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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.Y1278S

Detailed results for job #oncokb produced by ELASPIC

Q9UM73, ALK tyrosine kinase receptor:
Y1278S
1
1620
JAK3, Tyrosine-protein kinase JAK3:
1
1124
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Protein: Q9UM73 | JAK3 | Cofactors | All
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Q9UM73.Y1278S

Completed successfully

Protein, domain: Q9UM73 Pkinase_Tyr

Interacting with: JAK3 Pkinase_Tyr

PDB templates used: 2zm3_B, 2zm3_C

Seq identity: 0.444, 0.265 Model score: 0.594

ELASPIC ΔΔG: -0.144

ELASPIC2 (EL2) score: 1.914

Mutation in databases: UniProt, COSMIC.

Download:  PDBwt   | PDBmut

Citation


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