Table 1.
Sequence and structural alignment scores for two example alignments.
Levitt-Gerstein Structural Similarity | Sequence Alignment Score† | Shift Score vs. Dali | Levitt-Gerstein Structural Similarity | Sequence Alignment Score† | Shift Score vs. Dali | |
---|---|---|---|---|---|---|
Alignment | 1 hdaB00 vs. 1 mytA00 (pair 25) | 1bcgA00 vs. 1b7dA00 (pair 42) | ||||
CE | 2333 | 85 | 0.986 | 978 | 61 | 0.920 |
Matras | 2330 | 103 | 0.983 | 966 | 49 | - |
DALI | 2334 | 115 | 1.000 | 980 | 24 | 1.000 |
LSQMAN | 2337 | -20 | 0.946 | 980 | 24 | 0.940 |
Optimal Sequence§ | 2352 | 145 | 0.940 | 583 | 108 | 0.837 |
95% Neighborhood§ | 2355 | 145 | 0.900 | 696 | 104 | 0.880 |
75% Neighborhood§ | 2359 | 145 | 0.923 | 812 | 88 | 0.780 |
probA§ | 2362 | 37 | 0.645 | 830 | 37 | 0.757 |
robustness¶ | 2301 | -526 | 0.734 | 383 | 24 | 0.565 |
model¶ | 2352 | 145 | 0.941 | 579 | 108 | 0.796 |
†Semi-global alignment, Blosum50 substitution matrix, gap open penalty -10, gap extension penalty -2.
§ The sequence with the highest Levitt-Gerstein similarity score was chosen from the set of optimal alignments, the set of alignments with a sequence similarity score within 95% of optimal, the set of alignments with a sequence similarity score within 75% of optimal, and the set of probA alignments, and the sequence similarity score and shift score for that alignment were recorded.
¶Alignments were created using the log-odds score produced by a logistic regression model in place of a substitution matrix. "Robustness" refers to a model that had only robustness as an independent variable, while "model" refers to the full model (incorporating robustness, edge frequency, and maximum bits-per-position). See text for details.