8XLX | pdb_00008xlx

Complex structure of AtHPPD with LB600


Experimental Data Snapshot

  • Method: X-RAY DIFFRACTION
  • Resolution: 1.56 Å
  • R-Value Free: 
    0.207 (Depositor), 0.205 (DCC) 
  • R-Value Work: 
    0.186 (Depositor), 0.186 (DCC) 
  • R-Value Observed: 
    0.188 (Depositor) 

Starting Model: experimental
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wwPDB Validation   3D Report Full Report


Ligand Structure Quality Assessment 


This is version 1.1 of the entry. See complete history


Literature

Reinforcement learning-based generative artificial intelligence for novel pesticide design.

Yang, R.Li, B.Dong, J.Cai, Z.Lin, H.Wang, F.Yang, G.

(2025) J Adv Res 

  • DOI: https://doi.org/10.1016/j.jare.2025.02.030
  • Primary Citation of Related Structures:  
    8XLX

  • PubMed Abstract: 

    Pesticides play a pivotal role in ensuring food security, and the development of green pesticides is an inevitable trend in global agricultural progress. Although deep learning-based generative models have revolutionized de novo drug design in pharmaceutical research, their application in pesticide research and development remains unexplored. This study aims to pioneer the application of generative artificial intelligence to pesticide design by proposing a reinforcement learning-based framework for obtaining pesticide-like molecules with high binding affinity. This framework comprises two key components: PestiGen-G, which systematically explores the pesticide-like chemical space using a character-based generative model coupled with the REINFORCE algorithm; and PestiGen-S, which combines a fragment-based generative model with the Monte Carlo Tree Search algorithm to generate molecules that stably bind to the specific target protein. Experimental results show that the molecules generated by PestiGen have superior pesticide-likeness and binding affinity compared to those generated by existing methods. In addition, we employ an active learning strategy to reduce the false-positive rate of the generated molecules. Finally, through collaboration with domain experts, we successfully designed a novel 4-hydroxyphenylpyruvate dioxygenase inhibitor (YH23768) with favorable enzyme inhibition and herbicidal potency. This proof-of-concept study highlights the utility of PestiGen as a valuable tool for pesticide design. The web server based on the model is freely available at https://dpai.ccnu.edu.cn/PestiGen/.


  • Organizational Affiliation
    • State Key Laboratory of Green Pesticide, International Joint Research Center for Intelligent Biosensor Technology and Health, Central China Normal University, Wuhan 430079, PR China.

Macromolecules
Find similar proteins by:  (by identity cutoff)  |  3D Structure
Entity ID: 1
MoleculeChains Sequence LengthOrganismDetailsImage
4-hydroxyphenylpyruvate dioxygenase417Arabidopsis thalianaMutation(s): 0 
Gene Names: HPDPDS1At1g06570F12K11.9
EC: 1.13.11.27
UniProt
Find proteins for P93836 (Arabidopsis thaliana)
Explore P93836 
Go to UniProtKB:  P93836
Entity Groups  
Sequence Clusters30% Identity50% Identity70% Identity90% Identity95% Identity100% Identity
UniProt GroupP93836
Sequence Annotations
Expand
  • Reference Sequence
Small Molecules
Ligands 2 Unique
IDChains Name / Formula / InChI Key2D Diagram3D Interactions
A1LWA
Query on A1LWA

Download Ideal Coordinates CCD File 
B [auth A](3~{R},4~{S},5~{R})-4-[2,4-bis(chloranyl)-3-phenylmethoxy-phenyl]carbonyl-1-ethyl-5-methyl-3-oxidanyl-pyrrolidin-2-one
C21 H21 Cl2 N O4
OFNHTQNNTWKNME-SMNXXWJPSA-N
CO
Query on CO

Download Ideal Coordinates CCD File 
C [auth A]COBALT (II) ION
Co
XLJKHNWPARRRJB-UHFFFAOYSA-N
Experimental Data & Validation

Experimental Data

  • Method: X-RAY DIFFRACTION
  • Resolution: 1.56 Å
  • R-Value Free:  0.207 (Depositor), 0.205 (DCC) 
  • R-Value Work:  0.186 (Depositor), 0.186 (DCC) 
  • R-Value Observed: 0.188 (Depositor) 
Space Group: C 1 2 1
Unit Cell:
Length ( Å )Angle ( ˚ )
a = 76.58α = 90
b = 83.527β = 101.89
c = 61.422γ = 90
Software Package:
Software NamePurpose
PHENIXrefinement
DIALSdata reduction
DIALSdata scaling
PHASERphasing

Structure Validation

View Full Validation Report



Ligand Structure Quality Assessment 


Entry History & Funding Information

Deposition Data


Funding OrganizationLocationGrant Number
National Natural Science Foundation of China (NSFC)China--

Revision History  (Full details and data files)

  • Version 1.0: 2025-01-01
    Type: Initial release
  • Version 1.1: 2025-07-02
    Changes: Database references