Funding: IDUB WUT
Project period: 2020 - 2022
Project leader: Michał Łaźniewski
Faculty of Mathematics and Information Science, Warsaw University of Technology
The goal of this project is to perform bioinformatic analysis of spike proteins from the Coronaviridae subfamily to identify strains that are potentially dangerous to the human population and could be responsible for the next pandemics. Our computational model will use in its first phase a machine learning approach to identify proteins that preferentially bind to the human proteins. Next, for the most relevant findings, we will predict binding energy between these proteins and their molecular partners from the selected organisms. A molecular dynamics simulation will be carried out using either available crystal structures of proteins in question or if they are unavailable, their homology models. The free energy of binding will be calculated using both MM-PBSA and weighted histogram analysis method.
SARS-CoV-2, a member of the Coronaviridae subfamily, is a causative agent of the latest pandemics. This situation should not be a surprise considering that in this century alone, two members of this family - SARS-CoV and MERS-CoV - gave rise to two lethal epidemics. Coronaviruses are predominantly of animal origin and their main reservoir is most likely bats, however, only a limited focus has been put to identify which bat strains might become a source of the next pandemics. Viral spike protein is responsible for determining host tropism. The spike protein of viruses from different evolutionary lineages can recognize diverse elements on the host cell like aminopeptidase N, dipeptidyl peptidase 4, or, in the case of SARS-Cov-2, angiotensin-converting enzyme 2. However, to effectively switch between hosts, several mutations in the receptor-binding site of this enzyme are usually required. This phenomenon was extensively studied for SARS-CoV-2 spike protein, yet, identified mutations are probably not universal for all coronaviruses and different paths can be taken to achieve the same goal – preferential bindings to human proteins. Successful prevention of future epidemics demands the creation of a reliable tool capable of predicting the host tropism for coronaviruses in a high-throughput manner. This would allow establishing which coronaviruses still circulating in bat population are on the verge of becoming a threat to the human population. This, in turn, would allow us to better prepare for the next epidemic by, for example, determining specific diagnostic procedures.
- Michał Łaźniewski – project leader
- Dariusz Plewczynski
- Michał Burdukiewicz
Former team members:
- Michał Kadlof
- Doni Dermawan
Budget – 125 000 PLN