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A PDB-wide, evolution-based assessment of protein-protein interfaces.

Baskaran K, Duarte JM, Biyani N, Bliven S, Capitani G - BMC Struct. Biol. (2014)

Bottom Line: An automated computational pipeline was developed to run our Evolutionary Protein-Protein Interface Classifier (EPPIC) software on the entire PDB and store the results in a relational database, currently containing > 800,000 interfaces.By comparing our safest predictions to the PDB author annotations, we provide a lower-bound estimate of the error rate of biological unit annotations in the PDB.These tools enable the comprehensive study of several aspects of protein-protein contacts in the PDB and represent a basis for future, even larger scale studies of protein-protein interactions.

View Article: PubMed Central - HTML - PubMed

ABSTRACT

Background: Thanks to the growth in sequence and structure databases, more than 50 million sequences are now available in UniProt and 100,000 structures in the PDB. Rich information about protein-protein interfaces can be obtained by a comprehensive study of protein contacts in the PDB, their sequence conservation and geometric features.

Results: An automated computational pipeline was developed to run our Evolutionary Protein-Protein Interface Classifier (EPPIC) software on the entire PDB and store the results in a relational database, currently containing > 800,000 interfaces. This allows the analysis of interface data on a PDB-wide scale. Two large benchmark datasets of biological interfaces and crystal contacts, each containing about 3000 entries, were automatically generated based on criteria thought to be strong indicators of interface type. The BioMany set of biological interfaces includes NMR dimers solved as crystal structures and interfaces that are preserved across diverse crystal forms, as catalogued by the Protein Common Interface Database (ProtCID) from Xu and Dunbrack. The second dataset, XtalMany, is derived from interfaces that would lead to infinite assemblies and are therefore crystal contacts. BioMany and XtalMany were used to benchmark the EPPIC approach. The performance of EPPIC was also compared to classifications from the Protein Interfaces, Surfaces, and Assemblies (PISA) program on a PDB-wide scale, finding that the two approaches give the same call in about 88% of PDB interfaces. By comparing our safest predictions to the PDB author annotations, we provide a lower-bound estimate of the error rate of biological unit annotations in the PDB. Additionally, we developed a PyMOL plugin for direct download and easy visualization of EPPIC interfaces for any PDB entry. Both the datasets and the PyMOL plugin are available at http://www.eppic-web.org/ewui/\#downloads.

Conclusions: Our computational pipeline allows us to analyze protein-protein contacts and their sequence conservation across the entire PDB. Two new benchmark datasets are provided, which are over an order of magnitude larger than existing manually curated ones. These tools enable the comprehensive study of several aspects of protein-protein contacts in the PDB and represent a basis for future, even larger scale studies of protein-protein interactions.

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The Janin curve (1997) revisited. The Janin curve is plotted against EPPIC calls (based on evolutionary indicators, cyan, and on geometry, green) for all current (May 2014) PDB interfaces larger than 600 Å 2 and against all PDB interfaces conducive to infinite assemblies. The curves are plotted as normalized probability versus interface area.
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Figure 5: The Janin curve (1997) revisited. The Janin curve is plotted against EPPIC calls (based on evolutionary indicators, cyan, and on geometry, green) for all current (May 2014) PDB interfaces larger than 600 Å 2 and against all PDB interfaces conducive to infinite assemblies. The curves are plotted as normalized probability versus interface area.

Mentions: In his landmark paper [6], Janin used a dataset of 1,320 pairwise interfaces derived from 152 crystal forms of monomeric proteins to draw a curve (exponential function) relating the interface area of a lattice contact to the probability of it being a crystal contact. For this fit, Janin used only data points corresponding to contacts with no point group symmetry, which are thus very unlikely to be biologically relevant, as discussed in the previous section (interfaces conducive to infinite assemblies). We set out to compare the Janin curve with our approach, using data from the now 15-fold larger PDB. The result is shown in Figure 5, where the Janin curve appears in light green and the distribution of all interfaces from the current PDB that are conducive to infinite assemblies, encompassing 56,378 interfaces, appears in brown. The two curves overlap very well, testifying to the validity of the original Janin approach and showing that the area distribution of contacts conducive to infinite assemblies has not changed, in spite of the huge increase in the size of the PDB.


A PDB-wide, evolution-based assessment of protein-protein interfaces.

Baskaran K, Duarte JM, Biyani N, Bliven S, Capitani G - BMC Struct. Biol. (2014)

The Janin curve (1997) revisited. The Janin curve is plotted against EPPIC calls (based on evolutionary indicators, cyan, and on geometry, green) for all current (May 2014) PDB interfaces larger than 600 Å 2 and against all PDB interfaces conducive to infinite assemblies. The curves are plotted as normalized probability versus interface area.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4274722&req=5

Figure 5: The Janin curve (1997) revisited. The Janin curve is plotted against EPPIC calls (based on evolutionary indicators, cyan, and on geometry, green) for all current (May 2014) PDB interfaces larger than 600 Å 2 and against all PDB interfaces conducive to infinite assemblies. The curves are plotted as normalized probability versus interface area.
Mentions: In his landmark paper [6], Janin used a dataset of 1,320 pairwise interfaces derived from 152 crystal forms of monomeric proteins to draw a curve (exponential function) relating the interface area of a lattice contact to the probability of it being a crystal contact. For this fit, Janin used only data points corresponding to contacts with no point group symmetry, which are thus very unlikely to be biologically relevant, as discussed in the previous section (interfaces conducive to infinite assemblies). We set out to compare the Janin curve with our approach, using data from the now 15-fold larger PDB. The result is shown in Figure 5, where the Janin curve appears in light green and the distribution of all interfaces from the current PDB that are conducive to infinite assemblies, encompassing 56,378 interfaces, appears in brown. The two curves overlap very well, testifying to the validity of the original Janin approach and showing that the area distribution of contacts conducive to infinite assemblies has not changed, in spite of the huge increase in the size of the PDB.

Bottom Line: An automated computational pipeline was developed to run our Evolutionary Protein-Protein Interface Classifier (EPPIC) software on the entire PDB and store the results in a relational database, currently containing > 800,000 interfaces.By comparing our safest predictions to the PDB author annotations, we provide a lower-bound estimate of the error rate of biological unit annotations in the PDB.These tools enable the comprehensive study of several aspects of protein-protein contacts in the PDB and represent a basis for future, even larger scale studies of protein-protein interactions.

View Article: PubMed Central - HTML - PubMed

ABSTRACT

Background: Thanks to the growth in sequence and structure databases, more than 50 million sequences are now available in UniProt and 100,000 structures in the PDB. Rich information about protein-protein interfaces can be obtained by a comprehensive study of protein contacts in the PDB, their sequence conservation and geometric features.

Results: An automated computational pipeline was developed to run our Evolutionary Protein-Protein Interface Classifier (EPPIC) software on the entire PDB and store the results in a relational database, currently containing > 800,000 interfaces. This allows the analysis of interface data on a PDB-wide scale. Two large benchmark datasets of biological interfaces and crystal contacts, each containing about 3000 entries, were automatically generated based on criteria thought to be strong indicators of interface type. The BioMany set of biological interfaces includes NMR dimers solved as crystal structures and interfaces that are preserved across diverse crystal forms, as catalogued by the Protein Common Interface Database (ProtCID) from Xu and Dunbrack. The second dataset, XtalMany, is derived from interfaces that would lead to infinite assemblies and are therefore crystal contacts. BioMany and XtalMany were used to benchmark the EPPIC approach. The performance of EPPIC was also compared to classifications from the Protein Interfaces, Surfaces, and Assemblies (PISA) program on a PDB-wide scale, finding that the two approaches give the same call in about 88% of PDB interfaces. By comparing our safest predictions to the PDB author annotations, we provide a lower-bound estimate of the error rate of biological unit annotations in the PDB. Additionally, we developed a PyMOL plugin for direct download and easy visualization of EPPIC interfaces for any PDB entry. Both the datasets and the PyMOL plugin are available at http://www.eppic-web.org/ewui/\#downloads.

Conclusions: Our computational pipeline allows us to analyze protein-protein contacts and their sequence conservation across the entire PDB. Two new benchmark datasets are provided, which are over an order of magnitude larger than existing manually curated ones. These tools enable the comprehensive study of several aspects of protein-protein contacts in the PDB and represent a basis for future, even larger scale studies of protein-protein interactions.

Show MeSH
Related in: MedlinePlus