Figure 1.
Relationship between the impact of positive design on the stability of different lattice folds and their respective average contact-frequencies.
The values of a measure of the effect of positive design of stability, <D(i,j)>short, for the 1081 different folds of 25 residue-long sequences on a 5×5 lattice are plotted against their respective average contact-frequencies, . A linear correlation is observed with r = −0.6082 and a P-value<0.0001.
Figure 2.
Relationship between the impact of negative design on the stability of different lattice folds and their respective average contact-frequencies.
The values of a measure of the effect of negative design of stability, <D(i,j)>long, for the 1081 different folds of 25 residue-long sequences on a 5×5 lattice are plotted against their respective average contact-frequencies, . A linear correlation is observed with r = 0.6390 and a P-value<0.0001.
Figure 3.
Trade-off between the effects of positive and negative design on the stabilities of different lattice folds.
The values of a measure of the effect of negative design of stability, <D(i,j)>long, for the 1081 different folds of 25 residue-long sequences on a 5×5 lattice are plotted against their respective values of a measure of the effect of positive design of stability, <D(i,j)>short. A linear correlation is observed with r = −0.96 and a P-value<0.0001.
Table 1.
Comparison between the correlated mutation densities averaged for all the alignments corresponding to the different sets examined.
Figure 4.
Distributions of densities of correlated mutations at positions involved in long-range interactions for different classes of lattice folds with increasing values of average contact-frequency.
The 1081 different folds of 25 residue-long sequences on a 5×5 lattice were ordered according to their average contact frequency, (), and then divided into three equal-sized groups comprising the folds with the lowest (A), in between (B) and highest (C) values of
, respectively. It can be seen that the density of correlated mutations tends to increase as the average contact-frequency of the fold increases.
Figure 5.
Distributions of correlated mutation densities in the case of the five different sets of real proteins examined in this study.
The densities of correlated mutations were calculated for the sets of control proteins (A), classes I (B), II (C) and III (D) of the GroEL-interacting proteins and the intrinsically unstructured proteins (E). It can be seen that the density of correlated mutations of these sets increases with the increasing likelihood that their average ‘contact-frequency’ has increased.