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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.

P15056.G478C

Detailed results for job #oncokb produced by ELASPIC

P15056, Serine/threonine-protein kinase B-raf:
G478C
1
766
MAP3K1, Mitogen-activated protein kinase kinase kinase 1:
1
1512
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Model: Wild-type | Mutant | Both
Protein: P15056 | MAP3K1 | Cofactors | All
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P15056.G478C

Completed successfully

Protein, domain: P15056 Pkinase_Tyr

Interacting with: MAP3K1 Pkinase

PDB templates used: 4e26_B, 4e26_A

Seq identity: 0.960, 0.275 Model score: -0.221

ELASPIC ΔΔG: 2.620

ELASPIC2 (EL2) score: 1.912

Mutation run by user.

Download:  PDBwt   | PDBmut

Citation


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