Fig. 2. Numerical simulation of hydropathy tuning. (A,
B, C) Simulated sequences in the absence of hydropathy tuning and(D, E, F) when hydropathy is tuned by B. Error bars indicate
the 95 % confidence interval within which values were obtained among
all runs. (A, D) Relative variances of hydropathies. Variances
were calculated for hydropathies of complete sequences («All») and for
hydropathies of sequences from which the indicated amino acid was
removed. The dashed line indicates the hydropathy variance of complete
sequences as a visual reference. (B, E) Correlations between
amino acid content and hydropathy based on Spearman’s rank correlation
coefficient (ρ). (C, F) Correlations between amino acid content
and hydropathy calculated without given amino acid. Only correlations
for the hydrophobic amino acids A, B and C are shown in bar plots B, C,
E and F. The generic hydrophilic amino acid D displayed strong positive
correlations in each case.
The results confirm the anticipated effects for hydropathy tuning: the
variation between hydropathies increases when calculated without the
tuning amino acid (Fig. 2D) and a positive correlation exists between
the content of the tuning amino acid and the hydropathy calculated
without this amino acid (Fig. 2F). Further, the simulation shows the
degree to which the effects are present when only a fraction of the
tuning amino acid is driving the hydropathy towards the optimum value.
The fdrive of 0.25 leads to similar patterns as were
observed within the sequences of class A GPCR TMDs, supporting the idea
that Leu is responsible for adjusting the hydropathy of these TMDs.
Interestingly, the numerical model also captures the overall patterns of
Ile within the TMD sequences. In the simulation, A was modeled after Ile
and its content was determined by a Gaussian distribution alone,
suggesting that Ile is not involved in tuning TMD hydropathy in class A
GPCRs.