Rational redesign of the 4-chlorobenzoate binding site of 4-chlorobenzoate: coenzyme a ligase for expanded substrate range

Environmental aromatic acids are transformed to chemical energy in bacteria that possess the requisite secondary pathways. Some of these pathways rely on the activation of the aromatic acid by coenzyme A (CoA) thioesterification catalyzed by an aromatic acid: CoA ligase. Adaptation of such pathways to the bioremediation of man-made pollutants such as polychlorinated biphenyl (PCB) and dichlorodiphenyltrichloroethane (DDT) requires that the chlorinated benzoic acid byproduct that is formed be able to be eliminated by further degradation. To take advantage of natural benzoic acid degrading pathways requiring initial ring activation by thioesterification, the pathway aromatic acid:CoA ligase must be an effective catalyst with the chlorinated benzoic acid. This study, which focuses on the 4-chlorobenzoate:CoA ligase (CBL) of the 4-monochlorobiphenyl degrading bacterium Alcaligenes sp. strain ALP83, was carried out to determine if the 4-chlorobenzoate binding site of this enzyme can be transformed by rational design to recognize the chlorobenzoic acids formed in the course of breakdown of other environmental PCB congeners. The fundamental question addressed in this study is whether it is possible to add or subtract space from the substrate-binding pocket of this ligase (to complement the topology of the unnatural aromatic substrate) without causing disruption of the ligase catalytic machinery. Herein, we report the results of a substrate specificity analysis that, when interpreted within the context of the X-ray crystal structures, set the stage for the rational design of the ligase for thioesterification of two PCB-derived chlorobenzoic acids. The ligase was first optimized to catalyze CoA thioesterification of 3,4-dichlorobenzoic acid, a poor substrate, by truncating Ile303, a large hydrophobic residue that packs against the ring meta-C(H) group. The structural basis for the approximately 100-fold enhancement in the rate of 3,4-dichlorobenzoate thioesterification catalyzed by the I303A and I303G CBL mutants was validated by determination of the crystal structure of the 3,4-dichlorobenzoate-bound enzymes. Determinations of the structures of I303 mutant complexes of 3-chlorobenzoate, a very poor substrate, revealed nonproductive binding as a result of the inability of the substrate ring C(4)H group to fill the pocket that binds the C(4)Cl group of the native substrate. The C(4)Cl pocket of the CBL I303A mutant was then reduced in size by strategic amino acid replacement. A 54-fold improvement in catalytic efficiency was observed for the CBL F184W/I303A/V209T triple mutant. The results of this investigation are interpreted as evidence that the plasticity of the ligase catalytic scaffold is sufficient to allow expansion of substrate range by rational design. The combination of structural and kinetic analyses of the constructed mutants proved to be an effective approach to engineering the ligase for novel substrates.     

The platelet-derived growth factor receptor alpha is destabilized by geldanamycins in cancer cells

The heat shock protein HSP90 serves as a chaperone for receptor protein kinases, steroid receptors, and other intracellular signaling molecules. Targeting HSP90 with ansamycin antibiotics disrupts the normal processing of clients of the HSP90 complex. The platelet-derived growth factor receptor alpha (PDGFRalpha) is a tyrosine kinase receptor up-regulated and activated in several malignancies. Here we show that the PDGFRalpha forms a complex with HSP90 and the co-chaperone cdc37 in ovarian, glioblastoma, and lung cancer cells. Treatment of cancer cell lines expressing the PDGFRalpha with the HSP90 inhibitor 17-allylamino-17-demethoxygeldanamycin (17-AAG) promotes degradation of the receptor. Likewise, phospho-Akt, a downstream target, is degraded after treatment with 17-AAG. In contrast, PDGFRalpha expression is not affected by 17-AAG in normal human smooth muscle cells or 3T3 fibroblasts. PDGFRalpha degradation by 17-AAG is inhibited by the proteasome inhibitor MG132. High molecular weight, ubiquitinated forms of the receptor are detected in cells treated with 17-AAG and MG132. Degradation of the receptor is also inhibited by a specific neutralizing antibody to the PDGFRalpha but not by a neutralizing antibody to PDGF or by imatinib mesylate (Gleevec). Ultimately, PDGFRalpha-mediated cell proliferation is inhibited by 17-AAG. These results show that 17-AAG promotes PDGFRalpha degradation selectively in transformed cells. Thus, not only mutated tyrosine kinases but also overexpressed receptors in cancer cells can be targeted by 17-AAG.     

DSA图像中运动伪影的消除方法

由于病人存在着各种运动(如呼吸、肌肉运动、心脏运动、设备噪声),在成像过程中常会造成图像上出现伪影,干扰医生的正常诊断,为消除这种伪影,本文提出一种基于图像配准思想的全自动消除伪影的方法,该方法能够自动消除DSA图像中的大部分运动伪影,使DSA图像得到较好的增强,并为后面的血管分割和三维重建提供便利,是一种快速有效的方法。     

医疗设备维修标准化管理的探讨

本文主要阐述现代医院在医疗设备购置过程中,怎样来进一步增强售后服务意识,事先防范风险。在医疗设备维修过程中,怎样来规范维修合同,制定标准合同,加强售后服务管理。     

Twenty-four novel mutations in Wilson disease patients of predominantly Italian origin

Herein we report the results of mutation analysis of the ATP7B gene in a group of 134 Wilson disease (WD) families (268 chromosomes) prevalently of Italian origin. Using the SSCP and sequencing methods we identified 71 disease-causing mutations. Twenty-four were novel, while 19 more mutations already described, were identified in new populations in this study. A known mutation G591D showed a regional distribution, since it was only detected in 38.5% of the analyzed chromosomes in WD patients originating from Apulia, a region of South Italy. Detection of new mutations in the ATP7B gene increases our capability of molecular analysis that is essential for early diagnosis and treatment of WD.     

Structure-based maximal affinity model predicts small-molecule druggability

Lead generation is a major hurdle in small-molecule drug discovery, with an estimated 60% of projects failing from lack of lead matter or difficulty in optimizing leads for drug-like properties. It would be valuable to identify these less-druggable targets before incurring substantial expenditure and effort. Here we show that a model-based approach using basic biophysical principles yields good prediction of druggability based solely on the crystal structure of the target binding site. We quantitatively estimate the maximal affinity achievable by a drug-like molecule, and we show that these calculated values correlate with drug discovery outcomes. We experimentally test two predictions using high-throughput screening of a diverse compound collection. The collective results highlight the utility of our approach as well as strategies for tackling difficult targets.