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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.

Q02750.S222D

Detailed results for job #oncokb produced by ELASPIC

Q02750, Dual specificity mitogen-activated protein kinase kinase 1:
S222D
1
393
PAK1, Serine/threonine-protein kinase PAK 1:
1
545
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Model: Wild-type | Mutant | Both
Protein: Q02750 | PAK1 | Cofactors | All
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Q02750.S222D

Completed successfully

Protein, domain: Q02750 Pkinase

Interacting with: PAK1 Pkinase

PDB templates used: 4o0r_B, 4o0r_A

Seq identity: 0.285, 0.993 Model score: 0.138

ELASPIC ΔΔG: 0.269

ELASPIC2 (EL2) score: 1.541

Mutation run by user.

Download:  PDBwt   | PDBmut

Citation


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