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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.


Three histidine residues from histidinol phosphate phosphatase (HPP) (PDB 2yz5) were analyzed by THEMATICS to produce theoretical titration curves (A), which plot the mean net charge of a given residue of a large ensemble of protein molecules as a function of pH, and first derivative plots (B).The titration curves of two non-catalytic residues, H84 and H150, show sigmoidal curve shapes with a small buffer range, while the catalytic H226 displays a curve with an anomalous shape, shallow slope, and larger buffer range. When analyzing the first derivatives of the titration curves, non-catalytic residues display symmetrical, highly peaked plots. However, active site residues such as H226 shown here display broad, asymmetric derivative plots and may have multiple peaks.
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f0005: Three histidine residues from histidinol phosphate phosphatase (HPP) (PDB 2yz5) were analyzed by THEMATICS to produce theoretical titration curves (A), which plot the mean net charge of a given residue of a large ensemble of protein molecules as a function of pH, and first derivative plots (B).The titration curves of two non-catalytic residues, H84 and H150, show sigmoidal curve shapes with a small buffer range, while the catalytic H226 displays a curve with an anomalous shape, shallow slope, and larger buffer range. When analyzing the first derivatives of the titration curves, non-catalytic residues display symmetrical, highly peaked plots. However, active site residues such as H226 shown here display broad, asymmetric derivative plots and may have multiple peaks.

Mentions: THEoretical Microscopic Anomalous TItration Curve Shapes (or THEMATICS) [53–55], a functional site prediction method, is able to predict accurately the ionizable active site residues within a given protein using only the 3D structure of the query protein. THEMATICS identifies ionizable amino acid residues (Arg, Asp, Cys, Glu, His, Lys, and Tyr, plus the N- and C- termini) that participate in catalysis or ligand recognition. The ionizable side chains of amino acid residues in protein active sites exhibit unusual electrostatic properties, specifically theoretical titration curves as shown in Fig. 1. These curves are obtained by approximate calculation of the electrostatic potential function, followed by a calculation of the average charge of each ionizable residue as a function of pH. These theoretical titration curves of active site residues are perturbed from the normal sigmoidal shape that is characteristic of the Brönsted acid–base chemistry of the free amino acid [53]. In a normal titration curve, the proton occupation is one at low pH and as the pH is increased, the proton occupation suddenly drops sharply around the pKa, approaching zero at higher pH. Normally this transition, where both the protonated and deprotonated forms exist in appreciable population, occurs in a narrow pH range. However, the residues within the active site tend to be partially protonated over a larger pH range and in this manner the shape of the titration curve is perturbed [53]. This method has been described previously as based on computed pKa shifts [38,56]; however, this is incorrect. Only metrics that characterize the shape of the titration curves, and not the pKa shifts, are used in the THEMATICS predictions. The degree of deviation of a catalytic ionizable residue from the typical Henderson–Hasselbalch titration curve can be quantified by the moments of the first derivative of the curve [57]. This method has been tested on the Catalytic Site Atlas (CSA) 100, and THEMATICS-predicted residues have been shown to constitute good predictions of the active site for proteins in the benchmark set [55]; they have also been shown to be generally well conserved [58].


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

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

Three histidine residues from histidinol phosphate phosphatase (HPP) (PDB 2yz5) were analyzed by THEMATICS to produce theoretical titration curves (A), which plot the mean net charge of a given residue of a large ensemble of protein molecules as a function of pH, and first derivative plots (B).The titration curves of two non-catalytic residues, H84 and H150, show sigmoidal curve shapes with a small buffer range, while the catalytic H226 displays a curve with an anomalous shape, shallow slope, and larger buffer range. When analyzing the first derivatives of the titration curves, non-catalytic residues display symmetrical, highly peaked plots. However, active site residues such as H226 shown here display broad, asymmetric derivative plots and may have multiple peaks.
© Copyright Policy - CC BY
Related In: Results  -  Collection

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

f0005: Three histidine residues from histidinol phosphate phosphatase (HPP) (PDB 2yz5) were analyzed by THEMATICS to produce theoretical titration curves (A), which plot the mean net charge of a given residue of a large ensemble of protein molecules as a function of pH, and first derivative plots (B).The titration curves of two non-catalytic residues, H84 and H150, show sigmoidal curve shapes with a small buffer range, while the catalytic H226 displays a curve with an anomalous shape, shallow slope, and larger buffer range. When analyzing the first derivatives of the titration curves, non-catalytic residues display symmetrical, highly peaked plots. However, active site residues such as H226 shown here display broad, asymmetric derivative plots and may have multiple peaks.
Mentions: THEoretical Microscopic Anomalous TItration Curve Shapes (or THEMATICS) [53–55], a functional site prediction method, is able to predict accurately the ionizable active site residues within a given protein using only the 3D structure of the query protein. THEMATICS identifies ionizable amino acid residues (Arg, Asp, Cys, Glu, His, Lys, and Tyr, plus the N- and C- termini) that participate in catalysis or ligand recognition. The ionizable side chains of amino acid residues in protein active sites exhibit unusual electrostatic properties, specifically theoretical titration curves as shown in Fig. 1. These curves are obtained by approximate calculation of the electrostatic potential function, followed by a calculation of the average charge of each ionizable residue as a function of pH. These theoretical titration curves of active site residues are perturbed from the normal sigmoidal shape that is characteristic of the Brönsted acid–base chemistry of the free amino acid [53]. In a normal titration curve, the proton occupation is one at low pH and as the pH is increased, the proton occupation suddenly drops sharply around the pKa, approaching zero at higher pH. Normally this transition, where both the protonated and deprotonated forms exist in appreciable population, occurs in a narrow pH range. However, the residues within the active site tend to be partially protonated over a larger pH range and in this manner the shape of the titration curve is perturbed [53]. This method has been described previously as based on computed pKa shifts [38,56]; however, this is incorrect. Only metrics that characterize the shape of the titration curves, and not the pKa shifts, are used in the THEMATICS predictions. The degree of deviation of a catalytic ionizable residue from the typical Henderson–Hasselbalch titration curve can be quantified by the moments of the first derivative of the curve [57]. This method has been tested on the Catalytic Site Atlas (CSA) 100, and THEMATICS-predicted residues have been shown to constitute good predictions of the active site for proteins in the benchmark set [55]; they have also been shown to be generally well conserved [58].

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.