Application of solid phase peptide synthesis to engineering PEO–peptide block copolymers for drug delivery

This work describes a simple, versatile solid-phase peptide-synthesis (SPPS) method for preparing micelle-forming poly(ethylene oxide)-block-peptide block copolymers for drug delivery. To demonstrate its utility, this SPPS method was used to construct two series of micelle-forming block copolymers (one of constant core-composition and variable length; the other of constant core length and variable composition). The block copolymers were then used to study in detail the effect of size and composition on micellization. The various block copolymers were prepared by a combination of SPPS for the peptide block, followed by solution–phase conjugation of the peptide block with a proprionic acid derivative of poly(ethylene oxide) (PEO) to form the PEO-b-peptide block copolymer. The composition of each block component was characterized by mass spectrometry (MALDI and ES-MS). Block copolymer compositions were characterized by ¹H NMR. All the block copolymers were found to form micelles as judged by transmission electron microscopy (TEM) and light scattering analysis. To demonstrate their potential as drug delivery systems, micelles prepared from one member of the PEO-b-peptide block copolymer series were physically loaded with the anticancer drug doxorubicin (DOX). Micelle static and dynamic stability were found to correlate strongly with micelle core length. In contrast, these same micellization properties appear to be a complex function of core composition, and no clear trends could be identified from among the set of compositionally varying, fixed length block copolymer micelles. We conclude that SPPS can be used to construct biocompatible block copolymers with well-defined core lengths and compositions, which in turn can be used to study and to tailor the behavior of block copolymer micelles.     

Drug metabolite cluster centers-based strategy for comprehensive profiling of Neomangiferin metabolites in vivo and in vitro and network pharmacology study on anti-inflammatory mechanism

Neomangiferin (NMF) is an extremely special xanthone that could be simultaneously attributed to C-glycoside and O-glycoside with a variety of biological activities, such as anti-inflammatory, antitumor, antipyretic, and so on. So far as we know, the metabolism profiling has been insufficient until now. Herein, Drug Metabolite Cluster Centers (DMCCs)-based Strategy has been developed to profile the NMF metabolites in vivo and in vitro. Firstly, the DMCCs was proposed depending on literature-related and preliminary analysis results. Secondly, the specific metabolic rule was implemented to screen the metabolites of candidate DMCCs from the acquired Ultra High Performance Liquid Chromatography Quadrupole Exactive Orbitrap Mass Spectrometry (UHPLC-Q-Exactive Orbitrap MS) data by extracted ion chromatography (EIC) method. Thirdly, candidate metabolites were accurately and tentatively identified according to the pyrolysis law of mass spectrometry, literature reports, comparison of reference substances, and especially the diagnostic product ions (DPIs) deduced preliminarily. Finally, network pharmacology was adopted to elucidate the anti-inflammatory action mechanism of NMF on the basis of DMCCs. As a result, 3 critical metabolites including NMF, Mangiferin (MF) and Norathyriol (NA) were proposed as DMCCs, and a total of 61 NMF metabolites (NMF included) were finally screened and characterized coupled with 3 different biological sample preparation methods including solid phase extraction (SPE), acetonitrile precipitation and methanol precipitation. Among them, 32 metabolites were discovered in rat urine, 30 in rat plasma, 12 in rat liver, 9 metabolites in liver microsomes and 8 in rat faeces, respectively. Our results also illustrated that NMF primarily underwent deglucosylation, glucuronidation, methylation, sulfation, dihydroxylation and their composite reactions in vivo and in vitro. Additionally, network pharmacology analysis based on DMCCs revealed 85 common targets of disease-metabolites, and the key targets were TNF, EGFR, ESR1, PTGS2, HIF1A, IL-2, PRKCA and PRKCB. They exerted anti-inflammatory effects mainly through the pathways of inflammatory response, calcium-dependent protein kinase C activity, nitrogen metabolism, pathways in cancer and so on. In general, our study constructed a novel strategy to comprehensive elucidate the biotransformation pathways of NMF in vivo and in vitro, and provided vital reference for further understanding its anti-inflammatory action mechanism. Moreover, the established strategy could be generalized to the metabolism and action mechanism study of other natural products.     

Characterization of CNS disorders and evaluation of therapy using structural and functional MRI

Modern drug development requires technologies that allow rapid translation from the preclinical to the clinical stage. It is obvious that non-invasive imaging modalities such as magnetic resonance imaging (MRI) will play a central role in this regard. This article reviews the use of structural and functional MRI readouts for characterization of central nervous system (CNS) disorders and evaluation of the efficacy of potential CNS drugs. Examples comprise dementia of Alzheimer's type, cerebral ischemia, and neuroinflammation covering both clinical and preclinical aspects. In these examples MRI has been used to obtain relevant structural information on brain atrophy, on the location and extent of ischemic brain areas, and on the number and distribution of demyelinated plaques. These structural data are complemented by readouts assessing the functional consequences associated with the pathomorphological changes. In the last decade, MRI has evolved into a standard tool for the development of CNS drugs. With regard to target-specific/molecular imaging applications MRI is limited by its inherently low sensitivity; complementary imaging modalities utilizing optical and radionuclear reporter systems will thus be required.     

Three-dimensional hydrogen-bond geometry and probability information from a crystal survey

Summary An extensive crystal survey of the Cambridge Structural Database has been carried out to provide hydrogen-bond data for use in drug-design strategies. Previous crystal surveys have generated 1D frequency distributions of hydrogen-bond distances and angles, which are not sufficient to model the hydrogen bond as a ligand-receptor interaction. For each hydrogen-bonding group of interest to the drug designer, geometric hydrogen-bond criteria have been derived. The 3D distribution of complementary atoms about each hydrogen-bonding group has been ascertained by dividing the space about each group into bins of equal volume and counting the number of observed hydrogen-bonding contacts in each bin. Finally, the propensity of each group to form a hydrogen bond has been calculated. Together, these data can be used to predict the potential site points with which a ligand could interact and there-fore could be used in molecular-similarity studies, pharmacophore query searching of databases, or de novo design algorithms.     

Automated site-directed drug design: An assessment of the transferability of atomic residual charges (CNDO) for molecular fragments

Summary In this paper a database of atomic residual charges has been constructed for all the molecular fragments defined previously in a combinatorial search of the Cambridge Structural Database. The charges generated for the atoms in each fragment are compared with charges calculated for whole molecules containing those fragments. The fragment atomic charges lie within 1 S.D. of the mean for 68%, and within 2 S.D. for 91%, of the atoms whose charges were computed for whole molecules. The actual charges on any atom are strongly influenced by the adjacent connected atoms. There is a large spread of atomic residual charge within the fragments database.     

The chromatographic properties of a mixed-bed stationary phase combining reversed-phase and strong anion exchange properties

Summary The feasibility of using columns prepared by mixing together ion exchange and reversed-phase packing materials, for the simultaneous separation of ionised and unionised molecules, has been examined using a range of test solutes. Columns prepared in this way showed chromatographic properties which were intermediate between those of the individual phases. The dual nature of the retention mechanism allowed the retention of ionisable molecules to be adjusted using pH whilst that of uncharged compounds was unaffected. The simultaneous chromatography of model compounds and their glucuronide, sulphate and glycine conjugates, under a variety of conditions, was demonstrated.     

聚己内酯聚醚嵌段共聚物和共混物的表面性质对其药物释放行为的影响

聚己内酯聚醚嵌段共聚物和共混物的表面性质对其药物释放行为的影响王卫华，贝建中，王智峰，王身国（中国科学院化学研究所北京１０００８０）关键词聚己内酯聚醚嵌段共聚物，共混物，电子能谱，表面性质，药物释放行为聚己内醋（ＰＣＬ）具有优良的药物通透性和生物相容...     

高效前沿分析的发展及在药物-蛋白结合研究中的应用

介绍了高效前沿分析方法的原理、特点、种类，综述了它在药物与蛋白结合研究中的应用及国内外研究概况；通过与高效液相色谱／前沿分析比较，阐明了毛细管电泳／前沿分析在药物蛋白结合研究中的优势；分析了在药物与蛋白结合研究中所采用的各种研究方法，通过与这些研究方法的比较，阐明了高效前沿分析的优越性及其广阔的应用前景，同时提出了在高效前沿分析方法中有待完善和注意的问题。     

径向基-偏最小二乘-贝叶斯方法及其在化学模式分类中的应用

提出一种用于模式分类的RBF-PLS—Bayes方法。它集成地应用径向基(RBF)变换与偏最小二乘(PLS)方法，从原有模式中提取出分类能力甚强的成分，然后进行贝叶斯(Bayes)判别。这种集成方法尤其适用于复杂化学信息的模式分类，本文将其应用于两种类型的化学模式分类问题，均取得了令人满意的效果。与经典的判别分析方法和单纯的神经网络方法相比，具有明显的优越性。