PDBsum entry 5ti2

Transcription/inhibitor

PDB id: 5ti2

Contents

Protein chain

127 a.a.

Ligands

7CJ

EDO ×3

Waters ×136

PDB id:

5ti2

Name:

Transcription/inhibitor

Title:

Crystal structure of the first bromodomain of human brd4 in complex with inhibitor 7635936

Structure:

Bromodomain-containing protein 4. Chain: a. Fragment: unp residues 44-168. Synonym: protein hunk1. Engineered: yes. Mutation: yes

Source:

Homo sapiens. Human. Organism_taxid: 9606. Gene: brd4, hunk1. Expressed in: escherichia coli. Expression_system_taxid: 469008.

Resolution:

1.65Å R-factor: 0.128 R-free: 0.181

Authors:

J.-Y.Zhu,S.W.J.Ember,E.Schonbrunn

Key ref:

B.K.Allen et al. (2017). Identification of a Novel Class of BRD4 Inhibitors by Computational Screening and Binding Simulations. ACS Omega, 2, 4760-4771. PubMed id: 28884163

Date:

30-Sep-16 Release date: 09-Aug-17

Protein chain

O60885  (BRD4_HUMAN) -  Bromodomain-containing protein 4 from Homo sapiens

Seq: 1362 a.a.

Struc: 127 a.a.*

* PDB and UniProt seqs differ at 1 residue position (black cross)

Enzyme reactions

• Enzyme class: E.C.?

ACS Omega 2:4760-4771 (2017)

PubMed id: 28884163

Identification of a Novel Class of BRD4 Inhibitors by Computational Screening and Binding Simulations.

B.K.Allen, S.Mehta, S.W.J.Ember, J.Y.Zhu, E.Schönbrunn, N.G.Ayad, S.C.Schürer.

ABSTRACT

Computational screening is a method to prioritize small-molecule compounds based on the structural and biochemical attributes built from ligand and target information. Previously, we have developed a scalable virtual screening workflow to identify novel multitarget kinase/bromodomain inhibitors. In the current study, we identified several novelN-[3-(2-oxo-pyrrolidinyl)phenyl]-benzenesulfonamide derivatives that scored highly in our ensemble docking protocol. We quantified the binding affinity of these compounds for BRD4(BD1) biochemically and generated cocrystal structures, which were deposited in the Protein Data Bank. As the docking poses obtained in the virtual screening pipeline did not align with the experimental cocrystal structures, we evaluated the predictions of their precise binding modes by performing molecular dynamics (MD) simulations. The MD simulations closely reproduced the experimentally observed protein-ligand cocrystal binding conformations and interactions for all compounds. These results suggest a computational workflow to generate experimental-quality protein-ligand binding models, overcoming limitations of docking results due to receptor flexibility and incomplete sampling, as a useful starting point for the structure-based lead optimization of novel BRD4(BD1) inhibitors.