后基因组研究与新药开发

传统的药物开发方法在很多方面受到制约，而新的生物技术以及计算机技术为药物开发提供了新的思路．应用现代生物学的理论和技术以及计算机技术来寻找药物作用的靶点，进行药物作用机制的研究以及进行新药毒理学和药动学的研究可以大大提高新药开发的效率．     

抗癌药物靶向制剂的研究现状

抗癌靶向药物制剂能使药物选择性地与靶组织在细胞或亚细胞水平上发生反应,使药物能够可控性地分布,并于靶区持续缓慢地释放药物,有效降低其对正常组织的毒副作用,从而提高化疗疗效.针对目前国内外正在研究并取得了一定进展的抗癌靶向药物制剂,进行了全面客观的综述.通过大量文献,从靶向治疗设计模式、靶向制剂的分类、抗癌靶向药物载体及影响药物靶向性的因素等方面进行探讨.发现尽管靶向制剂广泛应用于临床尚需时日,但它们对于克服肿瘤治疗中的毒副作用,从而提高疗效具有不可忽视的作用.     

社区卫生服务在药品不良反应监测中的作用

药物不良反应(ADR)对于民众的健康和生命安全有着重要的影响.社区卫生服务凭借其所具有的特征和优势,在减少药品不良反应中具有弥补药品上市前研究的不足,为上市后再评价提供服务;促进临床合理用药;促进新药的研制开发;及时发现重大药害事件,防止药害事件的蔓延和扩大,保障公众健康和社会稳定的作用.     

54例住院患者单日用药的合理性分析

为了解心内科、骨科住院患者单日的用药情况,评判两科药物使用的合理性,应用“合理用药监测软件系统（PASS系统）”对住院患者的用药进行了分析,共监测54名患者329条医嘱。结果是54名住院患者在住院期间共使用药物316种,在329条医嘱中,不合理用药均为心内科用药。通过对网科用药的分析,表明临床应加强对合理用药的监测,尽量减少用药品种,避免不合理的联用．以有助于提高住院患者的合理用药水平。     

A pathway profile-based method for drug repositioning

Finding new applications for existing pharmaceuticals,known as drug repositioning,is a validated strategy for resolving the problem of high expenditure but low productivity in drug discovery.Currently,the prevalent computational methods for drug repositioning are focused mainly on the similarity or relevance between known drugs based on their "features",including chemical structure,side effects,gene expression profile,and/or chemical-protein interactome.However,such drug-oriented methods may constrain the newly predicted functions to the pharmacological functional space of the existing drugs.Clinically,many drugs have been found to bind "off-target"(i.e.to receptors other than their primary targets),which can lead to undesirable effects.In this study,which integrates known drug target information,we propose a disease-oriented strategy for evaluating the relationship between drugs and disease based on their pathway profile.The basic hypothesis of this method is that drugs exerting a therapeutic effect may not only directly target the disease-related proteins but also modulate the pathways involved in the pathological process.Upon testing eight of the global best-selling drugs in 2010(each with more than three targets),the FDA(Food and Drug Administration,USA)-approved therapeutic function of each was included in the top 10 predicted indications.On average,60% of predicted results made using our method are proved by literature.This approach could be used to complement existing methods and may provide a new perspective in drug repositioning and side effect evaluation.     

纳米载体及其药物释放

通过纳米载体运输药物,并在特定的组织释放药物已经成为生物医学的热门研究之一.由于实体肿瘤的高通透性和滞留效应,纳米颗粒容易进入肿瘤细胞,并在肿瘤细胞中富集,因此以纳米粒子为载体加载药物并在目标细胞或组织释放药物可以提高靶部位的药物浓度,增加药效,降低药物对生物体全身的毒副作用.通常,载药的纳米粒子释放药物的方式有两种,即扩散型释放与侵袭型释放.而刺激纳米粒子释放药物的方式多种多样,包括pH响应、酶响应、光响应、磁响应以及超声波响应等.主要介绍了多功能纳米粒子的载药原理及其研究现状.     

Docking and molecular dynamics studies on CYP2D6

Drug-metabolizing enzymes, also known as cytochrome P450s, are a superfamily of hemoglobin responsible for metabolizing more than 90% clinical drugs. Cytochrome P450 2D6 (CYP2D6) is a significant member of cytochrome P450s for the reason of metabolizing about 20% clinical drugs. In this paper, molecular docking and molecular dynamic simulations are used to investi- gate the active site of CYP2D6, roles of essential amino acids within the active site and time-dependent protein energy changes. The results suggest that amino acids Glu216, Asp301, Ser304 and Ala305 in the active site are likely to form hydrogen bonding interac-tions with substrates; the benzene ring of Phe120 and aromatic ring in the substrates form ∏-∏ interactions. In addition, molecular dynamics simulations prove that the catalytic conformation of CYP2D6 without ligands can be obtained by their own atomic fluctuations. The impact of ligands on protein system energy and large conformational shift is not very large. Cytochrome P450s is known for their genetic polymorphisms, which will result in severe adverse drug reactions. Ideally, we hope to use mo- lecular modeling to investigate the differences between the substrates of wild-type and mutants while they are bonded with drugs, and predict the drug metabolizing ability of mutants. Reduce the possibility for people taking drugs that they can not metabolize, therefore reduce the rate of adverse drug reactions, and eventually establish a platform of personalized drugs to largely benefit human health.     

阿霉素对离体培养心肌细胞DNA合成的影响

阿霉素被视为治疗癌症最重要的药物之一,尤其在治疗硬性肿瘤方面特别有效。由于它引起心肌细胞损伤的副作用,因而在临床用上受到限制。 本文以离体培养乳鼠心肌细胞为实验材料,研究了阿霉素对心肌细胞DNA合成的影响,并对SOD等药物的保护作用进行了初步观察。实验结果表明,阿霉素对离体心肌细胞DNA合成有较大的影响,随着阿霉素剂量的加大和给药时间的延长,心肌细胞DNA合成的抑制作用增大。 SOD等药物对阿霉素所致的心肌细胞DNA合成的抑制有明显的保护作用。其中SOD为自由基的清除剂,健心Ⅰ号对自由基也有一定的清除能力,氦酯是抗衰老药物,而衰老一般认为与膜脂质过氧化有关,而自由基又是与脂质过氧化密切关系着的。 从本文的直接和间接结果提示:阿霉素所致心肌细胞DNA合成的抑制有可能与它产生自由基的作用有关。     

药代动力学在新药成药性转换医学研究中的作用

 全新分子实体作为新药的研发是一个长期的创新研究,是一个涉及多学科的系统工程。转换研究可以将新候选药物分子的基础实验室研究、临床前研究、临床评价和临床应用广泛联系在一起,建立新的开发模式,进而缩短研发周期和加快向临床推广速度。在全新研发过程和临床试验中,药物代谢和药物处置的属性特征(吸收、分布、代谢、排泄)是用以评价候选药物成药可能性的重要标准。因此,在整个全新的研发模式里,药代动力学研究对于全新分子实体在转换研究过程中的评估起着至关重要的作用。从实验室到临床,从临床到市场的转换研究方式对于提高效率是一种非常重要的策略,其中每一步都涉及大量的药代动力学研究;某一种化学实体成药可能性、早期失败、早期出局等问题可以在第一时间发现。因此,药代动力学评估在药物发现、设计、研发过程中对提高效率、控制成本并进一步获得安全有效的药物有重要价值。     

新医改下对药品价格的一点思考

目的:对药品价格调整中出现的问题进行探讨并提出建议。方法:分析廉价实用药品退市、部分药品"改头换面"高价上市等情况出现的原因。结论:进一步完善药品定价机制;加强医疗机构的公益补偿将有利于在新医改下药品价格回归的稳定、合理。     

人参皂甙Rh2抗肿瘤作用机制的研究

恶性肿瘤治疗至今尚无好的方法.传统化疗药因其缺乏特异性的细胞毒性作用,治疗中容易造成正常细胞的损伤,从而引起一系列的并发症.人参皂甙Rh2是人参中提取的天然活性成分,具有很高的抗肿瘤活性,而对正常细胞无毒副作用.文章从人参皂甙Rh2的抗肿瘤作用机制(抑制细胞增殖、诱导细胞凋亡、诱导分化、抑制肿瘤DNA合成、提高荷瘤机体的免疫功能和抑制肿瘤转移、抗肿瘤耐药性增强、其他化疗药物对耐药肿瘤作用)等方面进行研究.     

微针给药系统的研究进展

微针是一种具有微米尺度的经皮给药技术,从内部结构可分为实心与空心微针.制作微针的材料主要有硅、金属、聚合物等.微针增强了皮肤对药物尤其是大分子药物的渗透性,不会到达神经分布丰富的皮肤深层组织,并且使用方便,因此是一种高效、无痛、安全的经皮给药方式.微针在胰岛素给药、卵清蛋白的免疫接种、缓控释给药、微量输液等方面的研究为微针经皮给药提供了应用可能.     

高分子药物研究进展

综述了高分子药物的研究进展，将高分子药物分为具有药理活性的高分子聚合物、高分子络合物药物、高分子微胶囊药物以及高分子载体药物4大类，并对其在药学上的应用进行了阐述．     

采用偏最小二乘法的基因-药物共模块识别

首先,将药物二维化学结构转化为数值序列,计算药物之间的皮尔逊相关系数,进而构建药物关联网络;然后,在带有基因网络约束的稀疏偏最小二乘算法的基础上,加入药物关联网络信息,提出伴有基因和药物关联网络正则约束的稀疏偏最小二乘(SGDPLS)算法;最后,将SGDPLS算法应用于基因-药物共模块识别.结果表明:药物关联网络信息的加入能够有效提高所识别的共模块中基因模块与药物模块的相关性,增加共模块的生物可解释性.     

基于流形正则化非负矩阵分解预测药物-靶蛋白作用关系

识别药物-靶蛋白作用关系是当前药物研究的重要内容,其可帮助识别已有药物的新功能,发现药物的"偏靶蛋白"等。现有预测算法对新药物的作用靶蛋白,及新靶蛋白的作用药物预测存在困难,由此提出一种新奇的基于流形正则化非负矩阵分解的新药物/新靶蛋白作用关系预测算法,该方法首先通过聚类算法构建新药物/新靶蛋白的初始作用标签,然后设计引入流形学习正则化约束的非负矩阵分解算法预测药物-靶蛋白作用关系,最后在四个经典数据集中测试,并与最新预测算法BLM-NII、RLS-WNN和WKNKN+WGRMF算法进行比较,证明本文算法可获取较高的预测精度。     

Cell-to-cell spread of HIV permits ongoing replication despite antiretroviral therapy

Latency and ongoing replication have both been proposed to explain the drug-insensitive human immunodeficiency virus (HIV) reservoir maintained during antiretroviral therapy. Here we explore a novel mechanism for ongoing HIV replication in the face of antiretroviral drugs. We propose a model whereby multiple infections per cell lead to reduced sensitivity to drugs without requiring drug-resistant mutations, and experimentally validate the model using multiple infections per cell by cell-free HIV in the presence of the drug tenofovir. We then examine the drug sensitivity of cell-to-cell spread of HIV, a mode of HIV transmission that can lead to multiple infection events per target cell. Infections originating from cell-free virus decrease strongly in the presence of antiretrovirals tenofovir and efavirenz whereas infections involving cell-to-cell spread are markedly less sensitive to the drugs. The reduction in sensitivity is sufficient to keep multiple rounds of infection from terminating in the presence of drugs. We examine replication from cell-to-cell spread in the presence of clinical drug concentrations using a stochastic infection model and find that replication is intermittent, without substantial accumulation of mutations. If cell-to-cell spread has the same properties in vivo, it may have adverse consequences for the immune system, lead to therapy failure in individuals with risk factors, and potentially contribute to viral persistence and hence be a barrier to curing HIV infection.     

Ranking effects of candidate drugs on biological process by integrating network analysis and Gene Ontology

There are high preclinical attrition rates in current drug discovery. The efficient assessment approach in the high throughout candidate drugs screening still needs great improvement. We propose two hypotheses. First, both drug action process and biological process can be converted to a common space of gene or gene product profiling. Second, the strength of drug action on biological process can be realized in the context of biological network. Based on the above hypotheses, we establish an algorithm termed Network-based Assessment for Drug Action (NADA) to assess the action strength of candidate drugs on certain biological processes. Then NADA is used to prioritize the effects of six compounds from traditional Chinese medicine on endothelial cell migration, a simple process defined by Gene Ontology, in the biological network specific for a given pathological process, angiogenesis. The computational results are subsequently tested by the experiment on the migration of Human Umbilical Vein Endothelial Cells in vitro. The experimental ranks for six compounds generally agree with the predicted output of NADA. NADA also outperforms the DAVID and meet/min methods in terms of the experimental orders, suggesting that the network topological features may have a key role in catching the mechanistic relationship between drug action and biological process. Hopefully, the progress of network biology approaches for deciphering complex diseases will further expedite the preclinical screening and accelerate the development of treatment modalities.     

基于外部知识的药物相互作用关系抽取方法

药物相互作用是指药物之间存在的抑制或促进等作用. 针对目前方法在不同关系类别上的抽取结果差异较大的问题,论文提出了一种利用外部知识的关系抽取模型,该方法首先对外部药物数据库中的信息进行处理,构建带有药物描述信息的数据集,然后在该数据集上进行模型训练,并保存最优模型,最后将该最优模型与药物关系抽取模型相结合,进行药物关系抽取,从而更好的利用了药物数据库中已有的知识,缓解了不同关系类别抽取结果差异较大的问题,提高了抽取效果. 在DDIExtraction 2013数据集上的实验结果表明,论文方法的F1值优于目前最优方法2.47%.     

抗心律失常药物筛选研究进展

抗心律失常药物治疗是心律失常的基础治疗,大规模随机双盲试验表明抗心律失常药物存在总有效率不高,致心律失常副作用和对患者生存率改善作用不佳等问题. 就抗心律失常药物发展历程、存在的问题、研究进展和药物发现的新策略进行综述。     

诺氟沙星与氧氟沙星同时与牛血清白蛋白分子作用的荧光光谱

氧氟沙星(OFX)、诺氟沙星(NOR)皆能使牛血清白蛋白(BSA)的荧光猝灭.当2种药物共存时可进一步使BSA荧光猝灭,借此利用荧光光谱法研究了诺氟沙星、氧氟沙星药物间的相互作用.研究结果表明2种药物间存在相互作用,使药物与蛋白的结合稳定性减小;BSA的荧光猝灭属于静态猝灭,药物与BSA结合位点数n近似为1.依据F(o...