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Biochemical functional predictions for protein structures of unknown or uncertain function.

Mills CL, Beuning PJ, Ondrechen MJ - Comput Struct Biotechnol J (2015)

Bottom Line: In addition, the combination of different types of methods can help obtain more information and better predictions of function for proteins of unknown function.Global initiatives, including the Enzyme Function Initiative (EFI), COMputational BRidges to EXperiments (COMBREX), and the Critical Assessment of Function Annotation (CAFA), are evaluating and testing the different approaches to predicting the function of proteins of unknown function.These initiatives and global collaborations will increase the capability and reliability of methods to predict biochemical function computationally and will add substantial value to the current volume of structural genomics data by reducing the number of absent or inaccurate functional annotations.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, United States.

ABSTRACT
With the exponential growth in the determination of protein sequences and structures via genome sequencing and structural genomics efforts, there is a growing need for reliable computational methods to determine the biochemical function of these proteins. This paper reviews the efforts to address the challenge of annotating the function at the molecular level of uncharacterized proteins. While sequence- and three-dimensional-structure-based methods for protein function prediction have been reviewed previously, the recent trends in local structure-based methods have received less attention. These local structure-based methods are the primary focus of this review. Computational methods have been developed to predict the residues important for catalysis and the local spatial arrangements of these residues can be used to identify protein function. In addition, the combination of different types of methods can help obtain more information and better predictions of function for proteins of unknown function. Global initiatives, including the Enzyme Function Initiative (EFI), COMputational BRidges to EXperiments (COMBREX), and the Critical Assessment of Function Annotation (CAFA), are evaluating and testing the different approaches to predicting the function of proteins of unknown function. These initiatives and global collaborations will increase the capability and reliability of methods to predict biochemical function computationally and will add substantial value to the current volume of structural genomics data by reducing the number of absent or inaccurate functional annotations.

No MeSH data available.


The metabolites above dock in silico into Tm0936 and are substrates of the enzyme Tm0936. The general structure of these three metabolites is the same with the exception of the moieties shown in the boxes.
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f0025: The metabolites above dock in silico into Tm0936 and are substrates of the enzyme Tm0936. The general structure of these three metabolites is the same with the exception of the moieties shown in the boxes.

Mentions: Another successful docking study, performed by one of the Bridging Projects, aided in assigning function to Thermotoga maritima Tm0936, a member of the AH superfamily whose function was previously unknown. Tm0936 was predicted to have a novel function as an S-adenosylhomocysteine deaminase [91]. This study involved docking thousands of metabolites into Tm0936 and creating a target list comprising adenine analogues. Five potential substrates were chosen based on availability and rank within the docking study; of these, the enzyme had significant activity with three: adenosine, 5-methylthioadenosine (MTA), and S-adenosylhomocysteine (SAH) (Fig. 5). It was concluded that this enzyme is involved in the deamination of metabolites within the MTA/SAH pathway.


Biochemical functional predictions for protein structures of unknown or uncertain function.

Mills CL, Beuning PJ, Ondrechen MJ - Comput Struct Biotechnol J (2015)

The metabolites above dock in silico into Tm0936 and are substrates of the enzyme Tm0936. The general structure of these three metabolites is the same with the exception of the moieties shown in the boxes.
© Copyright Policy - CC BY
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4372640&req=5

f0025: The metabolites above dock in silico into Tm0936 and are substrates of the enzyme Tm0936. The general structure of these three metabolites is the same with the exception of the moieties shown in the boxes.
Mentions: Another successful docking study, performed by one of the Bridging Projects, aided in assigning function to Thermotoga maritima Tm0936, a member of the AH superfamily whose function was previously unknown. Tm0936 was predicted to have a novel function as an S-adenosylhomocysteine deaminase [91]. This study involved docking thousands of metabolites into Tm0936 and creating a target list comprising adenine analogues. Five potential substrates were chosen based on availability and rank within the docking study; of these, the enzyme had significant activity with three: adenosine, 5-methylthioadenosine (MTA), and S-adenosylhomocysteine (SAH) (Fig. 5). It was concluded that this enzyme is involved in the deamination of metabolites within the MTA/SAH pathway.

Bottom Line: In addition, the combination of different types of methods can help obtain more information and better predictions of function for proteins of unknown function.Global initiatives, including the Enzyme Function Initiative (EFI), COMputational BRidges to EXperiments (COMBREX), and the Critical Assessment of Function Annotation (CAFA), are evaluating and testing the different approaches to predicting the function of proteins of unknown function.These initiatives and global collaborations will increase the capability and reliability of methods to predict biochemical function computationally and will add substantial value to the current volume of structural genomics data by reducing the number of absent or inaccurate functional annotations.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, United States.

ABSTRACT
With the exponential growth in the determination of protein sequences and structures via genome sequencing and structural genomics efforts, there is a growing need for reliable computational methods to determine the biochemical function of these proteins. This paper reviews the efforts to address the challenge of annotating the function at the molecular level of uncharacterized proteins. While sequence- and three-dimensional-structure-based methods for protein function prediction have been reviewed previously, the recent trends in local structure-based methods have received less attention. These local structure-based methods are the primary focus of this review. Computational methods have been developed to predict the residues important for catalysis and the local spatial arrangements of these residues can be used to identify protein function. In addition, the combination of different types of methods can help obtain more information and better predictions of function for proteins of unknown function. Global initiatives, including the Enzyme Function Initiative (EFI), COMputational BRidges to EXperiments (COMBREX), and the Critical Assessment of Function Annotation (CAFA), are evaluating and testing the different approaches to predicting the function of proteins of unknown function. These initiatives and global collaborations will increase the capability and reliability of methods to predict biochemical function computationally and will add substantial value to the current volume of structural genomics data by reducing the number of absent or inaccurate functional annotations.

No MeSH data available.