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The A-type Aurora kinase is upregulated in many human cancers, and it stabilizes MYC-family oncoproteins, which have long been considered an undruggable target. Here, we describe the design and synthesis of a series of pyrimidine-based derivatives able to inhibit Aurora A kinase activity and reduce levels of cMYC and MYCN. Through structure-based drug design of a small molecule that induces the DFG-out conformation of Aurora A kinase, lead compound 13 was identified, which potently (IC50 < 200 nM) inhibited the proliferation of high-MYC expressing small-cell lung cancer (SCLC) cell lines. Pharmacokinetic optimization of 13 by prodrug strategies resulted in orally bioavailable 25, which demonstrated an 8-fold higher oral AUC (F = 62.3%). Pharmacodynamic studies of 25 showed it to effectively reduce cMYC protein levels, leading to >80% tumor regression of NCI-H446 SCLC xenograft tumors in mice. These results support the potential of 25 for the treatment of MYC-amplified cancers including SCLC.

Machine learning is a well-known approach for virtual screening. Recently, deep learning, a machine learning algorithm in artificial neural networks, has been applied to the advancement of precision medicine and drug discovery. In this study, we performed comparative studies between deep neural networks (DNN) and other ligand-based virtual screening (LBVS) methods to demonstrate that DNN and random forest (RF) were superior in hit prediction efficiency. By using DNN, several triple-negative breast cancer (TNBC) inhibitors were identified as potent hits from a screening of an in-house database of 165,000 compounds. In broadening the application of this method, we harnessed the predictive properties of trained model in the discovery of G protein-coupled receptor (GPCR) agonist, by which computational structure-based design of molecules could be greatly hindered by lack of structural information. Notably, a potent (~ 500 nM) mu-opioid receptor (MOR) agonist was identified as a hit from a small-size training set of 63 compounds. Our results show that DNN could be an efficient module in hit prediction and provide experimental evidence that machine learning could identify potent hits in silico from a limited training set.

Upregulation of Aurora kinases has been associated with increased tumor progression, and thus they are appealing targets for the development of anti-cancer therapies. In addition to have a critical role in cell cycle regulation, Aurora kinases have been shown to stabilize MYC-family oncoproteins for the maintenance of malignancy. Aurora kinase inhibitors such as Alisertib has demonstrated compelling anti-tumor efficacies; however, the reported side effects including serious haematological disturbances have limited its risk-benefit ratio in clinical use. In this study we discovered a novel pyrimidine-based Aurora kinase inhibitor compound A that degraded MYC- and MYCN- oncoproteins with better potency than Alisertib. The acyl-based prodrug design leads to the discovery of compound B which was able to regress MYC- or MYCN- overexpressing tumor xenografts including small cell lung cancer, neuroblastoma, hepatocellular carcinoma and medulloblastoma using a once-a-week (QW) oral dosing regimen. Pharmacokinetic studies revealed that the tumor/plasma ratio of compound B was about 20 at 24 h post drug administration, and the active compound remained detectable in the tumors after 7 days. No significant haematological or liver/kidney biochemical aberration was observed in mice treated with up to 500 mg/kg of DBPR728 on a QW dosing regimen in a 21-day cycle. The unique pharmacokinetic and molecular properties of compound B hold potential clinical promise for treating MYC- and MYCN- amplified tumors with manageable on-target haematological adverse effects caused by Aurora kinase inhibition. Citation Format: Ya-Hui Chi, Chun-Ping Chang, Teng-Kuang Yeh, Wan-Ping Wang, Yen-Ting Chen, Chia-Hua Tsai, Yan-Fu Chen, Yi-Yu Ke, Jing-Ya Wang, Ching-Ping Chen, Tsung-Chih Hsieh, Mine-Hsine Wu, Chiung-Tong Chen. Targeting myc-amplified cancers with a novel prodrug inhibiting aurora A kinase [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 523.

Herein, we report the total synthesis of landomycins Q and R as well as the aglycone core, namely anhydrolandomycinone and a related core analogue. The synthesis features an acetate-assisted arylation method for construction of the hindered B-ring in the core component and a one-pot aromatization–deiodination–denbenzylation procedure to streamline the global functional and protecting group manuipulation. Subsequent cytotoxicity and antibacterial studies revealed that the landomycin R is a potential antibacterial agent against methicillin-resistant Staphylococcus aureus.

Small cell lung cancer (SCLC) accounts for approximately 15% of all lung cancers, leading to ~30,000 deaths each year in the United States. SCLC patients often present with metastasis at time of diagnosis, excluding surgery as a treatment option. While patients show high response rate to standard chemotherapy such as cisplatin/etoposide, they soon develop drug resistance and disease progression. Therefore, new therapeutic strategies are urgently needed for SCLC. BPR6K609S0 is a novel Aurora kinase inhibitor which has been designed to inhibit the kinase activity of Aurora A, and induces proteasome-mediated degradation of MYC. The BPR6K609S0 active molecule provokes cell apoptosis and inhibits proliferation of several SCLC cell lines with IC50 < 100 nM. Oral administration of BPR6K609 induces >60 % tumor regression in a NCI-H446 xenograft mouse model. In addition, BPR6K609 further reduces tumor progression in NCI-H446 xenograft mice pre-treated with LY3295668, an Aurora A-selective inhibitor which is currently under clinical investigation. These results support the clinical potential of BRP6K609S0 for the treatment of SCLC. Citation Format: Ya-Hui Chi, Chun-Ping Chang, Yi-Yu Ke, Wen-Hsing Lin, Wan-Ping Wang, Chia-Hua Tsai, Yen-Ting Chen, Yu-Jie Su, Ming-Chun Hung, Zhong-Wei Wu, Mine-Hsine Wu, Teng-Kuang Yeh, Ching-Ping Chen, Jen-Shin Song, Chiung-Tong Chen, Chuan Shih. BPR6K609: An Aurora kinase inhibitor targeting small cell lung cancer with MYC amplification [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1937.

Indoleamine 2,3-dioxygenase is a heme-containing enzyme implicated in the down regulation of the anti-tumor immune response, and considered a promising anti-cancer drug target. Several pharmaceutical companies, including Pfizer, Merck, and Bristol-Myers Squibb, are known to be in pursuit of IDO inhibitors, and Incyte recently reported good results in the phase II clinical trial of the IDO inhibitor Epacadostat. In previous work, we developed a series of IDO inhibitors based on a sulfonylhydrazide core structure, and explored how they could serve as potent IDO inhibitors with good drug profiles. Herein, we disclose the development of the 4-bromophenylhydrazinyl benzenesulfonylphenylurea 5k, a potent IDO inhibitor which demonstrated 25% tumor growth inhibition in a murine CT26 syngeneic model on day 18 with 100 mg/kg oral administration twice daily, and a 30% reduction in tumor weight. Pharmacodynamic testing of 5k found it to cause a 25% and 21% reduction in kyn/trp ratio at the plasma and tumor, respectively. In the CT26 tumor model, 5k was found to slightly increase the percentage of CD3+ T cells and lymphocyte responsiveness, indicating that 5k may have potential in modulating anti-tumor immunity. These data suggest 5k to be worthy of further investigation in the development of anti-tumor drugs.