Composite Motifs Integrating Multiple Protein Structures Increase Sensitivity for Function Prediction

Chen, Brian Y.; Bryant, Drew H.; Cruess, Amanda E.; Bylund, Joseph H.; Fofanov, Viacheslav Y.; Kristensen, David M.; Kimmel, Marek; Lichtarge, Olivier; Kavraki, Lydia E.

doi:10.1142/9781860948732_0035

Cited by 6 publications

(2 citation statements)

References 46 publications

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“…In order to obtain an accurate assessment of protein function, a number of emerging studies have shown that detecting similarity of local surface where substrate binding occurs can be very effective14–27. One method for predicting protein function based on local surface similarities is to structurally compare a surface pocket from the query protein against a database of template surface pockets from proteins with known functions.…”

Section: Introductionmentioning

confidence: 99%

Structural Signatures of Enzyme Binding Pockets from Order-Independent Surface Alignment: A Study of Metalloendopeptidase and NAD Binding Proteins

Dundas

Adamian

Liang

2011

Journal of Molecular Biology

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Detecting similarities between local binding surfaces can facilitate identification of enzyme binding sites, prediction of enzyme functions, as well as aid in our understanding of enzyme mechanisms. A challenging task is to construct a template of local surface characteristics for a specific enzyme function or binding activity, as the size and shape of binding surfaces of a biochemical function often varies. Here we introduce the concept of signature binding pockets, which captures information about preserved and varied atomic positions at multi-resolution levels. For proteins with complex enzyme binding and activity, multiple signatures arise naturally in our model, which form a signature basis set that characterize this class of proteins. Both signatures and signature basis set can be automatically constructed by a method called SOLAR (Signature Of Local Active Regions). This method is based on a sequence order independent alignment of computed binding surface pockets. SOLAR also provides a structure based multiple sequence fragment alignment (MSFA) to facilitate interpretation of computed signatures. For studying a family of evolutionary related proteins, we show that for metzincin metalloendopeptidase, which has a broad spectrum of substrate binding, signature and basis set pockets can be used to discriminate metzincins from other enzymes, to predict the subclass of enzyme functions, and to identify the specific binding surfaces. For studying unrelated proteins which have evolved to bind to the same NAD co-factor, signatures of NAD binding pockets can be constructed and can be used to predict NAD binding proteins and to locate NAD binding pockets. By measuring preservation ratio and location variation, our method can identify residues and atoms important for binding affinity and specificity. In both cases, we show that signatures and signature basis set reveal significant biological insight.

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Section: Introductionmentioning

confidence: 99%

Structural Signatures of Enzyme Binding Pockets from Order-Independent Surface Alignment: A Study of Metalloendopeptidase and NAD Binding Proteins

Dundas

Adamian

Liang

2011

Journal of Molecular Biology

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“…Collectively, the set of consensus motifs for all clusters composes a motif ensemble. Earlier work investigated the performance of averaging all substructures within a family to identify a single family consensus motif [ 62 ]. However, it was found that for large geometrically diverse families, a single representative motif, based on any family member substructure or a substructure average of all members, could not sufficiently represent the entire family, just as building a single profile HMM for a large number of distantly related sequences can be difficult.…”

Section: Resultsmentioning

confidence: 99%

Analysis of substructural variation in families of enzymatic proteins with applications to protein function prediction

et al. 2010

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BackgroundStructural variations caused by a wide range of physico-chemical and biological sources directly influence the function of a protein. For enzymatic proteins, the structure and chemistry of the catalytic binding site residues can be loosely defined as a substructure of the protein. Comparative analysis of drug-receptor substructures across and within species has been used for lead evaluation. Substructure-level similarity between the binding sites of functionally similar proteins has also been used to identify instances of convergent evolution among proteins. In functionally homologous protein families, shared chemistry and geometry at catalytic sites provide a common, local point of comparison among proteins that may differ significantly at the sequence, fold, or domain topology levels.ResultsThis paper describes two key results that can be used separately or in combination for protein function analysis. The Family-wise Analysis of SubStructural Templates (FASST) method uses all-against-all substructure comparison to determine Substructural Clusters (SCs). SCs characterize the binding site substructural variation within a protein family. In this paper we focus on examples of automatically determined SCs that can be linked to phylogenetic distance between family members, segregation by conformation, and organization by homology among convergent protein lineages. The Motif Ensemble Statistical Hypothesis (MESH) framework constructs a representative motif for each protein cluster among the SCs determined by FASST to build motif ensembles that are shown through a series of function prediction experiments to improve the function prediction power of existing motifs.ConclusionsFASST contributes a critical feedback and assessment step to existing binding site substructure identification methods and can be used for the thorough investigation of structure-function relationships. The application of MESH allows for an automated, statistically rigorous procedure for incorporating structural variation data into protein function prediction pipelines. Our work provides an unbiased, automated assessment of the structural variability of identified binding site substructures among protein structure families and a technique for exploring the relation of substructural variation to protein function. As available proteomic data continues to expand, the techniques proposed will be indispensable for the large-scale analysis and interpretation of structural data.

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Meng¹,

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From Protein Structure to Function With Bioinformatics

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Composite Motifs Integrating Multiple Protein Structures Increase Sensitivity for Function Prediction

Cited by 6 publications

References 46 publications

Structural Signatures of Enzyme Binding Pockets from Order-Independent Surface Alignment: A Study of Metalloendopeptidase and NAD Binding Proteins

Structural Signatures of Enzyme Binding Pockets from Order-Independent Surface Alignment: A Study of Metalloendopeptidase and NAD Binding Proteins

Analysis of substructural variation in families of enzymatic proteins with applications to protein function prediction

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