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Protein functional surfaces: global shape matching and local spatial alignments of ligand binding sites.

Binkowski TA, Joachimiak A - BMC Struct. Biol. (2008)

Bottom Line: Surfaces performing identical functions are found in proteins absent of any sequence or fold similarity.Results using surface similarity to predict function for proteins of unknown function are reported.Additionally, an automated analysis of the ATP binding surface landscape is presented to provide insight into the correlation between surface similarity and function for structures in the PDB and for the subset of protein kinases.

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Affiliation: Midwest Center for Structural Genomics and Structural Biology Center, Biosciences Division, Argonne National Laboratory, Argonne, Illinois 60439, USA. abinkowski@anl.gov

ABSTRACT

Background: Protein surfaces comprise only a fraction of the total residues but are the most conserved functional features of proteins. Surfaces performing identical functions are found in proteins absent of any sequence or fold similarity. While biochemical activity can be attributed to a few key residues, the broader surrounding environment plays an equally important role.

Results: We describe a methodology that attempts to optimize two components, global shape and local physicochemical texture, for evaluating the similarity between a pair of surfaces. Surface shape similarity is assessed using a three-dimensional object recognition algorithm and physicochemical texture similarity is assessed through a spatial alignment of conserved residues between the surfaces. The comparisons are used in tandem to efficiently search the Global Protein Surface Survey (GPSS), a library of annotated surfaces derived from structures in the PDB, for studying evolutionary relationships and uncovering novel similarities between proteins.

Conclusion: We provide an assessment of our method using library retrieval experiments for identifying functionally homologous surfaces binding different ligands, functionally diverse surfaces binding the same ligand, and binding surfaces of ubiquitous and conformationally flexible ligands. Results using surface similarity to predict function for proteins of unknown function are reported. Additionally, an automated analysis of the ATP binding surface landscape is presented to provide insight into the correlation between surface similarity and function for structures in the PDB and for the subset of protein kinases.

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Automated identification of protein binding surfaces and construction of SurfaceShapeSignatures (SSS). The nicotinamide-adenine-dinucleotide phosphate (NADP) binding surface from human pathogen S. pyogenes (PDB:2ahr, a) is defined by measuring the change in solvent accessibility between the bound and apo structure (b, pink). The SSS of a binding surface is constructed by measuring the inter-atomic Euclidean distances between all unique surface atom pairs (c). The signatures of select DNA, ligand and metal binding surfaces for proteins in the PDB.
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Figure 1: Automated identification of protein binding surfaces and construction of SurfaceShapeSignatures (SSS). The nicotinamide-adenine-dinucleotide phosphate (NADP) binding surface from human pathogen S. pyogenes (PDB:2ahr, a) is defined by measuring the change in solvent accessibility between the bound and apo structure (b, pink). The SSS of a binding surface is constructed by measuring the inter-atomic Euclidean distances between all unique surface atom pairs (c). The signatures of select DNA, ligand and metal binding surfaces for proteins in the PDB.

Mentions: After a protein's binding surfaces has been identified (see Methods), the SSS is constructed by systematically measuring the Euclidean distance between all unique atom pairs for a given surface. This is seen for the nicotinamide-adenine-dinucleotide phosphate (NADP) binding surface from human pathogen S. pyogenes (PDB:2ahr) in Figure 1c. The inter-atomic distances are then sorted to form the shape signatures. The SSS distributions for a selection of heme, nicotinamide adenine dinucleotide (NAD) and adenosine 5'-triphosphate (ATP) binding surfaces are shown in Figure 1d. For reference, SSS distributions for a selection of DNA and metal binding surfaces are also shown. Once the shape distributions for two surfaces are computed, we apply the Kolmogorov-Smirnov (KS) test[25] to compare the probability distributions. The KS test identifies the greatest distance between the observed and expected cumulative frequencies and is bound between zero (identical distributions) and 1 (different distributions).


Protein functional surfaces: global shape matching and local spatial alignments of ligand binding sites.

Binkowski TA, Joachimiak A - BMC Struct. Biol. (2008)

Automated identification of protein binding surfaces and construction of SurfaceShapeSignatures (SSS). The nicotinamide-adenine-dinucleotide phosphate (NADP) binding surface from human pathogen S. pyogenes (PDB:2ahr, a) is defined by measuring the change in solvent accessibility between the bound and apo structure (b, pink). The SSS of a binding surface is constructed by measuring the inter-atomic Euclidean distances between all unique surface atom pairs (c). The signatures of select DNA, ligand and metal binding surfaces for proteins in the PDB.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2626596&req=5

Figure 1: Automated identification of protein binding surfaces and construction of SurfaceShapeSignatures (SSS). The nicotinamide-adenine-dinucleotide phosphate (NADP) binding surface from human pathogen S. pyogenes (PDB:2ahr, a) is defined by measuring the change in solvent accessibility between the bound and apo structure (b, pink). The SSS of a binding surface is constructed by measuring the inter-atomic Euclidean distances between all unique surface atom pairs (c). The signatures of select DNA, ligand and metal binding surfaces for proteins in the PDB.
Mentions: After a protein's binding surfaces has been identified (see Methods), the SSS is constructed by systematically measuring the Euclidean distance between all unique atom pairs for a given surface. This is seen for the nicotinamide-adenine-dinucleotide phosphate (NADP) binding surface from human pathogen S. pyogenes (PDB:2ahr) in Figure 1c. The inter-atomic distances are then sorted to form the shape signatures. The SSS distributions for a selection of heme, nicotinamide adenine dinucleotide (NAD) and adenosine 5'-triphosphate (ATP) binding surfaces are shown in Figure 1d. For reference, SSS distributions for a selection of DNA and metal binding surfaces are also shown. Once the shape distributions for two surfaces are computed, we apply the Kolmogorov-Smirnov (KS) test[25] to compare the probability distributions. The KS test identifies the greatest distance between the observed and expected cumulative frequencies and is bound between zero (identical distributions) and 1 (different distributions).

Bottom Line: Surfaces performing identical functions are found in proteins absent of any sequence or fold similarity.Results using surface similarity to predict function for proteins of unknown function are reported.Additionally, an automated analysis of the ATP binding surface landscape is presented to provide insight into the correlation between surface similarity and function for structures in the PDB and for the subset of protein kinases.

View Article: PubMed Central - HTML - PubMed

Affiliation: Midwest Center for Structural Genomics and Structural Biology Center, Biosciences Division, Argonne National Laboratory, Argonne, Illinois 60439, USA. abinkowski@anl.gov

ABSTRACT

Background: Protein surfaces comprise only a fraction of the total residues but are the most conserved functional features of proteins. Surfaces performing identical functions are found in proteins absent of any sequence or fold similarity. While biochemical activity can be attributed to a few key residues, the broader surrounding environment plays an equally important role.

Results: We describe a methodology that attempts to optimize two components, global shape and local physicochemical texture, for evaluating the similarity between a pair of surfaces. Surface shape similarity is assessed using a three-dimensional object recognition algorithm and physicochemical texture similarity is assessed through a spatial alignment of conserved residues between the surfaces. The comparisons are used in tandem to efficiently search the Global Protein Surface Survey (GPSS), a library of annotated surfaces derived from structures in the PDB, for studying evolutionary relationships and uncovering novel similarities between proteins.

Conclusion: We provide an assessment of our method using library retrieval experiments for identifying functionally homologous surfaces binding different ligands, functionally diverse surfaces binding the same ligand, and binding surfaces of ubiquitous and conformationally flexible ligands. Results using surface similarity to predict function for proteins of unknown function are reported. Additionally, an automated analysis of the ATP binding surface landscape is presented to provide insight into the correlation between surface similarity and function for structures in the PDB and for the subset of protein kinases.

Show MeSH