6ELO

Estimation of relative drug-target residence times by random acceleration molecular dynamics simulation

Experimental Data Snapshot

  • Method: X-RAY DIFFRACTION
  • Resolution: 1.80 Å
  • R-Value Free: 0.238 
  • R-Value Work: 0.192 
  • R-Value Observed: 0.195 

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Literature

Estimation of Drug-Target Residence Times by tau-Random Acceleration Molecular Dynamics Simulations.

Kokh, D.B., Amaral, M., Bomke, J., Gradler, U., Musil, D., Buchstaller, H.P., Dreyer, M.K., Frech, M., Lowinski, M., Vallee, F., Bianciotto, M., Rak, A., Wade, R.C.

(2018) J Chem Theory Comput 14: 3859-3869

  • DOI: 10.1021/acs.jctc.8b00230
  • Primary Citation of Related Structures:  
    5LO5, 5LO6, 6EI5, 6EL5, 6ELN, 6ELO, 6ELP, 6EY8, 6EY9, 6EYA, 6EYB, 6F1N

  • PubMed Abstract: 

    • Drug-target residence time (τ), one of the main determinants of drug efficacy, remains highly challenging to predict computationally and, therefore, is usually not considered in the early stages of drug design. Here, we present an efficient computational method, τ-random acceleration molecular dynamics (τRAMD), for the ranking of drug candidates by their residence time and obtaining insights into ligand-target dissociation mechanisms ...

    Drug-target residence time (τ), one of the main determinants of drug efficacy, remains highly challenging to predict computationally and, therefore, is usually not considered in the early stages of drug design. Here, we present an efficient computational method, τ-random acceleration molecular dynamics (τRAMD), for the ranking of drug candidates by their residence time and obtaining insights into ligand-target dissociation mechanisms. We assessed τRAMD on a data set of 70 diverse drug-like ligands of the N-terminal domain of HSP90α, a pharmaceutically important target with a highly flexible binding site, obtaining computed relative residence times with an accuracy of about 2.3τ for 78% of the compounds and less than 2.0τ within congeneric series. Analysis of dissociation trajectories reveals features that affect ligand unbinding rates, including transient polar interactions and steric hindrance. These results suggest that τRAMD will be widely applicable as a computationally efficient aid to improving drug residence times during lead optimization.

    Organizational Affiliation: 

    Interdisciplinary Center for Scientific Computing (IWR) , Heidelberg University , Heidelberg 69120 , Germany.



Macromolecules
Find similar proteins by: 
(by identity cutoff)  |  3D Structure
Entity ID: 1
MoleculeChainsSequence LengthOrganismDetailsImage
Heat shock protein HSP 90-alphaA236Homo sapiensMutation(s): 0 
Gene Names: HSP90AA1, HSP90A, HSPC1, HSPCA
EC: 3.6.4.10
UniProt & NIH Common Fund Data Resources
Find proteins for P07900 (Homo sapiens)
Explore P07900 
Go to UniProtKB:  P07900
PHAROS:  P07900
Entity Groups  
Sequence Clusters30% Identity50% Identity70% Identity90% Identity95% Identity100% Identity
UniProt GroupP07900
Protein Feature View
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  • Reference Sequence
Small Molecules
Ligands 1 Unique
IDChainsName / Formula / InChI Key2D Diagram3D Interactions
BAW
Query on BAW
Download Ideal Coordinates CCD File 
B [auth A]4-ethyl-6-[4-(2-fluorophenyl)-3-methyl-1~{H}-pyrazol-5-yl]benzene-1,3-diol
C18 H17 F N2 O2
LSNAMSAWSQUHGB-UHFFFAOYSA-N		 Ligand Interaction
Binding Affinity Annotations 
IDSourceBinding Affinity
BAW Binding MOAD:  6ELO Kd: 64 (nM) from 1 assay(s)
Experimental Data & Validation

Experimental Data

  • Method: X-RAY DIFFRACTION
  • Resolution: 1.80 Å
  • R-Value Free: 0.238 
  • R-Value Work: 0.192 
  • R-Value Observed: 0.195 
  • Space Group: I 2 2 2
Unit Cell:
Length ( Å )Angle ( ˚ )
a = 66.05α = 90
b = 89.21β = 90
c = 99.88γ = 90
Software Package:
Software NamePurpose
BUSTERrefinement
d*TREKdata reduction
d*TREKdata scaling
PHASERphasing

Structure Validation

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Entry History 

Deposition Data

Revision History  (Full details and data files)

  • Version 1.0: 2018-05-30
    Type: Initial release
  • Version 1.1: 2018-07-18
    Changes: Data collection, Database references
  • Version 1.2: 2019-10-16
    Changes: Data collection