SG-2000

Aberrant elevated Src activity is related to lung cancer growth and metastasis. Therefore, the development of potent small molecule inhibitors to target Src kinase is a potential therapeutic strategy for lung cancer. This study aimed to develop a computational model for the in silico screening of Src inhibitors and then assess the suppressive effect of candidate compounds on cellular functions. A 3D-quantitative structure-activity relationship (QSAR) pharmacophore model consisting of two hydrogen bond acceptors and two hydrophobic regions was constructed by using 28 structurally diverse compounds with IC₅₀ values spanning four orders of magnitude. A National Cancer Institute (NCI) compound dataset was employed for virtual screening by applying the pharmacophore model and molecular docking. Candidate compounds were chosen from the top 20% of scored hits. Among these compounds, the suppressive effects of 30 compounds available in the NCI on Src phosphorylation were validated by using an enzyme-linked immunosorbent assay. Among these compounds, SJG-136, a pyrrolobenzodiazepine dimer, showed a significant inhibitory effect against Src activity in a dose-dependent manner. Further investigations showed that SJG-136 can inhibit lung cancer cell proliferation, clonogenicity, invasion and migration in vitro and tumour growth in vivo. Furthermore, SJG-136 also had an inhibitory effect on Src-related signaling pathways, including the FAK, paxillin, p130Cas, PI3K, AKT, and MEK pathways. In conclusion, we have established a pharmacophore-based virtual screening approach to identify novel Src inhibitors that can inhibit lung cancer cell growth and motility through suppressing Src-related pathways. These findings may contribute to the development of targeted drugs for lung cancer treatment, such as lead compounds.

We describe the development and evaluation of pyrrolobenzodiazepines (PBDs) in poly(dl-lactide-co-glycolide) and lipid nanoparticle drug delivery systems. We have established that the partition coefficient (LogP) of PBD is a key influencer of the encapsulation efficiency in nanoparticle systems, with higher LogP values associated with higher encapsulation efficiencies toward increased drug payload delivery and better antitumor efficacy. Cytotoxicity assays demonstrated that compounds with higher LogP values demonstrated higher 50% inhibitory concentration values than the free drug. In vivo efficacy studies in mice demonstrated that a single injection of nanoparticle PBD formulations could inhibit tumor growth for nearly 3 weeks, whereas the free drug failed to inhibit growth. Importantly, mice treated with PBD-loaded nanoparticles did not experience significant loss of body weight. These data demonstrate that nanoparticles containing PBD molecules can be used as an alternative to the widely used antibody drug conjugate approach in delivering cytotoxic PBDs.