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.