Revealing the functional mechanism of the main protease of SARS-CoV-2 - Revealing the functional mechanism of the main protease of SARS-CoV-2
Revealing the functional mechanism of the main protease of SARS-CoV-2
COVID-19 disease has become an exceptionally serious health threat worldwide and no cure or vaccination has been discovered for the disease yet. There is a great need for research data and knowledge, and COVID-19 and the virus causing it, SARS-CoV-2, are being intensively studied in universities, research institutes and supercomputing centers around the world. The goal now is to find means to block the function of the SARS-CoV-2 and develop a vaccine to prevent the development of the disease.
CSC wanted to contribute and accelerate research related to the COVID-19 pandemic. In March, CSC opened a prioritized access to Puhti supercomputer for COVID-19 pandemic research. COVID-19 projects have used about a third of Puhti’s capacity.
One of these groups in the “fast track” is Professor Ilpo Vattulainen’s group in Department of Physics, University of Helsinki. The objective of their project is to use atomistic molecular dynamics simulations and machine learning techniques to unveil the mechanism of action of the main protease (mPro) of the SARS-COV-2 virus.
– This enzyme is responsible for the maturation of the viral particles, thus inhibition of the enzyme prevents viral replication. Many drugs have been suggested to deactivate the function of the main protease but progress in research is difficult if the mechanism of action is not understood in detail, said Ilpo Vattulainen.
Two lines of research
The project carried out by the Vattulainen group focuses on two lines of research.
First, since the active form of mPro is a dimer comprised of two bound monomeric proteins, the objective is to figure out how the two proteins dimerize and how their binding could be blocked.
Second, since several drug candidates are known to bind to the vicinity of the active site of mPro, the aim is to reveal how this binding interferes or blocks the enzyme activation. In both cases, the studies make use of databases of drug candidate molecules that are known not to be harmful to human health.
– In a month, the project has generated 0.5 milliseconds of atomistic simulation data that have been analyzed by several supervised and unsupervised machine learning techniques, said Vattulainen.
In the context of the dimerization interface, the goal is to look for molecules that could inhibit the formation of an active enzyme dimer or impair its stability. The relevance of this approach is highlighted by bioinformatics analyses of the mutations in the available strains of viable viral infections: they substantiate that there are no mutations at the dimeric interface of mPro.
These investigations are complemented by consideration of the active site dynamics, which reveals that the dynamics of the enzyme’s active site is modulated by the concerted motion of the protein monomers, which also highlights the importance of the dimerization interface in the activation and function of mPro. These results strongly suggest that drugs that inhibit the dimerization of the enzyme or disrupt the signalling between the dimeric interface and the active site are potent candidates for combating COVID-19.
Currently, the group is building Markov State Models (MSMs) to unveil the kinetics of the information transfer between the dimeric interface and the drug binding sites. Markov state models (MSMs) are a class of models for modeling the long timescale dynamics of molecular systems.
The research group is also using powerful free energy calculation methods to assess the binding free energies for a number of drugs proposed to inhibit mPro function. Using the knowledge gained from the machine learning models and free energy methods, effective drugs for the inhibition of the mPro enzyme can be proposed.
Mechanism of action of the main protease of SARS-COV-2. S. Kaptan, M. Girych, G. Enkavi, W. Kulig, T. Rog, V. Sharma, I. Vattulainen. Work in progress (2020).