计算机辅助药物设计在药物合成中的应用

计算机辅助药物设计方法(CADD)是药物分子设计的基础。从20世纪60年代构效关系方法(QSAR)提出以后,经过40多年的努力和探索,CADD方法已经发展成为一门完善和新兴的研究领域。计算机辅助药物设计是应用量子力学、分子动力学、构效关系等基础理论数据研究药物对酶、受体等作用的药效模型,从而达到药物设计之目的。计算机辅助药物设计方法(CADD)大体可以分为三类:基于小分子的药物分子设计方法;基于受体结构的药物分子设计方法;计算组合方法。计算机辅助药物设计是研究与开发新药的一种崭新技术,它大大加快了新药设计的速度,节省了创制新药工作的人力和物力,使药物学家能够以理论作指导,有目的地开发新药。     

计算机自动结构评价及其在吡酮酸类抗菌药物中的应用

在用经验筛选法寻找新药越来越困难的情况下,对有机分子生物活性的预测和评价已成为药物化学家所关心的中心问题之一。由于许多新仪器和新技术的应用,尤其是电子计算机的广泛应用,为合理设计生物活性分子开辟了广阔前景。上世纪开始已陆续出现了几种方法,其中应用较广泛的有定量构效关系(QSAR),模式识别自动数据分析(ADAPT),计算机自动结构评价(CASE),模式识别法(PR),判别分析(DA)等,这些方法各有其优缺点,其中在(QSAR)和(PR)法中,最主要的困难是选择有相关性的参数,这些参数的选择多少带有一定的主观因素,而参数的应用是否有效取决于对某些因素的正确判断和分析,这些因素在分子作用机制中起重要作用。要找到理想的参数,并使其在所有被考察的分子中普遍存在并容易计算,往往是难以实现的。另外一些方法,相对说来输入数据多,引起偏差大。为避免这些困难,尽可能的减少偏     

欧洲药物化学——策略、靶标和在研药物

2005年6月欧洲药物化学联会在奥地利维也纳召开。大会报告涵盖药物化学的各方面,如现代药物合成方法、针对特异靶标的药物研究方法、计算机辅助(insilico supported)分析和相关生物数据的处理。计算机辅助分析方面的内容包括:计算机辅助分子设计和虚拟筛选;蛋白质结构相似群集(     

女贞子的潜在作用靶标虚拟筛选

目的预测女贞子的潜在作用靶标,并为研究二至丸的分子机制提供线索。方法应用计算机辅助药物设计(CADD)方法采用多种软件协同联合,对潜在的作用靶点进行虚拟预测,并结合文献报道进行分析。结果预测的潜在作用靶标部分与齐墩果酸已有报道的药理作用一致,且与二至丸临床应用相关。结论为探讨二至丸的分子机制提供线索,为中药的治病机制研究提供参考。     

高内涵药物筛选的信息整合

高内涵药物筛选(HCS)结合自动显微成像技术与图像分析,使得基于细胞活性的化合物表型检测成为可能,它在预测药物毒性与治疗效果方面的巨大潜力也尚未开发。Feng等正在寻找运用化学结构信息和计算机靶点预测进行HCS数据整合的方法。首先,作者通过细胞增殖试验检测36种胞核细胞学     

药物清除率的定量构动关系研究

目的　利用量子化学和神经网络方法,建立药物分子结构参数与药物清除率之间的关联模型,以预测药物的清除率。方法　计算了已知清除率的100种药物的18个结构参数,并对其进行了主成分分析,获得3个独立结构参数,分别以3个结构参数和18个结构参数作为神经网络的输入,进行了神经网络的建模和预测。结果　采用3个结构参数作为输入参数的神经网络的预测能力明显优于采用18个结构参数的预测能力。结论　所建预测药物清除率的神经网络模型可行,建模时进行药物分子结构参数选择非常必要。     

运用自组织人工神经网络研究弱效安定药苯并二氮杂(艹卓)噁唑烷衍生物构效关系

本文运用T.Kohonen自组织人工神经网络,研究了弱效安定药苯并二氮杂(艹卓)噁唑烷衍生物构效关系,建立了该种药物构效分析的计算机智能专家系统。本研究中,预测成功率为100％。结果表明,该方法性能良好,可望成为药物构效关系分析的有效的辅助手段。     

基于配体-受体理论的计算机辅助药物分子设计方法及应用

药物设计包括药物分子设计和药物合成设计,它是新药研究的中心环节。药物分子设计是人工预建可与机体重要功能分子(蛋白质、核酸、酶、离子通道等)发生作用的化学物质的过程。近年来,生命科学和计算机科学的进展,使药物设计趋于定向化和合理化。1计算机辅助药物分子设计药物分子设计是依据生物化学、酶学、分子生物学及遗传学等生命科学的研究成果,针对这些基础研究中所揭示的药物作用靶位,再参考其内源性配体或天然底物的化学结构特征设计合理的药物分子〔1〕。基于配体与受体间相互作用原理的不断完善,出现了开发新药的新方法——计算机辅…     

药物毒理学的研究进展

近年来,国内药物毒理学发展迅速,在研究思路和观念、技术和手段、策略和方法上发生了巨大转变,其主要表现为;研究过程和实验操作逐步走向规范化、标准化;逐步采用体外筛选评价模型代替整体动物实验;在药物开发、申报、临床监测的各个环节药物毒理学发挥着主动指导作用;随着现代生物医药技术的发展,特别是基因组学、蛋白质组学和代谢组学等的出现为药物毒理学的发展赋予了新的契机,使之经历了研究思路、方法、技术和理念的巨大转变。药物毒理学是根据药物的理化特性,运用毒理学的原理和方法,对其进行全面系统的安全性评价并阐明其毒性作用机制,以便降低药物对人类健康的危害。毒理学是一门研究外源因素(化学、物理、生物因素)对生物系统的有害作用的应用学科。是一门研究化学物质对生物体的毒性反应、严重程度、发生频率和毒性作用机制的科学,也是对毒性作用进行定性和定量评价的科学。是预测对人体和生态环境的危害,为确定安全限值和采取防治措施提供科学依据的一门学科。然而药物毒理学是研究药物毒性的作用机制,并对药物进行全面系统的安全性评价的一门学科,在指导临床合理用药,降低药物不良反应及减少因药物毒性而导致的新药开发失败等方面起到了至关重要的作用。因此药物毒理成为现阶段我国研发人员所要攻克的重要问题。     

抗真菌药物的创新设计研究

运用计算机辅助药物设计技术和分子生物学技术,建立了一套集分子设计、化学合成和分子筛选三大系统为一体的抗真菌药创新设计体系.其工作原理是:通过药效构象搜寻、3D-QSAR研究,建立了抗真菌药物与受体作用模型,预测设计高活性化合物;另一方面,根据抗真菌药靶酶--羊毛甾醇14α-去甲基化酶的已知序列,采用同源蛋白模建技术构建其三维结构,再通过药物-靶酶对接研究,确定活性位点,设计与活性位点最佳匹配的活性化合物;然后针对设计的化合物类型,研究建立一套科学的合成方法,完成化合物的合成;最后以靶酶为模型,建立一套快速准确的分子筛选方法,用筛选结果指导进一步的设计与合成,直至得到最佳的新化学单体(NCE).将该体系用于抗真菌药物设计,获得了一个广谱、高效、低毒的抗真菌新药--艾迪康唑.     

Limitations of urinary mutagen assays for monitoring occupational exposure to antineoplastic drugs

The sensitivity of the Salmonella reversion test of Ames as a screen for accidental absorption of 17 antineoplastic agents by drug handlers was evaluated. Dilutions of each drug were added to agar inoculated with each of two Salmonella typhimurium strains (TA98 and TA100); control plates contained no test drug. Colonies were counted after incubation at 36 degrees C for 48 hours. The drugs were tested in the presence of a liver preparation to provide metabolic activation of mutagenicity. Urine samples collected from patients after doses of three mutagenic drugs were extracted and tested with the Ames test. For 11 of the 17 drug solutions, no mutagenic activity was seen, but many of these 11 were toxic to the organisms. The most highly mutagenic drugs were doxorubicin and cisplatin, with mechlorethamine, carmustine, dacarbazine, and cyclophosphamide exhibiting less mutagenic activity. Urine from patients treated with doxorubicin or cyclophosphamide showed mutagenicity, but the results suggested that the quantity of these drugs that would have to be absorbed to produce a definite reaction in urine is unlikely to be achieved by drug handlers who use standard precautions. Because of its lack of sensitivity and the potential effects of environmental and dietary factors on the results, this bacterial mutagenicity test should not be used routinely for detection of accidental absorption of antineoplastic drugs.     

The role of genetic toxicology in drug discovery and optimization

Genetic toxicology data is used as a surrogate for long-term carcinogenicity data during early drug development. The aim of genotoxicity testing is to identify potentially hazardous drug candidates. Results from genetic toxicology tests in combination with acute and subchronic animal data are used as the basis to approve clinical trials of drug candidates. With few exceptions, mutagenic compounds are dropped from development and clastogenic compounds result in unfavorable labeling, require disclosure in clinical trial consent forms, and can impact the marketability of a new drug. Therefore, genetic toxicology testing in drug discovery and optimization serves to quickly identify mutagens and remove them from development. Additionally, clastogenicity can delay drug development by requiring additional testing to determine in vivo relevance of in vitro clastogenic responses. Clastogenicity screening is conducted so any additional testing can be planned and perhaps integrated into other toxicity studies to expedite progression of drugs into the clinic. Commercially available genotoxicity and carcinogenicity predictive software systems used for decision support by ICSAS, FDA/CDER is described along with the strengths and weakness of each system. The FDA has concentrated on using a consensus approach to maximize certainty for positive predictions at the expense of sensitivity. The consensus approach consists of requiring 2 complementary software packages, such as MC4PC and MDL QSAR models, to agree that a compound has a genotoxic or carcinogenic liability. Mutagenicity and clastogenicity screening tests are described along with advantages and disadvantages of each test. Several testing strategies are presented for consideration.     

Prediction of drug toxicity

The use of computer-aided methods to predict the toxicity of drugs is described. These methods can assist in the identification of toxic compounds early in the drug development process. Thus, there is potential for these methods to be combined with combinatorial synthesis and library design. Quantitative structure-activity relationships allow for the prediction of individual endpoints, usually for restricted groups of compounds. Expert systems for toxicity prediction are based on a number of methodologies, each with its own strengths and weaknesses. The relative merit of each individual technique and methodology is described. However, more toxicity data are required, both to produce and to validate expert systems. Potential sources of new data include the use of high-throughput screening and microarrays for toxicology.     

Application of the programmable calculator in reporting emergency toxicology data

The use of a programmable calculator in reporting the results of emergency toxicology analyses by personnel who do not routinely perform such analyses has eliminated the problems previously encountered due to unfamiliarity with a particular test or tests. The program that is used alerts the physician to those drugs that could possibly interfere in the screening tests used for emergency toxicology analyses and, in addition, provides him or her with an updated listing of popular street and recreational drugs and drugs of abuse in this area in the event that one of these is not detectable in the screening procedure.