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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.

Q9UM73.M1166R

Detailed results for job #oncokb produced by ELASPIC

Q9UM73, ALK tyrosine kinase receptor:
M1166R
1
1620
MAP2K7, Dual specificity mitogen-activated protein kinase kinase 7:
1
419
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Protein: Q9UM73 | MAP2K7 | Cofactors | All
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Q9UM73.M1166R

Completed successfully

Protein, domain: Q9UM73 Pkinase_Tyr

Interacting with: MAP2K7 Pkinase

PDB templates used: 3qqu_C, 3qqu_B

Seq identity: 0.466, 0.236 Model score: 0.249

ELASPIC ΔΔG: 1.180

ELASPIC2 (EL2) score: 0.913

Mutation in databases: UniProt, COSMIC.

Download:  PDBwt   | PDBmut

Citation


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