Relationship between Metabolic Fluxes and Sequence-Derived Properties of Enzymes
Table 2
Elements and the statistical indices for multiple linear regression models which link the values of metabolic fluxes and the average AA property for the yeast Saccharomyces cerevisiae enzyme sequences, expressed according to the VARIMAX scales.
Model
Dependenta variable
Parametersb
Regression coefficient (standardized value)
S.E.
value
value
, % , %
VIFc
I
Metabolic flux (Teusink's model)
Constant
142.527
3.150
45.25
0.0000
94.46
93.32
1749.250 (1.141)
80.843
21.64
0.0000
1.71
−1347.310 (−0.948)
86.853
−15.51
0.0000
2.29
()2
−1234.03 (−0.540)
124.491
−9.91
0.0000
1.82
()2
−11296.70 (−0.310)
1930.380
−5.85
0.0000
1.73
()2
−6350.430 (−0.289)
1137.530
−5.58
0.0000
1.64
202.670 (0.222)
48.639
4.17
0.0002
1.74
44.481 (0.125)
17.534
2.54
0.0159
1.50
II
Metabolic flux (Hynne's model)
Constant
70.629
3.394
20.81
0.0000
94.20
92.91
()2
−0.780 (−0.638)
0.081
−9.65
0.0000
2.71
8.965 (1.028)
0.575
15.60
0.0000
2.70
−0.836 (−0.396)
0.112
−7.47
0.0000
1.74
()2
−0.083 (−0.610)
0.008
−10.11
0.0000
2.26
()2
−0.787 (−0.618)
0.076
−10.31
0.0000
2.23
−3.874 (−0.581)
0.383
−10.11
0.0000
2.05
2.683 (0.505)
0.311
8.63
0.0000
2.12
()2
−0.085 (−0.414)
0.014
−5.97
0.0000
2.99
Represent the mean values of metabolic fluxes within the range of external glucose concentrations as specified in the “Material and Methods”.
bElements of multiple linear regression which represent the average AA property, as specified in the Table 1, of the yeast Saccharomyces cerevisiae enzyme sequences and the constant (intercept) of equation.
cThe variance inflation factor which indicates the impact of collinearity between the independent variables [22].
