Analysis of zinc binding sites in protein crystal structures

The geometrical properties of zinc binding sites in a dataset of high quality protein crystal structures deposited in the Protein Data Bank have been examined to identify important differences between zinc sites that are directly involved in catalysis and those that play a structural role. Coordination angles in the zinc primary coordination sphere are compared with ideal values for each coordination geometry, and zinc coordination distances are compared with those in small zinc complexes from the Cambridge Structural Database as a guide of expected trends. We find that distances and angles in the primary coordination sphere are in general close to the expected (or ideal) values. Deviations occur primarily for oxygen coordinating atoms and are found to be mainly due to H-bonding of the oxygen coordinating ligand to protein residues, bidentate binding arrangements, and multi-zinc sites. We find that H-bonding of oxygen containing residues (or water) to zinc bound histidines is almost universal in our dataset and defines the elec-His-Zn motif. Analysis of the stereochemistry shows that carboxyl elec-His-Zn motifs are geometrically rigid, while water elec-His-Zn motifs show the most geometrical variation. As catalytic motifs have a higher proportion of carboxyl elec atoms than structural motifs, they provide a more rigid framework for zinc binding. This is understood biologically, as a small distortion in the zinc position in an enzyme can have serious consequences on the enzymatic reaction. We also analyze the sequence pattern of the zinc ligands and residues that provide elecs, and identify conserved hydrophobic residues in the endopeptidases that also appear to contribute to stabilizing the catalytic zinc site. A zinc binding template in protein crystal structures is derived from these observations.     

肿瘤坏死因子家族新成员——TRAIL

肿瘤坏死因子相关的凋亡诱导配体(TRAIL)或称凋亡素2配体(Apo2 ligand, Apo-2L), 是TNF家族的新成员.它是从表达序列标签库(expressed sequenced tag, EST)中寻找TNF的同源分子时发现的.TRAIL是一种分子质量为32.5 ku的Ⅱ型跨膜糖蛋白, 活性形式呈同源三聚体.TRAIL和可溶性的TRAIL强烈诱导肿瘤细胞株凋亡.新近发现的TRAIL受体DR4和DR5及TRID说明了TRAIL与TNF和Fas/Apo-1配体的作用途径是不同的.随着对TRAIL的受体及作用机理研究的深入, TRAIL很可能成为新一代抗肿瘤制剂.     

受体介导的基因转移技术

通过受体对DNA-配体复合物的特异识别和内吞, 可以将外源基因导入特定的细胞内进行表达,称为受体介导的基因转移技术. 对该项技术的基本方法、体内外应用研究进展以及发展方向等进行了介绍和综述.     

sTRAIL蛋白原核表达载体的构建、表达及抗肿瘤活性研究

目的:从HL-60细胞中获得了sTrail基因片段,优化蛋白表达条件,并研究其抗肿瘤活性。方法:培养HL-60细胞,提取总RNA,通过RT-PCR扩增sTRAIL蛋白基因片段,并将目的基因克隆至原核表达载体p ET28a上,并电击转化E.coli BL21(DE3),IPTG诱导表达,优化蛋白表达条件,Ni-IDA柱纯化重组蛋白,SDS-PAGE蛋白电泳,胶内酶解质谱鉴定。纯化后的重组蛋白作用HUVEC,He La,Hep-3B,HCT-116,MDA-MB-231,H460细胞检测蛋白生物学作用。结果:DNA测序结果证实成功构建了重组质粒p ET28a-sTrail,SDS-PAGE蛋白电泳,胶内酶解质谱检测显示成功表达sTRAIL蛋白,MTT法和流式细胞术结果显示,sTRAIL蛋白对肿瘤细胞包括He La,HCT-116,MDA-MB-231,H460,Hep-3B细胞有良好的生物活性,对正常的HUVEC细胞无毒性。结论:成功构建可以高效表达sTRAIL蛋白的原核表达载体,优化蛋白的表达和纯化后所得sTRAIL蛋白具有良好的抗肿瘤生物活性,为研究和发展利用sTRAIL蛋白作为临床治疗抗肿瘤药物提供了重要基础。     

Targeted purification development enabled by computational biophysical modeling

Chromatographic and non‐chromatographic purification of biopharmaceuticals depend on the interactions between protein molecules and a solid–liquid interface. These interactions are dominated by the protein–surface properties, which are a function of protein sequence, structure, and dynamics. In addition, protein–surface properties are critical for in vivo recognition and activation, thus, purification strategies should strive to preserve structural integrity and retain desired pharmacological efficacy. Other factors such as surface diffusion, pore diffusion, and film mass transfer can impact chromatographic separation and resin design. The key factors that impact non‐chromatographic separations (e.g., solubility, ligand affinity, charges and hydrophobic clusters, and molecular dynamics) are readily amenable to computational modeling and can enhance the understanding of protein chromatographic. Previously published studies have used computational methods such as quantitative structure–activity relationship (QSAR) or quantitative structure–property relationship (QSPR) to identify and rank order affinity ligands based on their potential to effectively bind and separate a desired biopharmaceutical from host cell protein (HCP) and other impurities. The challenge in the application of such an approach is to discern key yet subtle differences in ligands and proteins that influence biologics purification. Using a relatively small molecular weight protein (insulin), this research overcame limitations of previous modeling efforts by utilizing atomic level detail for the modeling of protein–ligand interactions, effectively leveraging and extending previous research on drug target discovery. These principles were applied to the purification of different commercially available insulin variants. The ability of these computational models to correlate directionally with empirical observation is demonstrated for several insulin systems over a range of purification challenges including resolution of subtle product variants (amino acid misincorporations). Broader application of this methodology in bioprocess development may enhance and speed the development of a robust purification platform. © 2014 American Institute of Chemical Engineers Biotechnol. Prog., 31:154–164, 2015     

Insights into the role of components of the tumor microenvironment in oral carcinoma call for new therapeutic approaches

The research on oral cancer has focused mainly on the cancer cells, their genetic changes and consequent phenotypic modifications. However, it is increasingly clear that the tumor microenvironment (TME) has been shown to be in a dynamic state of inter-relations with the cancer cells. The TME contains a variety of components including the non-cancerous cells (i.e., immune cells, resident fibroblasts and angiogenic vascular cells) and the ECM milieu [including fibers (mainly collagen and fibronectin) and soluble factors (i.e., enzymes, growth factors, cytokines and chemokines)]. Thus, it is currently assumed that TME is considered a part of the cancerous tissue and the functionality of its key components constitutes the setting on which the hallmarks of the cancer cells can evolve. Therefore, in terms of controlling a malignancy, one should control the growth, invasion and spread of the cancer cells through modifications in the TME components. This mini review focuses on the TME as a diagnostic approach and reports the recent insights into the role of different TME key components [such as carcinoma-associated fibroblasts (CAFs) and inflammation (CAI) cells, angiogenesis, stromal matrix molecules and proteases] in the molecular biology of oral carcinoma. Furthermore, the impact of TME components on clinical outcomes and the concomitant need for development of new therapeutic approaches will be discussed.