› 1c3v

X-ray diffraction
2.39Å resolution

DIHYDRODIPICOLINATE REDUCTASE FROM MYCOBACTERIUM TUBERCULOSIS COMPLEXED WITH NADPH AND PDC

Released:
DOI: 10.2210/pdb1c3v/pdb
PDB entry 1c3v coloured by chain, front view.
PDB entry 1c3v coloured by chain, side view.
PDB entry 1c3v coloured by chain, top view.
Source organism: Mycobacterium tuberculosis
Primary publication:
The three-dimensional structures of the Mycobacterium tuberculosis dihydrodipicolinate reductase-NADH-2,6-PDC and -NADPH-2,6-PDC complexes. Structural and mutagenic analysis of relaxed nucleotide specificity.
Cirilli M, Zheng R, Scapin G, Blanchard JS
Biochemistry 42 10644-50 (2003)
PMID: 12962488

Function and Biology Details

Reaction catalysed: 
(S)-2,3,4,5-tetrahydropyridine-2,6-dicarboxylate + NAD(P)(+) + H(2)O = (2S,4S)-4-hydroxy-2,3,4,5-tetrahydrodipicolinate + NAD(P)H
Biochemical function:
Biological process:
Cellular component:
Sequence domains:
Structure domains:

Structure analysis Details

Assembly composition:
homo tetramer (preferred)
Assembly name:
PDBe Complex ID:
PDB-CPX-161917 (preferred)
Entry contents:
1 distinct polypeptide molecule
Macromolecule:
4-hydroxy-tetrahydrodipicolinate reductase Chains: A, B
Molecule details ›
Chains: A, B
Length: 245 amino acids
Theoretical weight: 25.79 KDa
Source organism: Mycobacterium tuberculosis
Expression system: Escherichia coli
UniProt:
  • Canonical: P9WP23 (Residues: 1-245; Coverage: 100%)
Gene names: MTV002.38c, Rv2773c, dapB
Sequence domains:
Structure domains:

Ligands and Environments


Cofactor: Ligand NDP 2 x NDP
2 bound ligands:
Ligand PDC 2 x PDC
Ligand PG4 1 x PG4
No modified residues

Experiments and Validation Details

Entry percentile scores
X-ray source: RIGAKU RU200
Spacegroup: I212121
Unit cell:
a: 118.831Å b: 118.257Å c: 79.377Å
α: 90° β: 90° γ: 90°
R-values:
R R work R free
0.212 0.193 0.243
Expression system: Escherichia coli

Quick links

Citations

2 review citations

Inhibition of lysine biosynthesis: an evolving antibiotic strategy.
Hutton et al. (2007)
1 more

10 mentions without citation

Navigating bioactivity space in anti-tubercular drug discovery through the deployment of advanced machine learning models and cheminformatics tools: a molecular modeling based retrospective study.
Bhowmik et al. (2023)
9 more