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ELASPIC ΔΔG
The final Gibbs free energy change (ΔΔG) in kcal/mol is predicted using more than 70 sequential, molecular and energetic features with the Stochastic Gradient Boosting of Decision Trees algorithm.
For more information see the ELASPIC publication.
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ELASPIC2 (EL2) score
The ELASPIC2 (EL2) score is obtained using features generated by pretrained ProteinSolver and ProtBert neural networks with the Stochastic Gradient Boosting of Decision Trees algorithm and a ranking objective function.
For more information see the ELASPIC2 (EL2) publication.

P04637.H178D

Detailed results for job #oncokb produced by ELASPIC

P04637, Cellular tumor antigen p53:
H178D
1
393
TP53, Cellular tumor antigen p53:
1
393
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Protein: P04637 | TP53 | Cofactors | All
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P04637.H178D

Completed successfully

Protein, domain: P04637 P53+P53_tetramer

Interacting with: TP53 P53+P53_tetramer

PDB templates used: 4ibt_B, 4ibt_A

Seq identity: 0.990, 0.990 Model score: -0.607

ELASPIC ΔΔG: 3.857

ELASPIC2 (EL2) score: -0.544

Mutation in databases: UniProt, COSMIC, COSMIC, COSMIC, COSMIC.

Download:  PDBwt   | PDBmut

Citation


If you use these results, please cite the papers on this page.