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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.F595L

Detailed results for job #oncokb produced by ELASPIC

P15056, Serine/threonine-protein kinase B-raf:
F595L
1
766
PAK2, Serine/threonine-protein kinase PAK 2:
1
524
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Model: Wild-type | Mutant | Both
Protein: P15056 | PAK2 | Cofactors | All
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P15056.F595L

Completed successfully

Protein, domain: P15056 Pkinase_Tyr

Interacting with: PAK2 PBD

PDB templates used: 1f3m_D, 1f3m_B

Seq identity: 0.287, 0.855 Model score: 0.215

ELASPIC ΔΔG: 1.491

ELASPIC2 (EL2) score: 1.963

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

Download:  PDBwt   | PDBmut

Citation


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