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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.

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.

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Retrieval of HIV-1 proteases from the GPSS library using surface similarity. The binding surface of human HIV-1 protease (ab) complexed with inhibitor BEB (c) was queried against the GPSS library. The sorted KS distances are shown in (d) with other HIV-1 proteases highlighted in red. ROC curves for retrieval using SurfaceShapeSignature, SurfaceAlign and SurfaceScreen scoring are shown in (e). The highest ranking non-protease surface was from the DcmaT (h) binding surface aclacinomycin methylesterase (RdmC) from S. purpurascens (fg). A superposition of the surfaces based on the SurfaceAlign alignment (ij) and with their respective ligands (k).
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Figure 6: Retrieval of HIV-1 proteases from the GPSS library using surface similarity. The binding surface of human HIV-1 protease (ab) complexed with inhibitor BEB (c) was queried against the GPSS library. The sorted KS distances are shown in (d) with other HIV-1 proteases highlighted in red. ROC curves for retrieval using SurfaceShapeSignature, SurfaceAlign and SurfaceScreen scoring are shown in (e). The highest ranking non-protease surface was from the DcmaT (h) binding surface aclacinomycin methylesterase (RdmC) from S. purpurascens (fg). A superposition of the surfaces based on the SurfaceAlign alignment (ij) and with their respective ligands (k).

Mentions: The binding surface of human HIV-1 (PDB:1eby, E.C. 3.4.23.16, CATH[39] 20.40.70.10, Figure 6ab) with bound inhibitor BEB (MW 652.7, Figure 6c) was selected as a query. First, the query was searched against the GPSS library using the SSS comparisons. The sorted KS distance scores between the query surface and all members from the library are plotted in Figure 6d. Points highlighted in red indicate known HIV-1 inhibitor binding surfaces. The results behave expectedly as 124 of 151 have KS distance scores less than 0.1. Plotting the search results in a receiver operator characteristic (ROC) curve (see Methods) we measure the retrieval rate using SSS at 84.7% from the area under the curve (AUC) (Figure 6e). The poorest ranking HIV-1 protease surfaces are associated with aggressive mutation studies in the binding pocket or correlated to decisively small (<200) or large (>900) molecular weight inhibitors.


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

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

Retrieval of HIV-1 proteases from the GPSS library using surface similarity. The binding surface of human HIV-1 protease (ab) complexed with inhibitor BEB (c) was queried against the GPSS library. The sorted KS distances are shown in (d) with other HIV-1 proteases highlighted in red. ROC curves for retrieval using SurfaceShapeSignature, SurfaceAlign and SurfaceScreen scoring are shown in (e). The highest ranking non-protease surface was from the DcmaT (h) binding surface aclacinomycin methylesterase (RdmC) from S. purpurascens (fg). A superposition of the surfaces based on the SurfaceAlign alignment (ij) and with their respective ligands (k).
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 6: Retrieval of HIV-1 proteases from the GPSS library using surface similarity. The binding surface of human HIV-1 protease (ab) complexed with inhibitor BEB (c) was queried against the GPSS library. The sorted KS distances are shown in (d) with other HIV-1 proteases highlighted in red. ROC curves for retrieval using SurfaceShapeSignature, SurfaceAlign and SurfaceScreen scoring are shown in (e). The highest ranking non-protease surface was from the DcmaT (h) binding surface aclacinomycin methylesterase (RdmC) from S. purpurascens (fg). A superposition of the surfaces based on the SurfaceAlign alignment (ij) and with their respective ligands (k).
Mentions: The binding surface of human HIV-1 (PDB:1eby, E.C. 3.4.23.16, CATH[39] 20.40.70.10, Figure 6ab) with bound inhibitor BEB (MW 652.7, Figure 6c) was selected as a query. First, the query was searched against the GPSS library using the SSS comparisons. The sorted KS distance scores between the query surface and all members from the library are plotted in Figure 6d. Points highlighted in red indicate known HIV-1 inhibitor binding surfaces. The results behave expectedly as 124 of 151 have KS distance scores less than 0.1. Plotting the search results in a receiver operator characteristic (ROC) curve (see Methods) we measure the retrieval rate using SSS at 84.7% from the area under the curve (AUC) (Figure 6e). The poorest ranking HIV-1 protease surfaces are associated with aggressive mutation studies in the binding pocket or correlated to decisively small (<200) or large (>900) molecular weight inhibitors.

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