ABSTRACT
The solution structure of SARS-CoV-2 nonstructural protein 7 (nsp7) at pH 7.0 has been determined by NMR spectroscopy. nsp7 is conserved in the coronavirinae subfamily and is an essential co-factor of the viral RNA-dependent RNA polymerase for active and processive replication. Similar to the previously deposited structures of SARS-CoV-1 nsp7 at acidic and basic conditions, SARS-CoV-2 nsp7 has a helical bundle folding at neutral pH. Remarkably, the 4 helix shows gradual dislocation from the core 2-3 structure as pH increases from 6.5 to 7.5. The protonation state of residue H36 contributes to the change of nsp7s intramolecular interactions, and thus, to the structural variation near-neutral pH. Spin-relaxation results revealed that all three loop regions in nsp7 possess dynamic properties associated with this structural variation.
ABSTRACT
Motif detection, which is to discover short patterns involved in many important biological processes, has been recently raised as an important task in bioinformatics. The traditional algorithms to find a sequence motif have been developed using machine learning only without involving the experience and domain knowledge of human experts effectively. In this paper, we propose an interactive motif discovery system by introducing a new learning algorithm, by generalizing a well-known statistical motif model, whose inference can be shepherded by human feedback.
