6VLV

Factor XIa in complex with compound 11


Experimental Data Snapshot

  • Method: X-RAY DIFFRACTION
  • Resolution: 1.72 Å
  • R-Value Free: 0.198 
  • R-Value Work: 0.172 
  • R-Value Observed: 0.173 

wwPDB Validation   3D Report Full Report


Ligand Structure Quality Assessment 


This is version 1.1 of the entry. See complete history


Literature

Augmenting Hit Identification by Virtual Screening Techniques in Small Molecule Drug Discovery.

Yan, X.C.Sanders, J.M.Gao, Y.D.Tudor, M.Haidle, A.M.Klein, D.J.Converso, A.Lesburg, C.A.Zang, Y.Wood, H.B.

(2020) J Chem Inf Model 60: 4144-4152

  • DOI: 10.1021/acs.jcim.0c00113
  • Primary Citation of Related Structures:  
    6VLM, 6VLU, 6VLV

  • PubMed Abstract: 
  • Two orthogonal approaches for hit identification in drug discovery are large-scale in vitro and in silico screening. In recent years, due to the emergence of new targets and a rapid increase in the size of the readily synthesizable chemical space, there is a growing emphasis on the integration of the two techniques to improve the hit finding efficiency ...

    Two orthogonal approaches for hit identification in drug discovery are large-scale in vitro and in silico screening. In recent years, due to the emergence of new targets and a rapid increase in the size of the readily synthesizable chemical space, there is a growing emphasis on the integration of the two techniques to improve the hit finding efficiency. Here, we highlight three examples of drug discovery projects at Merck & Co., Inc., Kenilworth, NJ, USA in which different virtual screening (VS) techniques, each specifically tailored to leverage knowledge available for the target, were utilized to augment the selection of high-quality chemical matter for in vitro assays and to enhance the diversity and tractability of hits. Central to success is a fully integrated workflow combining in silico and experimental expertise at every stage of the hit identification process. We advocate that workflows encompassing VS as part of an integrated hit finding plan should be widely adopted to accelerate hit identification and foster cross-functional collaborations in modern drug discovery.


    Organizational Affiliation

    School of Biological Sciences, Nanyang Technological University, Singapore jtorres@ntu.edu.sg.



Macromolecules
Find similar proteins by:  (by identity cutoff)  |  Structure
Entity ID: 1
MoleculeChainsSequence LengthOrganismDetailsImage
Coagulation factor XIa light chainA238Homo sapiensMutation(s): 1 
Gene Names: F11
EC: 3.4.21.27
UniProt & NIH Common Fund Data Resources
Find proteins for P03951 (Homo sapiens)
Explore P03951 
Go to UniProtKB:  P03951
PHAROS:  P03951
Protein Feature View
Expand
  • Reference Sequence
Small Molecules
Ligands 2 Unique
IDChainsName / Formula / InChI Key2D Diagram3D Interactions
R3A (Subject of Investigation/LOI)
Query on R3A

Download Ideal Coordinates CCD File 
D [auth A]1-carbamimidamido-4-chloro-N-[(2R)-3-methyl-1-(morpholin-4-yl)-1-oxobutan-2-yl]isoquinoline-7-sulfonamide
C19 H25 Cl N6 O4 S
JKDPCBXPJMGTJT-MRXNPFEDSA-N
 Ligand Interaction
FLC
Query on FLC

Download Ideal Coordinates CCD File 
B [auth A], C [auth A]CITRATE ANION
C6 H5 O7
KRKNYBCHXYNGOX-UHFFFAOYSA-K
 Ligand Interaction
Experimental Data & Validation

Experimental Data

  • Method: X-RAY DIFFRACTION
  • Resolution: 1.72 Å
  • R-Value Free: 0.198 
  • R-Value Work: 0.172 
  • R-Value Observed: 0.173 
  • Space Group: P 21 21 21
Unit Cell:
Length ( Å )Angle ( ˚ )
a = 59.23α = 90
b = 59.88β = 90
c = 67.9γ = 90
Software Package:
Software NamePurpose
SCALAdata scaling
BUSTERrefinement
PDB_EXTRACTdata extraction
XDSdata reduction
BUSTERphasing

Structure Validation

View Full Validation Report



Ligand Structure Quality Assessment  



Entry History 

Deposition Data

  • Deposited Date: 2020-01-27 
  • Released Date: 2020-05-06 
  • Deposition Author(s): Lesburg, C.A.

Revision History  (Full details and data files)

  • Version 1.0: 2020-05-06
    Type: Initial release
  • Version 1.1: 2020-10-07
    Changes: Database references