2H2Q

Crystal structure of Trypanosoma cruzi Dihydrofolate Reductase-Thymidylate synthase


Experimental Data Snapshot

  • Method: X-RAY DIFFRACTION
  • Resolution: 2.40 Å
  • R-Value Free: 0.241 
  • R-Value Work: 0.206 
  • R-Value Observed: 0.208 

Starting Model: experimental
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Ligand Structure Quality Assessment 


This is version 1.4 of the entry. See complete history


Literature

Structure-based approach to pharmacophore identification, in silico screening, and three-dimensional quantitative structure-activity relationship studies for inhibitors of Trypanosoma cruzi dihydrofolate reductase function.

Schormann, N.Senkovich, O.Walker, K.Wright, D.L.Anderson, A.C.Rosowsky, A.Ananthan, S.Shinkre, B.Velu, S.Chattopadhyay, D.

(2008) Proteins 73: 889-901

  • DOI: https://doi.org/10.1002/prot.22115
  • Primary Citation of Related Structures:  
    2H2Q, 3CL9, 3CLB

  • PubMed Abstract: 

    We have employed a structure-based three-dimensional quantitative structure-activity relationship (3D-QSAR) approach to predict the biochemical activity for inhibitors of T. cruzi dihydrofolate reductase-thymidylate synthase (DHFR-TS). Crystal structures of complexes of the enzyme with eight different inhibitors of the DHFR activity together with the structure in the substrate-free state (DHFR domain) were used to validate and refine docking poses of ligands that constitute likely active conformations. Structural information from these complexes formed the basis for the structure-based alignment used as input for the QSAR study. Contrary to indirect ligand-based approaches the strategy described here employs a direct receptor-based approach. The goal is to generate a library of selective lead inhibitors for further development as antiparasitic agents. 3D-QSAR models were obtained for T. cruzi DHFR-TS (30 inhibitors in learning set) and human DHFR (36 inhibitors in learning set) that show a very good agreement between experimental and predicted enzyme inhibition data. For crossvalidation of the QSAR model(s), we have used the 10% leave-one-out method. The derived 3D-QSAR models were tested against a few selected compounds (a small test set of six inhibitors for each enzyme) with known activity, which were not part of the learning set, and the quality of prediction of the initial 3D-QSAR models demonstrated that such studies are feasible. Further refinement of the models through integration of additional activity data and optimization of reliable docking poses is expected to lead to an improved predictive ability.


  • Organizational Affiliation

    Department of Pharmaceutical Sciences, University of Alabama at Birmingham, Birmingham, Alabama 35294, USA.


Macromolecules
Find similar proteins by:  (by identity cutoff)  |  3D Structure
Entity ID: 1
MoleculeChains Sequence LengthOrganismDetailsImage
Bifunctional dihydrofolate reductase-thymidylate synthase
A, B
521Trypanosoma cruziMutation(s): 0 
EC: 1.5.1.3 (PDB Primary Data), 2.1.1.45 (PDB Primary Data)
UniProt
Find proteins for Q27793 (Trypanosoma cruzi)
Explore Q27793 
Go to UniProtKB:  Q27793
Entity Groups  
Sequence Clusters30% Identity50% Identity70% Identity90% Identity95% Identity100% Identity
UniProt GroupQ27793
Sequence Annotations
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  • Reference Sequence
Experimental Data & Validation

Experimental Data

  • Method: X-RAY DIFFRACTION
  • Resolution: 2.40 Å
  • R-Value Free: 0.241 
  • R-Value Work: 0.206 
  • R-Value Observed: 0.208 
  • Space Group: C 2 2 21
Unit Cell:
Length ( Å )Angle ( ˚ )
a = 88.681α = 90
b = 137.25β = 90
c = 189.27γ = 90
Software Package:
Software NamePurpose
REFMACrefinement
SCALEPACKdata scaling
CNSrefinement
PDB_EXTRACTdata extraction
HKL-2000data reduction
CCP4phasing
DENZOdata reduction

Structure Validation

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Ligand Structure Quality Assessment 


Entry History 

Deposition Data

Revision History  (Full details and data files)

  • Version 1.0: 2008-04-08
    Type: Initial release
  • Version 1.1: 2011-07-13
    Changes: Advisory, Derived calculations, Version format compliance
  • Version 1.2: 2017-10-18
    Changes: Refinement description
  • Version 1.3: 2019-07-24
    Changes: Data collection, Refinement description
  • Version 1.4: 2023-08-30
    Changes: Data collection, Database references, Derived calculations, Refinement description