Pitchai Daisy, Manikkam Rajalakshmi, Rajendran Sasikala R, Pitchai Gnanamani
Bioinformatics centre (BIF), PG, Research Department of Biotechnology, Bioinformatics,Holy Cross College(Autonomous), Teppakulam, Tiruchirapalli-620002, Tamilnadu, India.
Bioinformation. 2010 Jul 6;5(2):43-5. doi: 10.6026/9732063000543.
Plants continue to be a major source of medicines, as they have been throughout human history. In the present days, drug discovery from plants involves a multidisciplinary approach combining ethnobotanical, phytochemical and biological techniques to provide us new chemical compounds (lead molecules) for the development of drugs against various pharmacological targets, including cancer, diabetes and its secondary complications. In view of this need in current drug discovery from medicinal plants, here we describe another web database containing the information of pharmacophore analysis of active principles possessing antidiabetic, antimicrobial, anticancerous and antioxidant properties from medicinal plants. The database provides the botanical, taxonomic classification, biochemical as well as pharmacological properties of medicinal plants. Data on antidiabetic, antimicrobial, anti oxidative, anti tumor and anti inflammatory compounds, and their physicochemical properties, SMILES Notation, Lipinski's properties are included in our database. One of the proposed features in the database is the predicted ADMET values and the interaction of bioactive compounds to the target protein. The database alphabetically lists the compound name and also provides tabs separating for anti microbial, antitumor, antidiabetic, and antioxidative compounds.
植物一直是药物的主要来源,贯穿人类历史至今。如今,从植物中发现药物涉及多学科方法,结合民族植物学、植物化学和生物技术,为我们提供新的化合物(先导分子),用于开发针对各种药理靶点的药物,包括癌症、糖尿病及其并发症。鉴于目前从药用植物中发现药物的这种需求,在此我们描述另一个网络数据库,其中包含来自药用植物的具有抗糖尿病、抗菌、抗癌和抗氧化特性的活性成分的药效团分析信息。该数据库提供了药用植物的植物学、分类学分类、生化以及药理特性。我们的数据库包含有关抗糖尿病、抗菌、抗氧化、抗肿瘤和抗炎化合物的数据,以及它们的物理化学性质、SMILES 符号、Lipinski 性质。该数据库的一个拟议功能是预测的ADMET值以及生物活性化合物与靶蛋白的相互作用。该数据库按字母顺序列出化合物名称,并提供用于分离抗菌、抗肿瘤、抗糖尿病和抗氧化化合物的标签。