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These results demonstrate that characterizing the deviation from the open-cell model is vital to gain a full understanding of scaffold biophysical properties, and provide a template for structural studies of other freeze-dried biomaterials.
In both studies the CP of STNV was also found to be the best template for structural modeling of the geminiviral CPs.
Architectural cues of scaffolds provide not only an appropriate template for structural guidance of MSCs but also a 3D environment that may direct their functional activity.
Out of all these icosahedral virus structures CP of Satellite tobacco necrosis virus (STNV) was found to be the only suitable template for structural modeling with significant scores for all four geminiviral CPs.
Among viruses for which a 3D structure is available, the Satellite tobacco necrosis virus (STNV) was found, with a significant score, to be a suitable template for structural modeling of geminiviral CPs, as was also earlier reported in [ 27, 28].
The structure of STNV capsid protein (CP) [ 31] was determined to be the best template for structural modeling with significance scores ranging from 57.67 – 82.50; scores above 50 are assumed to be significant and correspond to a prediction accuracy of above 90% [ 29].
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The structures of SiCYS-N and SiCYS-C appeared alike using those structures as templates for structural prediction.
The DHCCs 1ETP and 3MK7c are the best templates for structural alignments and are both soluble proteins that contain two c-type hemes.
In fact, our attempts to use these CPs as templates for structural modeling of the geminivirus CPs did not produce significant scores, according to the Structure Prediction MetaServer [ 34] (not shown).
The crystal structures of maize ZmLTP1.6 (PDB ID: 1FK7) [ 7], wheat nsLTP2 (PDB ID: 1TUK) [ 8], AtDIR1 (PDB ID: 2RKN) [ 4] were selected as templates for structural modeling based on searches against the PDB using the Basic Local Alignment Search Tool (BLAST) at NCBI (http://blast.ncbi.nlm.nih.gov/) with the target Type 1, 2 and D protein sequences as baits.
Thus such second order predictions significantly raise the sensitivity of 3D template annotations for structural genomics.
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