Limits...
Assessing the ability of sequence-based methods to provide functional insight within membrane integral proteins: a case study analyzing the neurotransmitter/Na+ symporter family.

Livesay DR, Kidd PD, Eskandari S, Roshan U - BMC Bioinformatics (2007)

Bottom Line: The resultant phylogenetic trees always contain six major subfamilies are consistent with the functional diversity across the family.Interestingly, the various prediction schemes provide results that are predominantly orthogonal to each other.The results presented herein clearly establish the viability of sequence-based bioinformatic strategies to provide functional insight within the NSS family.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Computer Science and Bioinformatics Research Center, University of North Carolina at Charlotte, Charlotte, NC 28262, USA. drlivesa@uncc.edu

ABSTRACT

Background: Efforts to predict functional sites from globular proteins is increasingly common; however, the most successful of these methods generally require structural insight. Unfortunately, despite several recent technological advances, structural coverage of membrane integral proteins continues to be sparse. ConSequently, sequence-based methods represent an important alternative to illuminate functional roles. In this report, we critically examine the ability of several computational methods to provide functional insight within two specific areas. First, can phylogenomic methods accurately describe the functional diversity across a membrane integral protein family? And second, can sequence-based strategies accurately predict key functional sites? Due to the presence of a recently solved structure and a vast amount of experimental mutagenesis data, the neurotransmitter/Na+ symporter (NSS) family is an ideal model system to assess the quality of our predictions.

Results: The raw NSS sequence dataset contains 181 sequences, which have been aligned by various methods. The resultant phylogenetic trees always contain six major subfamilies are consistent with the functional diversity across the family. Moreover, in well-represented subfamilies, phylogenetic clustering recapitulates several nuanced functional distinctions. Functional sites are predicted using six different methods (phylogenetic motifs, two methods that identify subfamily-specific positions, and three different conservation scores). A canonical set of 34 functional sites identified by Yamashita et al. within the recently solved LeuTAa structure is used to assess the quality of the predictions, most of which are predicted by the bioinformatic methods. Remarkably, the importance of these sites is largely confirmed by experimental mutagenesis. Furthermore, the collective set of functional site predictions qualitatively clusters along the proposed transport pathway, further demonstrating their utility. Interestingly, the various prediction schemes provide results that are predominantly orthogonal to each other. However, when the methods do provide overlapping results, specificity is shown to increase dramatically (e.g., sites predicted by any three methods have both accuracy and coverage greater than 50%).

Conclusion: The results presented herein clearly establish the viability of sequence-based bioinformatic strategies to provide functional insight within the NSS family. As such, we expect similar bioinformatic investigations will streamline functional investigations within membrane integral families in the absence of structure.

Show MeSH

Related in: MedlinePlus

The entire LeuTAa structure is shown with the α-carbons of the 34 known functional sites highlighted; the binding site residues are colored red, cytoplasmic gate residues are colored green, and extracellular/periplasmic gate residues are colored purple. The leucine substrate and sodium ions are rendered in spacefill and colored blue.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC2194793&req=5

Figure 4: The entire LeuTAa structure is shown with the α-carbons of the 34 known functional sites highlighted; the binding site residues are colored red, cytoplasmic gate residues are colored green, and extracellular/periplasmic gate residues are colored purple. The leucine substrate and sodium ions are rendered in spacefill and colored blue.

Mentions: From the LeuTAa structure (see Figure 4), a canonical set of 34 functional sites has been identified [10]. The functional sites include the two unwound transmembrane helices (TM1 and TM6) at the leucine-binding site, residues directly involved in substrate binding, two Na+ binding sites, two extended interaction networks at the cytoplasmic and extracellular gates, and one residue (Glu62) that stabilizes the unwound TM6 helix. The 34 functional sites are detailed in Table 2. Here, we apply six different functional site prediction strategies (see Methods for details). The six methods are based on phylogenetic motifs [43], conserved motifs [43], individual site conservation, the Consurf [44] conservation algorithm (which is called Rate4Site [45]), evolutionary trace [46], and prediction of specificity determining positions [47]. Table 3 describes each method's performance on the complete benchmark, whereas Table 4 provides performance assessment across the structurally observed binding sites, the predicted cytoplasmic gate residues and the predicted extracellular/periplasmic gate residues.


Assessing the ability of sequence-based methods to provide functional insight within membrane integral proteins: a case study analyzing the neurotransmitter/Na+ symporter family.

Livesay DR, Kidd PD, Eskandari S, Roshan U - BMC Bioinformatics (2007)

The entire LeuTAa structure is shown with the α-carbons of the 34 known functional sites highlighted; the binding site residues are colored red, cytoplasmic gate residues are colored green, and extracellular/periplasmic gate residues are colored purple. The leucine substrate and sodium ions are rendered in spacefill and colored blue.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2194793&req=5

Figure 4: The entire LeuTAa structure is shown with the α-carbons of the 34 known functional sites highlighted; the binding site residues are colored red, cytoplasmic gate residues are colored green, and extracellular/periplasmic gate residues are colored purple. The leucine substrate and sodium ions are rendered in spacefill and colored blue.
Mentions: From the LeuTAa structure (see Figure 4), a canonical set of 34 functional sites has been identified [10]. The functional sites include the two unwound transmembrane helices (TM1 and TM6) at the leucine-binding site, residues directly involved in substrate binding, two Na+ binding sites, two extended interaction networks at the cytoplasmic and extracellular gates, and one residue (Glu62) that stabilizes the unwound TM6 helix. The 34 functional sites are detailed in Table 2. Here, we apply six different functional site prediction strategies (see Methods for details). The six methods are based on phylogenetic motifs [43], conserved motifs [43], individual site conservation, the Consurf [44] conservation algorithm (which is called Rate4Site [45]), evolutionary trace [46], and prediction of specificity determining positions [47]. Table 3 describes each method's performance on the complete benchmark, whereas Table 4 provides performance assessment across the structurally observed binding sites, the predicted cytoplasmic gate residues and the predicted extracellular/periplasmic gate residues.

Bottom Line: The resultant phylogenetic trees always contain six major subfamilies are consistent with the functional diversity across the family.Interestingly, the various prediction schemes provide results that are predominantly orthogonal to each other.The results presented herein clearly establish the viability of sequence-based bioinformatic strategies to provide functional insight within the NSS family.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Computer Science and Bioinformatics Research Center, University of North Carolina at Charlotte, Charlotte, NC 28262, USA. drlivesa@uncc.edu

ABSTRACT

Background: Efforts to predict functional sites from globular proteins is increasingly common; however, the most successful of these methods generally require structural insight. Unfortunately, despite several recent technological advances, structural coverage of membrane integral proteins continues to be sparse. ConSequently, sequence-based methods represent an important alternative to illuminate functional roles. In this report, we critically examine the ability of several computational methods to provide functional insight within two specific areas. First, can phylogenomic methods accurately describe the functional diversity across a membrane integral protein family? And second, can sequence-based strategies accurately predict key functional sites? Due to the presence of a recently solved structure and a vast amount of experimental mutagenesis data, the neurotransmitter/Na+ symporter (NSS) family is an ideal model system to assess the quality of our predictions.

Results: The raw NSS sequence dataset contains 181 sequences, which have been aligned by various methods. The resultant phylogenetic trees always contain six major subfamilies are consistent with the functional diversity across the family. Moreover, in well-represented subfamilies, phylogenetic clustering recapitulates several nuanced functional distinctions. Functional sites are predicted using six different methods (phylogenetic motifs, two methods that identify subfamily-specific positions, and three different conservation scores). A canonical set of 34 functional sites identified by Yamashita et al. within the recently solved LeuTAa structure is used to assess the quality of the predictions, most of which are predicted by the bioinformatic methods. Remarkably, the importance of these sites is largely confirmed by experimental mutagenesis. Furthermore, the collective set of functional site predictions qualitatively clusters along the proposed transport pathway, further demonstrating their utility. Interestingly, the various prediction schemes provide results that are predominantly orthogonal to each other. However, when the methods do provide overlapping results, specificity is shown to increase dramatically (e.g., sites predicted by any three methods have both accuracy and coverage greater than 50%).

Conclusion: The results presented herein clearly establish the viability of sequence-based bioinformatic strategies to provide functional insight within the NSS family. As such, we expect similar bioinformatic investigations will streamline functional investigations within membrane integral families in the absence of structure.

Show MeSH
Related in: MedlinePlus