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Results: 7

1.
Figure 4

Figure 4. The ROC curves of different features/predictors.. From: Identification of Catalytic Residues Using a Novel Feature that Integrates the Microenvironment and Geometrical Location Properties of Residues.

Panel A gives the ROC curves at each possible control of false positive rate, while panel B only plots ROC curves at a false positive rate ≤10%.

Lei Han, et al. PLoS One. 2012;7(7):e41370.
2.
Figure 5

Figure 5. The relationship between Dscore and Closeness.. From: Identification of Catalytic Residues Using a Novel Feature that Integrates the Microenvironment and Geometrical Location Properties of Residues.

The red points denote catalytic residues, while the blue points represent the non-catalytic residues. The correlation coefficient between Dscore and Closeness is 0.946 as derived by regression equation (i.e. the green line).

Lei Han, et al. PLoS One. 2012;7(7):e41370.
3.
Figure 3

Figure 3. The distribution of MEscores.. From: Identification of Catalytic Residues Using a Novel Feature that Integrates the Microenvironment and Geometrical Location Properties of Residues.

Panel A and Panel B represent the distributions of MEscore in catalytic and non-catalytic residues, respectively. The pink triangle in x-axis represents the average MEscore of all residues in the enzyme dataset, while the red (Panel A) and blue triangle (Panel B) denote the average MEscores of catalytic residues and non-catalytic residues, respectively.

Lei Han, et al. PLoS One. 2012;7(7):e41370.
4.
Figure 6

Figure 6. Venn diagrams showing the numbers of catalytic residues identified at a false positive rate ≤10%.. From: Identification of Catalytic Residues Using a Novel Feature that Integrates the Microenvironment and Geometrical Location Properties of Residues.

Panel A shows the overlapping predictions by three different features (Dscore, Closeness and MEscore), and panel B summarizes the prediction results by MEDscore and CONscore.

Lei Han, et al. PLoS One. 2012;7(7):e41370.
5.
Figure 2

Figure 2. The weight coefficients of spatially neighboring residue pairs in the MEs of catalytic residues.. From: Identification of Catalytic Residues Using a Novel Feature that Integrates the Microenvironment and Geometrical Location Properties of Residues.

The x-axis denotes different catalytic amino acids and the y-axis represents the corresponding neighboring residue types occurring in the MEs of catalytic residues. A weight coefficient close to maximum value is color-coded in blue, and it varies continuously to white color as equal to 0.0. Note that the weight coefficients were derived from the whole enzyme dataset (i.e. the 223 enzymes used in this work).

Lei Han, et al. PLoS One. 2012;7(7):e41370.
6.
Figure 1

Figure 1. Propensities of 20 amino acids in their roles as catalytic residues and their spatially neighboring residues.. From: Identification of Catalytic Residues Using a Novel Feature that Integrates the Microenvironment and Geometrical Location Properties of Residues.

The catalytic propensity of any residue is defined as its frequency been a catalytic residue minus its corresponding background frequency. Likewise, the propensity of any residue as catalytic residues' neighbor is defined as its frequency in the MEs of catalytic residues minus the corresponding background frequency. A positive bar means that the residue is enriched, while a negative bar means that the residue is depleted. The distance cutoff (Rcutoff) values, ranging from 4 to 11 Å at an interval of 1Å, were used to calculate the structural neighbors of catalytic residues. All the residues in the enzyme dataset were used to calculate the background frequency.

Lei Han, et al. PLoS One. 2012;7(7):e41370.
7.
Figure 7

Figure 7. Two case studies illustrating the prediction performance of different features at a false positive rate control of 3%.. From: Identification of Catalytic Residues Using a Novel Feature that Integrates the Microenvironment and Geometrical Location Properties of Residues.

Panel A shows the predicted catalytic residues of TrpG (the small domain of anthranilate synthase; PDB entry: 1QDL), and panel B gives the predictions of diaminopimelate (DAP) epimerase (PDB entry: 1BWZ). Top parts: Protein structures are represented by cartoon ribbons and the corresponding catalytic residues are highlighted by ball-and-stick-models, as seen in the insets. Lower parts: The blue triangles represent the sequence positions of the catalytic residues. With respect to the prediction results of each feature, the sequence positions of the predicted catalytic residues are marked using colored bars, with a higher score corresponding to a more saturated color. The black bars denote catalytic residues which a corresponding feature failed to predict.

Lei Han, et al. PLoS One. 2012;7(7):e41370.

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