Computational study of COVID-19 and protein folding on the ribosome

Identyfikator grantu: PT00886

Kierownik projektu: Mai Suan Li_


  • Vu Van Quyen
  • Truong Co Nguyen
  • Pham Dinh Quoc Huy
  • Man Hoang Viet

Instytut Fizyki PAN w Warszawie


Data otwarcia: 2021-05-18

Streszczenie projektu

COVID-19 is a severe acute respiratory syndrome (SARS) disease caused by the novel coronavirus (SARS-CoV-2), which was first reported in Wuhan, China, in December 2019. The rapid spread of SARS-CoV-2 worldwide led the World Health Organization to declare a pandemic on 11 March 2020. To effectively combat COVID-19, we must understand the molecular interactions between SARS-CoV-2 and human host cells. To date, most efforts has been focused on understanding viral entry through binding to the angiotensin-converting enzyme 2 (ACE2) in humans. However, recent experiments have shown that the S (spike) protein of SARS-CoV-2 can bind to protein Neuropilin-1 before entering the cell but the molecular mechanism of this phenomenon is not fully understood. Here we will study this problem using a computer simulation.
Although many vaccines are produced and widely available, their ability to provide at least some protection against new variants of the virus remains unclear. Therefore, we still need effective drugs and antibodies to treat Covid-19. However, they have been not been developed due to the short period of time, although in many countries several repurposed drugs such as the antiviral drug Remdesivir and the anti-inflammatory Dexamethasone have been prescribed to patients. Therefore, the development of new drugs is critical to combat the Covid-19 pandemic. For this purpose, we will select two targets from the many SARS-CoV-2 drug targets: RNA-dependent RNA polymerase (RdRp) and RNA methyltransferase (NSP16-NSP10), which play a decisive role in the replication and transcription of the virus that catalyzes the synthesis of viral RNA. Potential drugs will be identified from large databases combining computational methods with in vitro experiments. We will also be looking for potential Covid-19 drugs from all drugs on the market, using NSP16-NSP10 as a target.
There is evidence that convalescent plasma (CP),which is the yellow liquid that remains after cells are removed from blood, actually helps patients. CP therapy is based on scientific principles according to which plasma of recovered people contains antibodies and proteins involved in regulating immune. In the SARS-CoV-2 case, antibodies can interact with the viral spike protein, preventing the virus from entering the cell. The spike protein of SARS-CoV-2 consists of two subunits, S1 and S2. Experiments have shown that antibodies prefer to bind to the N-terminal domain (NTD) and receptor binding domain (RBD) of S1 and several sites of S2. The dissociation constant of monoclonal antibodies (mAbs) like 4A8 and CR3022 from NTB and RBD has been experimentally measured, but the binding mechanism has not been elucidated. Thus, one of our goals is to solve this problem using computer simulations.
It has been demonstrated that nanobodies can be used to treat Covid. They can be used on their own or in combination with other antibodies, motivating us to carry out molecular dynamics simulations to better understand their interaction with the SARS-CoV-2 S protein. Recently emerging SARS-CoV-2 variants B.1.1.7 (UK), B.1.351 (South Africa), P.1 (Brazil), and B.1.617 (India) harbor mutations in the viral S protein that can alter the virus-host cell interactions and confer resistance to antibodies and nanobodies. Thus, our next goal is to study the effect of new mutations on the binding affinity of antibodies and nanobodies to SARS-CoV-2.
It should be noted that convalescent plasma has been tested only in small trials without the statistical power to provide firm conclusions. More importantly, even if plasma therapy is effective, the amount of plasma will not be enough for every patient. It is therefore very important to develop antibodies from other sources and this encourages us to find antibodies that are able to treat Covid-19 from the available databases. In this project we will use molecular simulations and in vitro experiments to obtain candidates that can strongly bind to NTD and RBD of the SARS-Cov-2 spike protein.
Protein folding on the ribosome
Ribosome is a molecular machine for protein synthesis which consists of four phases of translation – initiation, elongation, termination and ribosome recycling. This process is an area of intense research due to the essential role of proteins to life. For many decades, protein folding research has been dominated by the assumption that thermodynamics determines protein structure and function. However, recently accumulated evidence has supported the emerging paradigm of non-equilibrium control of protein behavior. Namely, speed of synthesis of proteins in the ribosome greatly influences their properties, mRNA sequence evolution, and disease. Thus, identifying the factors that govern the translation-elongation kinetics is vital for understanding the function of nascent proteins in vivo. This work will utilize a range of theoretical methods to address the following problems. First, recent interesting experimental observation is that the binding of the non-structural protein 1 (NSP1) of SARS-CoV-2 to the 40S subunit of the human ribosome does not affect the translation of viral mRNA but can inhibit the translation of the host mRNA. We plan to investigate this problem by using all-atom steered molecular dynamics simulations. The binding free energy of NSP1 to the ribosome will be obtained.
Secondly, our next goal is to understand how variable codon translation rates can result in soluble but non-functional protein: Influence of translation-elongation kinetics on protein dimerization in bulk. Changes in codon translation rates have recently been shown to alter a protein’s function but not necessarily its solubility, suggesting that structural changes in the nascent protein must be modest because otherwise aggregation would likely occur. Here, we will explore how extensive these structural rearrangements may be by simulating the synthesis of proteins that heterodimerize/homodimerize and calculating how their binding affinity changes as codon translation rates are altered. We hypothesize that the structural changes will involve partially folded structures that are long-lived kinetic traps, perhaps with secondary structural elements at the binding interface not properly arranged and thereby increasing the dissociation constant KD. These predictions will be corroborated by an experimental collaborator.


  1. Hong An Pham, Duc Toan Truong, and Mai Suan Li, Dependence of Work on the Pulling Speed in Mechanical Ligand Unbinding, J Phys Chem B 125, (2021) 8325–8330
  2. Adolfo B. Poma, Tran Thi Minh Thu, Lam Tang Minh Tri, Hoang Linh Nguyen, and Mai Suan Li, Nanomechanical Stability of Aβ Tetramers and Fibril-like Structures: Molecular Dynamics Simulations , J Phys Chem B 125, (2021) 7628–7637
  3. Nguyen Truong Co and Mai Suan Li, Effect of Surface Roughness on Aggregation of Polypeptide Chains: A Monte Carlo Study , J Phys Chem B 11, (2021) 596
  4. Hoang Linh Nguyen, Nguyen Quoc Thai and Mai Suan Li, Identifying inhibitors of NSP16-NSP10 of SARS-CoV-2 from large databases, Journal of Biomolecular Structure and Dynamics NA, (2022) NA
  5. Tran Thi Minh Thu and Mai Suan Li, Protein aggregation rate depends on mechanical stability of fibrillar structure , J. Chem. Phys. 157, (2022) 055101
  6. Hoang Linh Nguyen, Nguyen Quoc Thai, Phuong H. Nguyen, and Mai Suan Li, SARS-CoV-2 Omicron Variant Binds to Human Cells More Strongly than the Wild Type: Evidence from Molecular Dynamics Simulation , J. Phys. Chem. B 126 (25), (2022) 4669–4678
  7. Hung Nguyen & Mai Suan Li, Antibody–nanobody combination increases their neutralizing activity against SARS-CoV-2 and nanobody H11-H4 is effective against Alpha, Kappa and Delta variants , Scientific Reports 12, (2022) Article number: 9701
  8. Hoang Linh Nguyen, Huynh Quang Linh, Pawel Krupa, Giovanni La Penna, and Mai Suan Li , Amyloid β Dodecamer Disrupts the Neuronal Membrane More Strongly than the Mature Fibril: Understanding the Role of Oligomers in Neurotoxicity , J. Phys. Chem. B 126 (20), (2022) 3659-3672
  9. Hoang Linh Nguyen, Nguyen Quoc Thai, Mai Suan Li, Determination of Multidirectional Pathways for Ligand Release from the Receptor: A New Approach Based on Differential Evolution , J. Chem. Theory Comput. 18 (6), (2022) 3860–3872
  10. Hung Nguyen, Pham Dang Lan, Daniel A. Nissley, Edward P. O’Brien, and Mai Suan Li, Antibodies Binds More Strongly to SARS-CoV-2 Than Its Components, but the Omicron Variant Reduces Its Neutralizing Ability , J. Phys. Chem. B 2022, 126, 15, 2812–2823 126 (15), (2022) 2812–2823
  11. Hung Nguyen, Pham Dang Lan, Daniel A. Nissley, Edward P. O’Brien, and Mai Suan Li, Antibodies Binds More Strongly to SARS-CoV-2 Than Its Components, but the Omicron Variant Reduces Its Neutralizing Ability , J. Phys. Chem. B 2022, 126, 15, 2812–2823 126 (15), (2022) 2812–2823
  12. Hoang Linh Nguyen, Nguyen Quoc Thai and Mai Suan Li, Identifying inhibitors of NSP16-NSP10 of SARS-CoV-2 from large databases, Journal of Biomolecular Structure and Dynamics 41 (15), (2023) 7045-7054
  13. Quyen V. Vu, Daniel A. Nissley, Yang Jiang, Edward P. O’Brien, and Mai Suan Li, Is Posttranslational Folding More Efficient Than Refolding from a Denatured State: A Computational Study, J. Phys. Chem. B 127 (21), (2023) 4761–4774
  14. Lan, P. D.; Nissley, D. A.; O'Brien, E. P.; Nguyen, T. T.; Li, M. S, Deciphering the free energy landscapes of SARS-CoV-2 wild type and Omicron variant interacting with human ACE2, J. Chem. Phys. 160, (2024) 055101

← Powrót do spisu projektów


Nasi konsultanci służą pomocą przyszłym i początkującym użytkownikom specjalistycznego oprogramowania zainstalowanego na Komputerach Dużej Mocy w Centrum Informatycznym TASK.

Kontakt w sprawach Komputerów Dużej Mocy, oprogramowania/licencji, grantów obliczeniowych, sprawozdań:

Administratorzy odpowiadają na maile w dni robocze w godzinach 8:00 – 15:00.