› 5z1d

X-ray diffraction
2.28Å resolution

MAP2K7 C276S mutant-inhibitor

Released:
DOI: 10.2210/pdb5z1d/pdb
PDB entry 5z1d coloured by chain, front view.
PDB entry 5z1d coloured by chain, side view.
PDB entry 5z1d coloured by chain, top view.
Source organism: Homo sapiens
Primary publication:
Covalent Docking Identifies a Potent and Selective MKK7 Inhibitor.
Shraga A, Olshvang E, Davidzohn N, Khoshkenar P, Germain N, Shurrush K, Carvalho S, Avram L, Albeck S, Unger T, Lefker B, Subramanyam C, Hudkins RL, Mitchell A, Shulman Z, Kinoshita T, London N
Cell Chem Biol 26 98-108.e5 (2019)
PMID: 30449673

Function and Biology Details

Reaction catalysed: 
ATP + L-seryl/L-threonyl/L-tyrosyl-[protein] = ADP + O-phospho-L-seryl/O-phospho-L-threonyl/O-phospho-L-tyrosyl-[protein]
Biochemical function:
Biological process:
Cellular component:
  • not assigned
Sequence domains:

Structure analysis Details

Assembly composition:
monomeric (preferred)
Assembly name:
PDBe Complex ID:
PDB-CPX-127070 (preferred)
Entry contents:
1 distinct polypeptide molecule
Macromolecule:
Dual specificity mitogen-activated protein kinase kinase 7 Chain: A
Molecule details ›
Chain: A
Length: 324 amino acids
Theoretical weight: 36.98 KDa
Source organism: Homo sapiens
Expression system: Escherichia coli B
UniProt:
  • Canonical: O14733 (Residues: 102-419; Coverage: 76%)
Gene names: JNKK2, MAP2K7, MEK7, MKK7, PRKMK7, SKK4
Sequence domains: Protein kinase domain
Structure domains: Transferase(Phosphotransferase) domain 1

Ligands and Environments

2 bound ligands:
Ligand 95U 1 x 95U
Ligand EPE 1 x EPE
No modified residues

Experiments and Validation Details

Entry percentile scores
X-ray source: PHOTON FACTORY BEAMLINE BL-17A
Spacegroup: P212121
Unit cell:
a: 54.584Å b: 63.827Å c: 88.458Å
α: 90° β: 90° γ: 90°
R-values:
R R work R free
0.195 0.192 0.258
Expression system: Escherichia coli B

Quick links

Citations

7 review citations

Recent Advances in Selective and Irreversible Covalent Ligand Development and Validation.
Zhang et al. (2019)
6 more

1 mention without citation

TransDTI: Transformer-Based Language Models for Estimating DTIs and Building a Drug Recommendation Workflow.
Kalakoti et al. (2022)