Molecular-Simulation-Driven Fragment Screening for the Discovery of New CXCL12 Inhibitors

Fragment-based drug discovery (FBDD) has become a mainstream approach in drug design because it allows the reduction of the chemical space and screening libraries while identifying fragments with high protein–ligand efficiency interactions that can later be grown into drug-like leads. In this work,...

Full description

Saved in:
Bibliographic Details
Published in:Journal of chemical information and modeling 2018-03, Vol.58 (3), p.683-691
Main Authors: Martinez-Rosell, Gerard, Harvey, Matt J, De Fabritiis, Gianni
Format: Article
Language:English
Subjects:
Affinity
Binding
Binding Sites
Chemokine CXCL12 - antagonists & inhibitors
Chemokine CXCL12 - chemistry
Chemokine CXCL12 - metabolism
Computer simulation
Drug Design
Drug Discovery - methods
Fragmentation
Fragments
High-Throughput Screening Assays - methods
Humans
Hydrophobic and Hydrophilic Interactions
Kinetics
Leverage
Ligands
Markov chains
Molecular chains
Molecular Docking Simulation - methods
Molecular dynamics
Molecular Dynamics Simulation
Organic chemistry
Pharmacology
Proteins
R&D
Research & development
Screening
Small Molecule Libraries - chemistry
Small Molecule Libraries - pharmacology
Studies
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Fragment-based drug discovery (FBDD) has become a mainstream approach in drug design because it allows the reduction of the chemical space and screening libraries while identifying fragments with high protein–ligand efficiency interactions that can later be grown into drug-like leads. In this work, we leverage high-throughput molecular dynamics (MD) simulations to screen a library of 129 fragments for a total of 5.85 ms against the CXCL12 monomer, a chemokine involved in inflammation and diseases such as cancer. Our in silico binding assay was able to recover binding poses, affinities, and kinetics for the selected library and was able to predict 8 mM-affinity fragments with ligand efficiencies higher than 0.3. All of the fragment hits present a similar chemical structure, with a hydrophobic core and a positively charged group, and bind to either sY7 or H1S68 pockets, where they share pharmacophoric properties with experimentally resolved natural binders. This work presents a large-scale screening assay using an exclusive combination of thousands of short MD adaptive simulations analyzed with a Markov state model (MSM) framework.
ISSN:1549-9596
1549-960X
DOI:10.1021/acs.jcim.7b00625