Despite the passing of a year since the first
outbreak of SARS, efficient counter-measures are still few and
many believe that the reappearance of SARS, which is caused by a
coronavirus, is not unlikely. For other virus families like the
picornaviruses it is known that pathology is related to
proteolytic cleavage of host proteins by viral proteinases.
Furthermore, several studies indicate that virus proliferation can
be arrested using specific proteinase inibitors supporting the
belief that proteinases are indeed important during infection.
Prompted by this, we set out to analyse and predict cleavage by
the coronavirus main proteinase using computational methods.
Results: We retrieved sequence data on seven fully
sequenced coronaviruses and identified the main 3CL proteinase
cleavage sites in polyproteins using alignments. A neural network
was trained to recognise the cleavage sites in the genomes
obtaining a sensitivity of 87.0% and a specificity of 99.0%.
Several proteins known to be cleaved by other viruses were
submitted to prediction as well as proteins suspected relevant in
coronavirus pathology. Cleavage sites were predicted in proteins
such as the cystic fibrosis transmembrane conductance regulator
(CFTR), transcription factors CREB-RP and OCT-1, and components of
the ubiquitin pathway.
Conclusion: Our prediction method NetCorona predicts
coronavirus cleavage sites with high specificity and several
potential cleavage candidates were identified which might be
important to elucidate coronavirus pathology. Furthermore the
method might assist in design of proteinase inhibitors for
treatment of SARS and possible future diseases caused by