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Editorial
. 2018 Apr 5;14(4):e1005756.
doi: 10.1371/journal.pcbi.1005756. eCollection 2018 Apr.

New computational approaches to understanding molecular protein function

Jacquelyn S Fetrow  1 , Patricia C Babbitt  2
Affiliations
Editorial

New computational approaches to understanding molecular protein function

Jacquelyn S Fetrow et al. PLoS Comput Biol. .
No abstract available

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. An illustration of the concept of molecular functional hierarchy and its correlation with network analysis.
Similarity network analysis (left) uses edge thresholds to identify clusters that are progressively more similar to each other. As an example of molecular functional hierarchy, the Structure-Function Linkage Database (SFLD) hierarchy is shown on the right. Ideally, network clustering would capture the biologically relevant functional boundaries that would correlate with defined level of functional hierarchy, such as those defined by SFLD or the Gene Ontology (GO) hierarchies. (Note: the figure is illustrative and is not meant to suggest that an edge threshold of 0.3 correlates with the subgroup level of the SFLD hierarchy. One challenge in this field, illustrated by some of the papers in this Focus Feature, is which edge metric and threshold correlate with which levels of functional hierarchy).
Fig 2
Fig 2. Specificity determining or “signature” positions are amino acids directly involved in an enzyme’s activity.
Three such residues are shown as black side chains (left) for 5 arsenate reductase enzymes. Residues within close structural space are shown as colored fragments. The sequences of those colored fragments create the active site signature (right), a residue sequence originally defined by Cammer and colleagues [35]. Signatures can be aligned to create a profile, which allows direct comparison of residues in and near the active site. This active site profile concept is used by 3 of the approaches for functionally relevant clustering of protein superfamilies included in this Focus Feature. (The authors gratefully acknowledge Mikaela Rosen for creating these figures).
See this image and copyright information in PMC

References

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