Here, we show that integrated computational and biophysical approaches improve screening efficiency and finding hits in FBDD.

Attempts to design small molecule TNF-α inhibitors have not yet led to approved products. In this study, we followed a fragment-based screening approach to provide insight into designing small molecule inhibitors directly targeting TNF-α.

In collaboration with Key Organics Limited, we conducted a fragment-based screening study against TNF-α using our Integrated Medicinal/Computational Chemistry Platform. A surface plasmon resonance (SPR) "clean screen" of BIONET Premium Fragment Library was run to identify and remove fragments that bind non-specifically to the Biacore CM7 Sensor Chip. After this initial clean-up step, "binding level screens" were carried out for the remaining fragments to identify binders against the target protein and exclude fragments with atypical binding behavior. Top hits from the binding level screens will then be validated by "affinity screens" to verify binders and estimate affinity (K_D). In parallel, molecular modeling and X-ray crystallography for these fragments against TNF-α are currently underway in order to develop a structure-activity relationship (SAR) study for TNF-α.

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To cite this poster: Abdel-Haq, R., Assar, Z., Muzzarelli, K.M., et al.. Fragment-based drug discovery (FBDD) approach for TNF-α. Poster presented at: 18^th Annual Drug Discovery Chemistry Conference; April 10-13, 2023.