Our work used datasets S1676, S236, S543 to investigate the prediction of stability changes on protein (Table S1).
Table S1 Datasets used to build, evaluate and independently test in SCpre-seq
Dataset | Total Variants (Proteins) | Destabilizing Variants (Proteins) | Stabilizing Variants (Proteins) | Stabilizing Variants (Proteins) | Additional Details |
---|---|---|---|---|---|
S1676 | 1676 (67) | 1,223 (64) | 424 (53) | 29(4) | Unique Variants/Averaged DDG |
S236 | 236 (22) | 192 (18) | 42 (14) | 2(2) | Unique Variants/Averaged DDG |
S543 | 543(55) | 426(48) | 107(37) | 10(6) | Unique Variants/Averaged DDG |
p53 | 42 (1) | 31(1) | 11 (1) | 0 | One Protein |
Folkman, L., et al., EASE-MM: Sequence-Based Prediction of Mutation-Induced Stability Changes with Feature-Based Multiple Models. J Mol Biol, 2016. 428(6): p. 1394-1405.
Pires, D.E., D.B. Ascher, and T.L. Blundell, mCSM: predicting the effects of mutations in proteins using graph-based signatures. Bioinformatics, 2014. 30(3): p. 335-42.
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