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Quantification of the impact of PSI:Biology according to the annotations of the determined structures.

DePietro PJ, Julfayev ES, McLaughlin WA - BMC Struct. Biol. (2013)

Bottom Line: One result is that PSI:Biology structures are found to have a higher rate of annotations than structures determined during the first two phases of PSI.We conclude that PSI:Biology determines structures that are estimated to have a higher degree of biomedical interest than those determined during the first two phases of PSI based on a broad array of biomedical annotations.For the PSI:Biology Partnerships, we see that there is an associated added value that represents part of the progress toward the goals of PSI:Biology.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Basic Science, The Commonwealth Medical College, 525 Pine Street, Scranton, PA 18509, USA. wmclaughlin@tcmedc.org.

ABSTRACT

Background: Protein Structure Initiative:Biology (PSI:Biology) is the third phase of PSI where protein structures are determined in high-throughput to characterize their biological functions. The transition to the third phase entailed the formation of PSI:Biology Partnerships which are composed of structural genomics centers and biomedical science laboratories. We present a method to examine the impact of protein structures determined under the auspices of PSI:Biology by measuring their rates of annotations. The mean numbers of annotations per structure and per residue are examined. These are designed to provide measures of the amount of structure to function connections that can be leveraged from each structure.

Results: One result is that PSI:Biology structures are found to have a higher rate of annotations than structures determined during the first two phases of PSI. A second result is that the subset of PSI:Biology structures determined through PSI:Biology Partnerships have a higher rate of annotations than those determined exclusive of those partnerships. Both results hold when the annotation rates are examined either at the level of the entire protein or for annotations that are known to fall at specific residues within the portion of the protein that has a determined structure.

Conclusions: We conclude that PSI:Biology determines structures that are estimated to have a higher degree of biomedical interest than those determined during the first two phases of PSI based on a broad array of biomedical annotations. For the PSI:Biology Partnerships, we see that there is an associated added value that represents part of the progress toward the goals of PSI:Biology. We interpret the added value to mean that team-based structural biology projects that utilize the expertise and technologies of structural genomics centers together with biological laboratories in the community are conducted in a synergistic manner. We show that the annotation rates can be used in conjunction with established metrics, i.e. the numbers of structures and impact of publication records, to monitor the progress of PSI:Biology towards its goals of examining structure to function connections of high biomedical relevance. The metric provides an objective means to quantify the overall impact of PSI:Biology as it uses biomedical annotations from external sources.

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Ratios of mean number of annotation assignments per protein from PSI:Biology Partnerships versus the PDB US non-SG ensemble. Asterisks indicate the annotation ratios that are statistically significant based on a Student’s t-test (p-value ≤ 0.05). Data for the plot is available in Additional file 1: Table S3. Inset- Ratios for a group of annotations based on the UniProt keyword system.
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Figure 3: Ratios of mean number of annotation assignments per protein from PSI:Biology Partnerships versus the PDB US non-SG ensemble. Asterisks indicate the annotation ratios that are statistically significant based on a Student’s t-test (p-value ≤ 0.05). Data for the plot is available in Additional file 1: Table S3. Inset- Ratios for a group of annotations based on the UniProt keyword system.

Mentions: Figure 3 shows that the Partnership structures tend to have higher annotation rates than structures from the PDB US non-SG ensemble. For the comparison, we see that there is a focus on higher order biological processes and diseases. One illustrative example is a higher focus on signaling pathways related to human cancer, as exhibited in the representation of proteins in the National Cancer Institute’s Pathway Interaction Database [18]. A second illustrative example is a greater focus on coding sequence diversity, which includes complex annotations of splice variants [19]. UniProt domains are also higher, which indicates a focus on biologically relevant domains. Noteworthy exceptions are enzymes, annotated with EC numbers, and relevant ligands, as suggested by BioCyc small molecule entries. We interpret this finding as a result of a selection bias against enzymes within the PSI:Biology Partnerships. See Additional file 1: Table S3 for data used in Figure 3.


Quantification of the impact of PSI:Biology according to the annotations of the determined structures.

DePietro PJ, Julfayev ES, McLaughlin WA - BMC Struct. Biol. (2013)

Ratios of mean number of annotation assignments per protein from PSI:Biology Partnerships versus the PDB US non-SG ensemble. Asterisks indicate the annotation ratios that are statistically significant based on a Student’s t-test (p-value ≤ 0.05). Data for the plot is available in Additional file 1: Table S3. Inset- Ratios for a group of annotations based on the UniProt keyword system.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4016320&req=5

Figure 3: Ratios of mean number of annotation assignments per protein from PSI:Biology Partnerships versus the PDB US non-SG ensemble. Asterisks indicate the annotation ratios that are statistically significant based on a Student’s t-test (p-value ≤ 0.05). Data for the plot is available in Additional file 1: Table S3. Inset- Ratios for a group of annotations based on the UniProt keyword system.
Mentions: Figure 3 shows that the Partnership structures tend to have higher annotation rates than structures from the PDB US non-SG ensemble. For the comparison, we see that there is a focus on higher order biological processes and diseases. One illustrative example is a higher focus on signaling pathways related to human cancer, as exhibited in the representation of proteins in the National Cancer Institute’s Pathway Interaction Database [18]. A second illustrative example is a greater focus on coding sequence diversity, which includes complex annotations of splice variants [19]. UniProt domains are also higher, which indicates a focus on biologically relevant domains. Noteworthy exceptions are enzymes, annotated with EC numbers, and relevant ligands, as suggested by BioCyc small molecule entries. We interpret this finding as a result of a selection bias against enzymes within the PSI:Biology Partnerships. See Additional file 1: Table S3 for data used in Figure 3.

Bottom Line: One result is that PSI:Biology structures are found to have a higher rate of annotations than structures determined during the first two phases of PSI.We conclude that PSI:Biology determines structures that are estimated to have a higher degree of biomedical interest than those determined during the first two phases of PSI based on a broad array of biomedical annotations.For the PSI:Biology Partnerships, we see that there is an associated added value that represents part of the progress toward the goals of PSI:Biology.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Basic Science, The Commonwealth Medical College, 525 Pine Street, Scranton, PA 18509, USA. wmclaughlin@tcmedc.org.

ABSTRACT

Background: Protein Structure Initiative:Biology (PSI:Biology) is the third phase of PSI where protein structures are determined in high-throughput to characterize their biological functions. The transition to the third phase entailed the formation of PSI:Biology Partnerships which are composed of structural genomics centers and biomedical science laboratories. We present a method to examine the impact of protein structures determined under the auspices of PSI:Biology by measuring their rates of annotations. The mean numbers of annotations per structure and per residue are examined. These are designed to provide measures of the amount of structure to function connections that can be leveraged from each structure.

Results: One result is that PSI:Biology structures are found to have a higher rate of annotations than structures determined during the first two phases of PSI. A second result is that the subset of PSI:Biology structures determined through PSI:Biology Partnerships have a higher rate of annotations than those determined exclusive of those partnerships. Both results hold when the annotation rates are examined either at the level of the entire protein or for annotations that are known to fall at specific residues within the portion of the protein that has a determined structure.

Conclusions: We conclude that PSI:Biology determines structures that are estimated to have a higher degree of biomedical interest than those determined during the first two phases of PSI based on a broad array of biomedical annotations. For the PSI:Biology Partnerships, we see that there is an associated added value that represents part of the progress toward the goals of PSI:Biology. We interpret the added value to mean that team-based structural biology projects that utilize the expertise and technologies of structural genomics centers together with biological laboratories in the community are conducted in a synergistic manner. We show that the annotation rates can be used in conjunction with established metrics, i.e. the numbers of structures and impact of publication records, to monitor the progress of PSI:Biology towards its goals of examining structure to function connections of high biomedical relevance. The metric provides an objective means to quantify the overall impact of PSI:Biology as it uses biomedical annotations from external sources.

Show MeSH