature is theirs (the paper will be issued in August). This serves as further evidence of the importance of having powerful computational resources for modeling and opportunities for biological experiments.
“We need the opportunity to immediately” declare “the results in a high-level Russian chemical journal. And there are only a few of them. Unfortunately, if we approve only publications in 1st and 2nd quarter magazines that are exclusively international, such Russian magazines will never appear. “- Igor Svitanko, Doctor of Science (Chemistry), Professor in the Joint Department of Organic Chemistry of the HSE at the Institute of Organic Chemistry of the Russian Academy of Sciences Zelinski
Meanwhile, the main achievement is the demonstration that the “docking top” approach works and gives quite realistic and controllable results. The team’s plans for the end of 2020 and 2021 include molecular modeling of treatments for diseases that have proven their harmfulness but have not yet spread around the world.
It is important to mention that any molecular modeling requires significant computational resources, and before collaborating with HSE University, chemists were only able to use their method under very limited conditions. Today, they have access to HSE University’s powerful supercomputer, which can help them search existing medicines and purposefully synthesize new pharmaceuticals.
This is a shining example of fruitful cooperation between a university and an institute of the Russian Academy of Sciences. An obvious next step in such academic collaboration is the organization of a Molecular Modeling Laboratory at HSE University. This laboratory will not only create drugs, but will model various chemical processes, both by docking or other simple methods, and by more universal and complex methods of quantum chemistry.
Meanwhile, the global chemical community faces the next challenge – modeling the structure of the G4 EA H1N1 virus protein inhibitor – a new swine flu that was recently discovered in China. Researchers believe that this infection is much more dangerous and is transmitted faster from person to person than COVID-19. To deal with it, researchers will need support, both in terms of resources and tools, and they will also need support in organizing productive academic work and setting priorities.
Reference: “Computational identification of disulfiram and neratinib as putative major protease inhibitors of SARS-CoV-2” by Victor S. Stroylova and Igor V. Svitanka, August 4, 2020, Mendeleev Communications,,
DOI: 10.1016 / j.mencom.2020.07.004