Peptides are emerging as an increasingly dependable class of therapeutics in the treatment of cancer and metabolic and cardiovascular diseases, which are all areas of high interest to the pharmaceutical industry. The global market for peptide therapeutics was valued at about 25 billion USD in 2018 and is estimated to reach 57.2 billion USD by the end of 2027. Here, we describe a method for the screening and deconvolution of combinatorial peptide libraries to discover compounds that target discrete signaling components of the NF-κB pathway. Recently, we used this approach to specifically disrupt the interaction between the JNK-activating kinase, MKK7, and the NF-κB-regulated antiapoptotic factor, GADD45β, in multiple myeloma (MM). We showed that the GADD45β/MKK7 complex is a functionally critical survival module downstream of NF-κB in MM cells and as such provides an attractive therapeutic target to selectively inhibit NF-κB antiapoptotic signaling in cancer cells. By integrating the library screening and deconvolution methods described here with a rational chemical optimization strategy, we developed the first-in-class GADD45β/MKK7 inhibitor, DTP3 (a D-tripeptide), which is now being trialed in MM and diffuse large B-cell lymphoma (DLBCL) patients. The same drug discovery approach may be generally applied to therapeutically target other key components of the NF-κB pathway in cancers beyond MM and DLBCL, as well as in non-malignant NF-κB-driven diseases.
Keywords: Apoptosis; Cancer; Combinatorial chemistry; Drug discovery; GADD45β; MKK7; NF-κB; Peptides; Targeted therapy.