TNF & RANKL: Key Drivers of Chronic Inflammation
Targeting Protein-Protein Interactions in Inflammatory Disease
TNF and RANKL are key cytokines driving chronic inflammatory and autoimmune diseases including rheumatoid arthritis, multiple sclerosis, and osteoporosis. While anti-TNF biologics have revolutionized treatment, they have significant drawbacks: progressive immunodeficiency, loss of response in some patients, high cost, and IV administration. Small-molecule protein-protein interaction (PPI) inhibitors that directly block TNF and RANKL trimerization represent a more accessible and versatile therapeutic approach. However, disrupting protein-protein interactions with small molecules is notoriously difficult — requiring both high affinity and selectivity while maintaining favorable pharmacokinetic properties.
Our Approach
An integrated drug discovery pipeline combining ligand-based and structure-based screening
Data Assembly & Ligand-Based Modeling
Compiled the largest available dataset of 2,481 known TNF inhibitors from the literature. Developed ligand-based predictive models using cheminformatics approaches to identify molecular features associated with TNF inhibition, building a foundation for rational compound selection.
Structure-Based Virtual Screening
Combined ligand-based models with structure-based docking against the TNF trimerization interface. Virtually screened approximately 15,000 small molecules with unknown activity to predict their interactions with TNF and RANKL proteins, prioritizing candidates based on predicted binding modes.
Compound Prioritization & Selection
The virtual screening pipeline identified 9 promising candidates from thousands of molecules. Compounds were prioritized based on predicted binding affinity, drug-likeness scores (Lipinski criteria), and commercial availability for rapid experimental validation.
Molecular Dynamics Simulations
Extended MD simulations using the EnalosMD suite rationalized the binding modes of top compounds at the molecular level. Confirmed stable interactions and favorable conformations at the TNF and RANKL trimerization interfaces, validating computational predictions.
In Vitro Validation
Comprehensive biological testing identified compounds T8 and T23 as potent direct inhibitors of TNF function with IC50 values comparable to the previously described inhibitor SPD304, but with significantly reduced toxicity profiles and improved cell permeability.
Dual Inhibitor Discovery
Both T8 and T23 validated as dual inhibitors of TNF and RANKL, effectively blocking biologically active trimer formation. These represent only the 2nd and 3rd published examples of dual small-molecule direct function inhibitors of TNF and RANKL.
Key Results
Powered by NovaMechanics Software
Enalos Asclepios KNIME Nodes
Used for molecular dynamics simulations, structure-based virtual screening, and automated docking pipelines. Enabled comprehensive validation of TNF and RANKL binding modes through extended MD simulations and binding free energy calculations.
Learn moreEnalos Cloud Platform
Hosted the TNF ligand-based predictive model as a web application for accessible screening and predictions. The platform democratizes access to the cheminformatics pipeline, enabling researchers worldwide to identify potential TNF and RANKL inhibitors at enalos.insilicotox.com/TNFPubChem/.
Learn moreMedia Highlights
How scientific media covered this breakthrough discovery
Scientists ID Two Molecules That Inhibit Proteins Involved in Chronic Inflammatory Disease
EurekAlert featured our dual TNF/RANKL inhibitor discovery, highlighting the potential for developing new treatments for inflammatory and autoimmune diseases with improved safety profiles compared to current biologics.
Read on EurekAlertBioinformatics Approach Can Identify Potential Therapies for MS, Other Diseases
Multiple Sclerosis News Today emphasized the implications of our cheminformatics pipeline for discovering novel treatments for multiple sclerosis and other inflammatory conditions, positioning the work as a significant advance in computational drug discovery.
Read on MS News TodayRelated Publication
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)
This study demonstrated that NovaMechanics' cheminformatics pipeline can successfully identify small-molecule PPI inhibitors — one of the most challenging targets in drug discovery. The dual TNF/RANKL inhibitors T8 and T23, with low toxicity profiles and demonstrated dual activity, represent promising lead compounds for developing novel treatments for inflammatory and autoimmune diseases including multiple sclerosis and rheumatoid arthritis. The open-access TNF predictive model continues to enable researchers globally to discover next-generation inhibitors.
Have a Similar Challenge?
Let's explore how our computational drug discovery pipeline can accelerate your research into protein-protein interaction inhibitors and other challenging targets.
Get in Touch