A gastrointestinal locally activating Janus kinase inhibitor to treat ulcerative colitis.

In this study, we integrated machine learning (ML), structure-tissue selectivity-activity-relationship (STAR), and wet lab synthesis/testing to design a gastrointestinal (GI) locally activating JAK inhibitor for ulcerative colitis treatment. The JAK inhibitor achieves site-specific efficacy through high local GI tissue selectivity while minimizing the requirement for JAK isoform specificity to reduce systemic toxicity. We used the ML model (CoGT) to classify whether the designed compounds were inhibitors or noninhibitors. Then we used the regression ML model (MTATFP) to predict their IC50 against related JAK isoforms of predicted JAK inhibitors. The ML model predicted MMT3-72, which was retained in the GI tract, to be a weak JAK1 inhibitor, while MMT3-72-M2, which accumulated in only GI tissues, was predicted to be an inhibitor of JAK1/2 and TYK2. ML docking methods were applied to simulate their docking poses in JAK isoforms. Application of these ML models enabled us to limit our synthetic efforts to MMT3-72 and MMT3-72-M2 for subsequent wet lab testing. The kinase assay confirmed MMT3-72 weakly inhibited JAK1, and MMT3-72-M2 inhibited JAK1/2 and TYK2. We found that MMT3-72 accumulated in the GI lumen, but not in GI tissue or plasma, but released MMT3-72-M2 accumulated in colon tissue with minimal exposure in the plasma. MMT3-72 achieved superior efficacy and reduced p-STAT3 in DSS-induced colitis. Overall, the integration of ML, the structure-tissue selectivity-activity-relationship system, and wet lab synthesis/testing could minimize the effort in the optimization of a JAK inhibitor to treat colitis. This site-specific inhibitor reduces systemic toxicity by minimizing the need for JAK isoform specificity.

CoGT: Ensemble Machine Learning Method and Its Application on JAK Inhibitor Discovery.

The discovery of new drug candidates to inhibit an intended target is a complex and resource-consuming process. A machine learning (ML) method for predicting drug-target interactions (DTI) is a potential solution to improve the efficiency. However, traditional ML approaches have limitations in accuracy. In this study, we developed a novel ensemble model CoGT for DTI prediction using multilayer perceptron (MLP), which integrated graph-based models to extract non-Euclidean molecular structures and large pretrained models, specifically chemBERTa, to process simplified molecular input line entry systems (SMILES). The performance of CoGT was evaluated using compounds inhibiting four Janus kinases (JAKs). Results showed that the large pretrained model, chemBERTa, was better than other conventional ML models in predicting DTI across multiple evaluation metrics, while the graph neural network (GNN) was effective for prediction on imbalanced data sets. To take full advantage of the strengths of these different models, we developed an ensemble model, CoGT, which outperformed other individual ML models in predicting compounds' inhibition on different isoforms of JAKs. Our data suggest that the ensemble model CoGT has the potential to accelerate the process of drug discovery.

A Precise Nanostructure of Folate-Overhung Mitoxantrone DNA Tetrahedron for Targeted Capture Leukemia.

Regular chemotherapy cannot eliminate leukemic cells, due to the sparse distribution of cancer cells in leukemia patients. Here, we report a precise nanostructure of folate-overhung mitoxantrone DNA tetrahedron that enables the treatment of leukemic cells by targeted action. Folate is used as a targeting molecule and synthesized with DNA strand in forming the folate-overhang DNA complement, and the complement is then separately base-paired onto six sides of the fabricated DNA tetrahedron. Mitoxantrone is used as an anticancer agent and intercalated into the double strands of the folate-overhung DNA tetrahedron for drug loading. The evaluation studies are performed on leukemia BALL-1 and K562 cells. The results demonstrate that the folate-overhung mitoxantrone DNA tetrahedra (approximately 25 nm) are able to target leukemic cells, transport across the nuclei membrane, induce the apoptosis, and enhance the overall efficacy of treating leukemic cells in vitro and in leukemia-bearing mice. This study provides a potential drug-containing DNA nanostructure, to clean the sparsely distributed leukemic cells in patients.

Lipid vesicles containing transferrin receptor binding peptide TfR-T12 and octa-arginine conjugate stearyl-R8 efficiently treat brain glioma along with glioma stem cells.

Surgery and radiotherapy cannot fully remove brain glioma; thus, chemotherapy continues to play an important role in treatment of this illness. However, because of the restriction of the blood-brain barrier (BBB) and the regeneration of glioma stem cells, post-chemotherapy relapse usually occurs. Here, we report a potential solution to these issues that involves a type of novel multifunctional vinblastine liposomes equipped with transferrin receptor binding peptide TfR-T12 and octa-arginine conjugate stearyl-R8. Studies were performed on brain glioma and glioma stem cells in vitro and were verified in brain glioma-bearing mice. The liposomes were transported across the BBB, killing brain glioma and glioma stem cells via the induction of necrosis, apoptosis and autophagy. Furthermore, we reveal the molecular mechanisms for treating brain glioma and glioma stem cells via functionalized drug lipid vesicles.

The use of functional epirubicin liposomes to induce programmed death in refractory breast cancer.

Currently, chemotherapy is less efficient in controlling the continued development of breast cancer because it cannot eliminate extrinsic and intrinsic refractory cancers. In this study, mitochondria were modified by functional epirubicin liposomes to eliminate refractory cancers through initiation of an apoptosis cascade. The efficacy and mechanism of epirubicin liposomes were investigated on human breast cancer cells in vitro and in vivo using flow cytometry, confocal microscopy, high-content screening system, in vivo imaging system, and tumor inhibition in mice. Mechanistic studies revealed that the liposomes could target the mitochondria, activate the apoptotic enzymes caspase 8, 9, and 3, upregulate the proapoptotic protein Bax while downregulating the antiapoptotic protein Mcl-1, and induce the generation of reactive oxygen species (ROS) through an apoptosis cascade. In xenografted mice bearing breast cancer, the epirubicin liposomes demonstrated prolonged blood circulation, significantly increased accumulation in tumor tissue, and robust anticancer efficacy. This study demonstrated that functional epirubicin liposomes could significantly induce programmed death of refractory breast cancer by activating caspases and ROS-related apoptotic signaling pathways, in addition to the direct killing effect of the anticancer drug itself. Thus, we present a simple nanomedicine strategy to treat refractory breast cancer.

Dual-functional drug liposomes in treatment of resistant cancers.

Efficacy of regular chemotherapy is significantly hampered by multidrug resistance (MDR) and severe systemic toxicity. The reduced toxicity has been evidenced after administration of drug liposomes, consisting of the first generation of regular drug liposomes, the second generation of long-circulation drug liposomes, and the third generation of targeting drug liposomes. However, MDR of cancers remains as an unsolved issue. The objective of this article is to review the dual-functional drug liposomes, which demonstrate the potential in overcoming MDR. Herein, dual-functional drug liposomes are referring to the drug-containing phospholipid bilayer vesicles that possess a dual-function of providing the basic efficacy of drug and the extended effect of the drug carrier. They exhibit unique roles in treatment of resistant cancer via circumventing drug efflux caused by adenosine triphosphate binding cassette (ABC) transporters, eliminating cancer stem cells, destroying mitochondria, initiating apoptosis, regulating autophagy, destroying supply channels, utilizing microenvironment, and silencing genes of the resistant cancer. As the prospect of an estimation, dual-functional drug liposomes would exhibit more strength in their extended function, hence deserving further investigation for clinical validation.

C-type natriuretic peptide-modified lipid vesicles: fabrication and use for the treatment of brain glioma.

Chemotherapy of brain glioma faces a major obstacle owing to the inability of drug transport across the blood-brain barrier (BBB). Besides, neovasculatures in brain glioma site result in a rapid infiltration, making complete surgical removal virtually impossible. Herein, we reported a novel kind of C-type natriuretic peptide (CNP) modified vinorelbine lipid vesicles for transferring drug across the BBB, and for treating brain glioma along with disrupting neovasculatures. The studies were performed on brain glioma U87-MG cells in vitro and on glioma-bearing nude mice in vivo. The results showed that the CNP-modified vinorelbine lipid vesicles could transport vinorelbine across the BBB, kill the brain glioma, and destroy neovasculatures effectively. The above mechanisms could be associated with the following aspects, namely, long circulation in the blood; drug transport across the BBB via natriuretic peptide receptor B (NPRB)-mediated transcytosis; elimination of brain glioma cells and disruption of neovasculatures by targeting uptake and cytotoxic injury. Besides, CNP-modified vinorelbine lipid vesicles could induce apoptosis of the glioma cells. The mechanisms could be related to the activations of caspase 8, caspase 3, p53, and reactive oxygen species (ROS), and inhibition of survivin. Hence, CNP-modified lipid vesicles could be used as a carrier material for treating brain glioma and disabling glioma neovasculatures.