8S1X

Crystal structure of Actinonin-bound PDF1 and the computationally designed DBAct553_1 protein binder


Experimental Data Snapshot

  • Method: X-RAY DIFFRACTION
  • Resolution: 1.88 Å
  • R-Value Free: 
    0.203 (Depositor), 0.206 (DCC) 
  • R-Value Work: 
    0.184 (Depositor), 0.182 (DCC) 
  • R-Value Observed: 
    0.185 (Depositor) 

Starting Model: in silico
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wwPDB Validation   3D Report Full Report


Ligand Structure Quality Assessment 

Created with Raphaël 2.3.0Worse 01 BetterLigand structure goodness of fit to experimental dataBest fitted BB2Click on this verticalbar to view details

This is version 1.2 of the entry. See complete history


Literature

Targeting protein-ligand neosurfaces with a generalizable deep learning tool.

Marchand, A.Buckley, S.Schneuing, A.Pacesa, M.Elia, M.Gainza, P.Elizarova, E.Neeser, R.M.Lee, P.W.Reymond, L.Miao, Y.Scheller, L.Georgeon, S.Schmidt, J.Schwaller, P.Maerkl, S.J.Bronstein, M.Correia, B.E.

(2025) Nature 

  • DOI: https://doi.org/10.1038/s41586-024-08435-4
  • Primary Citation of Related Structures:  
    8S1X, 9FKD

  • PubMed Abstract: 

    Molecular recognition events between proteins drive biological processes in living systems 1 . However, higher levels of mechanistic regulation have emerged, in which protein-protein interactions are conditioned to small molecules 2-5 . Despite recent advances, computational tools for the design of new chemically induced protein interactions have remained a challenging task for the field 6,7 . Here we present a computational strategy for the design of proteins that target neosurfaces, that is, surfaces arising from protein-ligand complexes. To develop this strategy, we leveraged a geometric deep learning approach based on learned molecular surface representations 8,9 and experimentally validated binders against three drug-bound protein complexes: Bcl2-venetoclax, DB3-progesterone and PDF1-actinonin. All binders demonstrated high affinities and accurate specificities, as assessed by mutational and structural characterization. Remarkably, surface fingerprints previously trained only on proteins could be applied to neosurfaces induced by interactions with small molecules, providing a powerful demonstration of generalizability that is uncommon in other deep learning approaches. We anticipate that such designed chemically induced protein interactions will have the potential to expand the sensing repertoire and the assembly of new synthetic pathways in engineered cells for innovative drug-controlled cell-based therapies 10 .


  • Organizational Affiliation

    Laboratory of Protein Design and Immunoengineering, Institute of Bioengineering, Ecole polytechnique fédérale de Lausanne, Lausanne, Switzerland.


Macromolecules
Find similar proteins by:  (by identity cutoff)  |  3D Structure
Entity ID: 1
MoleculeChains Sequence LengthOrganismDetailsImage
Peptide deformylase168Pseudomonas aeruginosaMutation(s): 0 
Gene Names: defPA0019
EC: 3.5.1.88
UniProt
Find proteins for Q9I7A8 (Pseudomonas aeruginosa (strain ATCC 15692 / DSM 22644 / CIP 104116 / JCM 14847 / LMG 12228 / 1C / PRS 101 / PAO1))
Explore Q9I7A8 
Go to UniProtKB:  Q9I7A8
Entity Groups  
Sequence Clusters30% Identity50% Identity70% Identity90% Identity95% Identity100% Identity
UniProt GroupQ9I7A8
Sequence Annotations
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  • Reference Sequence
Find similar proteins by:  (by identity cutoff)  |  3D Structure
Entity ID: 2
MoleculeChains Sequence LengthOrganismDetailsImage
DBAct553_170synthetic constructMutation(s): 0 
Entity Groups  
Sequence Clusters30% Identity50% Identity70% Identity90% Identity95% Identity100% Identity
Sequence Annotations
Expand
  • Reference Sequence
Small Molecules
Ligands 5 Unique
IDChains Name / Formula / InChI Key2D Diagram3D Interactions
BB2 (Subject of Investigation/LOI)
Query on BB2

Download Ideal Coordinates CCD File 
D [auth A]ACTINONIN
C19 H35 N3 O5
XJLATMLVMSFZBN-VYDXJSESSA-N
PO4
Query on PO4

Download Ideal Coordinates CCD File 
M [auth A],
N [auth A],
O [auth A],
P [auth A]
PHOSPHATE ION
O4 P
NBIIXXVUZAFLBC-UHFFFAOYSA-K
ZN
Query on ZN

Download Ideal Coordinates CCD File 
C [auth A]ZINC ION
Zn
PTFCDOFLOPIGGS-UHFFFAOYSA-N
FMT
Query on FMT

Download Ideal Coordinates CCD File 
E [auth A]
F [auth A]
G [auth A]
H [auth A]
I [auth A]
FORMIC ACID
C H2 O2
BDAGIHXWWSANSR-UHFFFAOYSA-N
K
Query on K

Download Ideal Coordinates CCD File 
Q [auth B]POTASSIUM ION
K
NPYPAHLBTDXSSS-UHFFFAOYSA-N
Experimental Data & Validation

Experimental Data

  • Method: X-RAY DIFFRACTION
  • Resolution: 1.88 Å
  • R-Value Free:  0.203 (Depositor), 0.206 (DCC) 
  • R-Value Work:  0.184 (Depositor), 0.182 (DCC) 
  • R-Value Observed: 0.185 (Depositor) 
Space Group: P 21 21 21
Unit Cell:
Length ( Å )Angle ( ˚ )
a = 49.44α = 90
b = 75.01β = 90
c = 83.16γ = 90
Software Package:
Software NamePurpose
PHENIXrefinement
autoPROCdata reduction
autoPROCdata scaling
PHASERphasing

Structure Validation

View Full Validation Report



Ligand Structure Quality Assessment 

Created with Raphaël 2.3.0Worse 01 BetterLigand structure goodness of fit to experimental dataBest fitted BB2Click on this verticalbar to view details

Entry History & Funding Information

Deposition Data


Funding OrganizationLocationGrant Number
European Research Council (ERC)European Union716058
Swiss National Science FoundationSwitzerland310030_197724

Revision History  (Full details and data files)

  • Version 1.0: 2024-10-30
    Type: Initial release
  • Version 1.1: 2025-01-15
    Changes: Database references
  • Version 1.2: 2025-01-29
    Changes: Database references