Smart Targeted Delivery Systems for Enhancing Antitumor Therapy of Active Ingredients in Traditional Chinese Medicine

As a therapeutic tool inherited for thousands of years, traditional Chinese medicine (TCM) exhibits superiority in tumor therapy. The antitumor active components of TCM not only have multi-target treatment modes but can also synergistically interfere with tumor growth compared to traditional chemotherapeutics. However, most antitumor active components of TCM have the characteristics of poor solubility, high toxicity, and side effects, which are often limited in clinical application. In recent years, delivering the antitumor active components of TCM by nanosystems has been a promising field. The advantages of nano-delivery systems include improved water solubility, targeting efficiency, enhanced stability in vivo, and controlled release drugs, which can achieve higher drug-delivery efficiency and bioavailability. According to the method of drug loading on nanocarriers, nano-delivery systems can be categorized into two types, including physically encapsulated nanoplatforms and chemically coupled drug-delivery platforms. In this review, two nano-delivery approaches are considered, namely physical encapsulation and chemical coupling, both commonly used to deliver antitumor active components of TCM, and we summarized the advantages and limitations of different types of nano-delivery systems. Meanwhile, the clinical applications and potential toxicity of nano-delivery systems and the future development and challenges of these nano-delivery systems are also discussed, aiming to lay the foundation for the development and practical application of nano-delivery systems of TCM in clinical settings.

Ligands selectively tune the local and global motions of neurotensin receptor 1 (NTS(1))

Nuclear magnetic resonance (NMR) studies have revealed that fast methyl sidechain dynamics can report on entropically-driven allostery. Yet, NMR applications have been largely limited to the super-microsecond motional regimes of G protein-coupled receptors (GPCRs). We use ¹³C^ε-methionine chemical shift-based global order parameters to test if ligands affect the fast dynamics of a thermostabilized GPCR, neurotensin receptor 1 (NTS₁). We establish that the NTS₁ solution ensemble includes substates with lifetimes on several, discrete timescales. The longest-lived states reflect those captured in agonist- and inverse agonist-bound crystal structures, separated by large energy barriers. We observe that the rapid fluctuations of individual methionine residues, superimposed on these long-lived states, respond collectively with the degree of fast, global dynamics correlating with ligand pharmacology. This approach lends confidence to interpreting spectra in terms of local structure and methyl dihedral angle geometry. The results suggest a role for sub-microsecond dynamics and conformational entropy in GPCR ligand discrimination.

[Lectins in Viscum:a progress review]

Viscum plants,the evergreen perennial parasitic shrubs or subshrubs,are mainly distributed in tropical and subtropical regions. There are about 70 Viscum species around the world,including 11 species and one variety in China. Mistletoe lectins are typeⅡ ribosome-inactivating proteins( RIPs) extracted from Viscum plants with anticancer and immunoregulatory activities. Many studies have focused on the mistletoe lectins isolated from V. album in Europe and V. album var. coloratum distributed in South Korea,respectively,and several preparations,such as Iscucin Ⓡ,were developed and clinically applied for cancer treatment. Although Viscum plants are widely distributed in China,only a few studies of mistletoe lectins have been reported. The recent progress of mistletoe lectins was reviewed from extraction,purification,quantitative/qualitative detection,molecular structure,pharmacological activities,toxicities,and clinical application,aiming at providing a reference for in-depth research and utilization of mistletoe lectins produced in China.

Ligand-Dependent Conformational Transitions in Molecular Dynamics Trajectories of GPCRs Revealed by a New Machine Learning Rare Event Detection Protocol

Central among the tools and approaches used for ligand discovery and design are Molecular Dynamics (MD) simulations, which follow the dynamic changes in molecular structure in response to the environmental condition, interactions with other proteins, and the effects of ligand binding. The need for, and successes of, MD simulations in providing this type of essential information are well documented, but so are the challenges presented by the size of the resulting datasets encoding the desired information. The difficulty of extracting information on mechanistically important state-to-state transitions in response to ligand binding and other interactions is compounded by these being rare events in the MD trajectories of complex molecular machines, such as G-protein-coupled receptors (GPCRs). To address this problem, we have developed a protocol for the efficient detection of such events. We show that the novel Rare Event Detection (RED) protocol reveals functionally relevant and pharmacologically discriminating responses to the binding of different ligands to the 5-HT_2AR orthosteric site in terms of clearly defined, structurally coherent, and temporally ordered conformational transitions. This information from the RED protocol offers new insights into specific ligand-determined functional mechanisms encoded in the MD trajectories, which opens a new and rigorously reproducible path to understanding drug activity with application in drug discovery.

A Machine Learning Approach for the Discovery of Ligand-Specific Functional Mechanisms of GPCRs

G protein-coupled receptors (GPCRs) play a key role in many cellular signaling mechanisms, and must select among multiple coupling possibilities in a ligand-specific manner in order to carry out a myriad of functions in diverse cellular contexts. Much has been learned about the molecular mechanisms of ligand-GPCR complexes from Molecular Dynamics (MD) simulations. However, to explore ligand-specific differences in the response of a GPCR to diverse ligands, as is required to understand ligand bias and functional selectivity, necessitates creating very large amounts of data from the needed large-scale simulations. This becomes a Big Data problem for the high dimensionality analysis of the accumulated trajectories. Here we describe a new machine learning (ML) approach to the problem that is based on transforming the analysis of GPCR function-related, ligand-specific differences encoded in the MD simulation trajectories into a representation recognizable by state-of-the-art deep learning object recognition technology. We illustrate this method by applying it to recognize the pharmacological classification of ligands bound to the 5-HT_2A and D2 subtypes of class-A GPCRs from the serotonin and dopamine families. The ML-based approach is shown to perform the classification task with high accuracy, and we identify the molecular determinants of the classifications in the context of GPCR structure and function. This study builds a framework for the efficient computational analysis of MD Big Data collected for the purpose of understanding ligand-specific GPCR activity.

2D-DIGE as a strategy to identify serum protein biomarkers to monitor pharmacological efficacy in dopamine-dictated states of Parkinson's disease and schizophrenia

OBJECTIVES

Parkinson's disease and schizophrenia are clinical scenarios that occur due to dopaminergic deficit and hyperactivity in the midbrain, respectively. Current pharmacological interventions for these two diseases therefore aim to restore normal dopamine levels in the midbrain. But during therapy, there is a overshooting of dopamine concentrations that result in hallucinations in Parkinson's disease patients and extra-pyramidal symptoms in schizophrenic patients. This causes a lot of inconvenience to the patents and the clinicians. There are no tests currently available to monitor drug efficacy in these two neuropsychiatric diseases.

MATERIALS AND METHODS

Parkinson's disease and schizophrenic naïve patients were recruited. Serum proteins isolated from these two clinical phenotypes were labeled with fluorescent cyanine dyes and analyzed by two-dimensional difference in gel electrophoresis proteomic experiment. Differentially expressed spots that had consistent expression pattern across five sets of biological replicate gels were trypsin digested and subjected to mass spectrometric analysis for protein identification. Validation experiments were done for the identified proteins using antibody-based assay on a patient cohort that included naïve, treated, and those who had side effects.

RESULTS

Serum α- and β-globin chains were identified as differentially expressed proteins having threefold higher expressions in Parkinson's patients as compared to schizophrenia. Interestingly, concentrations of these two proteins had an inverse correlation across clinical phenotypes in the dopaminergic spectrum. RBC contamination as a source for these proteins was ruled out.

CONCLUSION

There is a clear association of free serum globin with dopaminergic clinical states. This lays a platform for protein biomarker-based monitoring of pharmacological efficacy in Parkinson's disease and schizophrenia.

Preclinical study and clinical trial of a novel therapeutic vaccine against multi-drug resistant tuberculosis

[Purpose] Multi-drug resistant (MDR), Mycobacterium tuberculosis (TB) is a big problem in the world. We have developed novel TB therapeutic vaccine (HVJ-E/HSP65 DNA +IL-12 DNA). [Methods and Results] DNA vaccine expressing TB heat shock protein 65 and IL-12 was delivered by the hemagglutinating virus of Japan (HVJ)-envelope. This vaccine provided remarkable protective efficacy and strong therapeutic efficacy against MDR-TB and XDR-TB in murine models. Furthermore, this vaccine provided therapeutic efficacy of prolongation of survival time of TB infected monkeys and augmented the immune responses. Therefore, the preclinical tests were studied for clinical trial. The injection of 100 μg of the vaccine /mouse i.m. three times in two weeks induced significantly strong production of IFN-γ and IL-2. 100 μg and 200 μg DNA vaccine/mouse i.m. augmented the production of these cytokines compared with 25 μg DNA vaccine/mouse i.m.. The ratio of 100 μg pDNA to 1AU HVJ-E enhanced the production of IFN-γ and IL-2. The decrease in the number of M. tuberculosis in liver of mice was observed by the vaccination of 100μg pDNA. By using these conditions, safety pharmacology study and toxicology test is being studied in monkeys administered by GMP level DNA vaccines. By the toxicology test using monkeys, high dose GMP level vaccine/ monkey is administrated. Safety pharmacological study of repeated administration is also being investigated in GLP level. Furthermore, we have planned to do clinical phase I trial. Targets are human patients with MDR-TB. The safety and tolerability of the vaccine will be evaluated. [Conclusion and recommendations] These data indicate that our novel vaccine might be useful against tuberculosis including XDR-TB and MDR-TB for human therapeutic clinical applications.