6EI5

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


Experimental Data Snapshot

  • Method: X-RAY DIFFRACTION
  • Resolution: 2.2 Å
  • R-Value Free: 0.217 
  • R-Value Work: 0.189 

wwPDB Validation 3D Report Full Report


This is version 1.1 of the entry. See complete history

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:  

  • 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 computati ...

    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

    Molecular and Cellular Modeling Group , Heidelberg Institute for Theoretical Studies , Heidelberg 69118 , Germany.




Macromolecules

Find similar proteins by: Sequence  |  Structure

Entity ID: 1
MoleculeChainsSequence LengthOrganismDetails
Heat shock protein HSP 90-alpha
A
209Homo sapiensMutation(s): 0 
Gene Names: HSP90AA1 (HSP90A, HSPC1, HSPCA)
Find proteins for P07900 (Homo sapiens)
Go to Gene View: HSP90AA1
Go to UniProtKB:  P07900
Small Molecules
Ligands 1 Unique
IDChainsName / Formula / InChI Key2D Diagram3D Interactions
B5Q
Query on B5Q

Download SDF File 
Download CCD File 
A
[2-azanyl-6-[2-(methylaminomethyl)phenyl]quinazolin-4-yl]-(1,3-dihydroisoindol-2-yl)methanone
C25 H23 N5 O
MNDBIURAICAMAU-UHFFFAOYSA-N
 Ligand Interaction
Experimental Data & Validation

Experimental Data

  • Method: X-RAY DIFFRACTION
  • Resolution: 2.2 Å
  • R-Value Free: 0.217 
  • R-Value Work: 0.189 
  • Space Group: I 2 2 2
Unit Cell:
Length (Å)Angle (°)
a = 66.230α = 90.00
b = 92.460β = 90.00
c = 98.970γ = 90.00
Software Package:
Software NamePurpose
PHASERphasing
BUSTERrefinement
XSCALEdata scaling
XDSdata processing
PDB_EXTRACTdata extraction

Structure Validation

View Full Validation Report or Ramachandran Plots



Entry History 

Deposition Data

Revision History 

  • Version 1.0: 2018-05-30
    Type: Initial release
  • Version 1.1: 2018-07-18
    Type: Data collection, Database references