The AutoDock suite at 30

The AutoDock suite provides a comprehensive toolset for computational ligand docking and drug design and development. The suite builds on 30 years of methods development, including empirical free energy force fields, docking engines, methods for site prediction, and interactive tools for visualization and analysis. Specialized tools are available for challenging systems, including covalent inhibitors, peptides, compounds with macrocycles, systems where ordered hydration plays a key role, and systems with substantial receptor flexibility. All methods in the AutoDock suite are freely available for use and reuse, which has engendered the continued growth of a diverse community of primary users and third‐party developers.     

雏鸡源致病性粪肠球菌的分离鉴定及其耐药性分析

[背景]粪肠球菌(Enterococcus faecalis)是人和动物肠道正常菌群之一,也是一种条件性致病菌.近年来,粪肠球菌引起人和动物感染的报道越来越多.[目的]探明引起某养鸡场雏鸡发病死亡的病原及其致病性和有效治疗药物.[方法]结合临床症状和病理剖检,开展病原菌分离、生理生化特性检测和16S rRNA基因序列分...     

秀丽隐杆线虫（Caenorhabditis elegans）在药物筛选中的应用

基于靶点的体外药物筛选操作相对简单,成本较低,但是由于药物在体内的作用并不仅仅取决于其与靶点的作用程度,吸收、分布、代谢、排泄特征和毒性均会对早期先导物能否进入临床使用产生极大的影响,因此,药物的体内筛选受到重视。本文重点综述了秀丽隐杆线虫（C.elegans）在抗衰老、抗感染药物筛选中的应用情况。秀丽隐杆线虫结构简单、易于培养和可实现高通量筛选,在未来的药物筛选中必将发挥更重要的作用。     

Discovery of C-(1-aryl-cyclohexyl)-methylamines as selective,orally available inhibitors of dipeptidyl peptidase IV

The successful launches of dipeptidyl peptidase IV (DPP IV) inhibitors as oral anti-diabetics warrant and spur the further quest for additional chemical entities in this promising class of therapeutics. Numerous pharmaceutical companies have pursued their proprietary candidates towards the clinic, resulting in a large body of published chemical structures associated with DPP IV. Herein, we report the discovery of a novel chemotype for DPP IV inhibition based on the C-(1-aryl-cyclohexyl)-methylamine scaffold and its optimization to compounds which selectively inhibit DPP IV at low-nM potency and exhibit an excellent oral pharmacokinetic profile in the rat.     

用于筛选抑制丙型肝炎病毒内部核糖体进入位点活性药物的整合型细胞药物筛选模型的构建和评价

目的：构建一个能用于筛选抑制丙型肝炎病毒内部核糖体进入位点（HCV—IRES）活性药物的整合型细胞药筛模型。方法：构建携带HCV 5＇-UTR调控报告基因分泌型碱性磷酸酶（SEAP）基因的质粒pHCV5’-SEAP和用作筛选标记的pNeo^R,线性化后共转染于Huh-7细胞中,经G418筛选后得到抗性细胞克隆,进行SEAP定量检测筛选后,得到能用于筛选抑制HCV-IRES活性药物的整合型细胞药筛模型;连续培养24代,用MTT法测细胞相对活力评价该药筛模型的生长稳定性,用SEAP定量检测法评价该药筛模型的SEAP表达稳定性,用反义寡聚核苷酸抑制试验评价模型的药筛灵敏度。结果：G418筛选后得到26个抗性细胞克隆;对其中5个抗性细胞克隆进行SEAP定量检测筛选后,得到3个能表达SEAP的阳性细胞克隆;连续培养24代过程中,该药筛模型的生长稳定性大干80％,SEAP表达稳定性达95％。结论：构建的细胞模型具有良好的稳定性和药筛灵敏度,符合作为药物筛选模型的要求。     

Prediction of location of active sites in biologically active peptides

In a previous paper we demonstrated that the short-range compact regions in atrial natriuretic factor (-hANF) predicted by the average distance map (ADM) correspond to its active sites [Kikuchi,J. Protein Chem.11, 579–581 (1992)]. In the present paper we apply the same method to other bioactive peptides and peptidic enzyme inhibitors. We again observe that active sites in each peptide are contained in short-range compact regions predicted by the ADM for the peptide. This demonstrates that the ADM method predicts the possible location of active sites in biologically active peptides in general. The possibility of practical application of the present method to rational drug design is also discussed.