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Cheminformatics-aided discovery of small-molecule Protein-Protein Interaction (PPI) dual inhibitors of Tumor Necrosis Factor (TNF) and Receptor Activator of NF-κB Ligand (RANKL)
- Source :
- PLoS Computational Biology, Vol 13, Iss 4, p e1005372 (2017), PLoS Computational Biology
- Publication Year :
- 2017
- Publisher :
- Public Library of Science (PLoS), 2017.
-
Abstract
- We present an in silico drug discovery pipeline developed and applied for the identification and virtual screening of small-molecule Protein-Protein Interaction (PPI) compounds that act as dual inhibitors of TNF and RANKL through the trimerization interface. The cheminformatics part of the pipeline was developed by combining structure–based with ligand–based modeling using the largest available set of known TNF inhibitors in the literature (2481 small molecules). To facilitate virtual screening, the consensus predictive model was made freely available at: http://enalos.insilicotox.com/TNFPubChem/. We thus generated a priority list of nine small molecules as candidates for direct TNF function inhibition. In vitro evaluation of these compounds led to the selection of two small molecules that act as potent direct inhibitors of TNF function, with IC50 values comparable to those of a previously-described direct inhibitor (SPD304), but with significantly reduced toxicity. These molecules were also identified as RANKL inhibitors and validated in vitro with respect to this second functionality. Direct binding of the two compounds was confirmed both for TNF and RANKL, as well as their ability to inhibit the biologically-active trimer forms. Molecular dynamics calculations were also carried out for the two small molecules in each protein to offer additional insight into the interactions that govern TNF and RANKL complex formation. To our knowledge, these compounds, namely T8 and T23, constitute the second and third published examples of dual small-molecule direct function inhibitors of TNF and RANKL, and could serve as lead compounds for the development of novel treatments for inflammatory and autoimmune diseases.<br />Author summary Developing drugs that disrupt protein-protein interactions (PPIs) is a difficult task in pharmaceutical research. The interaction between protein Tumor Necrosis Factor (TNF) and its receptors is implicated in several physiological functions and diseases, such as rheumatoid and psoriatic arthritis, Crohn’s disease, and multiple sclerosis. Despite their potency, current medications that block the interaction between TNF and its receptors are also associated with many adverse functions. Here, we employ comprehensive computational and experimental methods to discover novel small molecules that are direct inhibitors of TNF function. Functionality for RANKL, a second, clinically-relevant member of the TNF protein family, was also examined. Using a combination of an in silico drug discovery pipeline, which includes structure- and ligand-based modeling, and in vitro experiments, we identified compounds T8 and T23 as dual inhibitors of TNF and RANKL. These compounds present low toxicity and may be further optimized in drug design targeting TNF and RANKL to develop improved treatments for a range of inflammatory and autoimmune diseases.
- Subjects :
- 0301 basic medicine
Anti-Inflammatory Agents
Bioinformatics
Toxicology
Pathology and Laboratory Medicine
Molecular Dynamics
Ligands
Biochemistry
chemistry.chemical_compound
Mice
Computational Chemistry
Mathematical and Statistical Techniques
Drug Discovery
Medicine and Health Sciences
Biology (General)
Free Energy
Cells, Cultured
Crystallography
Ecology
biology
Drug discovery
Chemistry
Organic Compounds
Physics
Condensed Matter Physics
Small molecule
3. Good health
Computational Theory and Mathematics
RANKL
Modeling and Simulation
Physical Sciences
Crystal Structure
Thermodynamics
Statistics (Mathematics)
Research Article
Biotechnology
Cell Survival
QH301-705.5
In silico
Chemical physics
Bone Marrow Cells
Research and Analysis Methods
Protein–protein interaction
Cell Line
03 medical and health sciences
Cellular and Molecular Neuroscience
Genetics
Solid State Physics
Animals
Humans
Computer Simulation
Protein Interaction Domains and Motifs
Statistical Methods
Protein Interactions
Molecular Biology
Ecology, Evolution, Behavior and Systematics
Virtual screening
Toxicity
Tumor Necrosis Factor-alpha
Organic Chemistry
RANK Ligand
Chemical Compounds
Biology and Life Sciences
Proteins
NF-κB
Dimers (Chemical physics)
In vitro
030104 developmental biology
Small Molecules
biology.protein
Mathematics
Forecasting
Subjects
Details
- Language :
- English
- ISSN :
- 15537358
- Volume :
- 13
- Issue :
- 4
- Database :
- OpenAIRE
- Journal :
- PLoS Computational Biology
- Accession number :
- edsair.doi.dedup.....de45a7a44b22aba702a4723a90d6c4dd