Table 2.
Monte Carlo | s [1] | f/f0 [1] | % [1] | s [2] | f/f0 [2] | % [2] | RMSD |
---|---|---|---|---|---|---|---|
2DSA | 5.14 (4.74, 5.74) | 3.87 (3.11, 4.63) | 43.5 | 10.67 (10.21, 11.13) | 12.67 (1.71, 23.63) | 35.4 | 3.2146 |
GA | 5.15 (5.12, 5.18) | 3.71 (3.45, 3.97) | 46.7 | 10.66 (10.64, 10.68) | 11.25 (10.10, 12.39) | 35.3 | 3.2609 |
IS | 5.16 (4.56, 5.77) | 3.74 (3.21, 4.27) | 49.6 | 10.67 (10.26, 11.08) | 11.01 (10.38, 11.65) | 38.7 | 3.3697 |
SL | 5.05 (4.55, 5.55) | 3.95 (3.25, 4.65) | 44.6 | 10.67 (9.97, 11.38) | 9.74 (9.02, 10.46) | 40.2 | 3.4253 |
HL | 5.22 (1.44, 9.00) | 7.20 (0.00, 0.00) | 50.4 | 10.71 (9.84, 11.58) | 7.20 (0.00, 0.00) | 43.1 | 4.6832 |
One-hundred iteration Monte Carlo analyses were performed on 2DSA, genetic algorithms (GA), PCSA with an increasing sigmoid function (IS), straight-line parameterization (SL), and horizontal-line parameterization (HL). Ninety-five percent confidence limits are shown in parentheses. Numbers in square brackets refer to the fragment number in the DNA mixture. All values are corrected for conditions equivalent to water at 20°C. Two-dimensional pseudo-three-dimensional plots of each analysis are shown in Fig. S3, Fig. S4, Fig. S5, Fig. S6, and Fig. S7 in the Supporting Material. A large increase in RMSD is seen when PCSA-HL parameterization is used (compare also Fig. S2).