Dataset Information

Concise machinery for monitoring ubiquitination activities using novel artificial RING fingers.

ABSTRACT: Protein ubiquitination is involved in many cellular processes, such as protein degradation, DNA repair, and signal transduction pathways. Ubiquitin-conjugating (E2) enzymes of the ubiquitination pathway are associated with various cancers, such as leukemia, lung cancer, and gastric cancer. However, to date, detection of E2 activities is not practicable for capturing the pathological conditions of cancers due to complications related to the enzymatic cascade reaction. To overcome this hurdle, we have recently investigated a novel strategy for measuring E2 activities. Artificial RING fingers (ARFs) were developed to conveniently detect E2 activities during the ubiquitination reaction. ARFs were created by grafting the active sites of ubiquitin-ligating (E3) enzymes onto amino acid sequences with 38 residues. The grafting design downsized E3s to small molecules (ARFs). Such an ARF is a multifunctional molecule that possesses specific E2-binding capabilities and ubiquitinates itself without a substrate. In this review, we discuss the major findings from recent investigations on a new molecular design for ARFs and their simplified detection system for E2 activities. The use of the ARF allowed us to monitor E2 activities using acute promyelocytic leukemia (APL)-derived cells following treatment with the anticancer drug bortezomib. The molecular design of ARFs is extremely simple and convenient, and thus, may be a powerful tool for protein engineering. The ARF methodology may reveal a new screening method of E2s that will contribute to diagnostic techniques for cancers.

SUBMITTER: Miyamoto K

PROVIDER: S-EPMC6153401 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Concise machinery for monitoring ubiquitination activities using novel artificial RING fingers.

Miyamoto Kazuhide K Saito Kazuki K

Protein science : a publication of the Protein Society 20180503 8

Protein ubiquitination is involved in many cellular processes, such as protein degradation, DNA repair, and signal transduction pathways. Ubiquitin-conjugating (E2) enzymes of the ubiquitination pathway are associated with various cancers, such as leukemia, lung cancer, and gastric cancer. However, to date, detection of E2 activities is not practicable for capturing the pathological conditions of cancers due to complications related to the enzymatic cascade reaction. To overcome this hurdle, we ...[more]

PMID: 29663561

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Project description:BackgroundThe human hand plays a crucial role in accomplishing activities of daily living. The contribution of each finger in the human hand is remarkably unique in establishing object stabilization. According to the mechanical advantage hypothesis, the little finger tends to exert a greater normal force than the ring finger during a supination moment production task to stabilize the object. Similarly, during pronation, the index finger produces more normal force when compared with the middle finger. Hence, the central nervous system employs the peripheral fingers for torque generation to establish the equilibrium as they have a mechanical advantage of longer moment arms for normal force. In our study, we tested whether the mechanical advantage hypothesis is supported in a task in which the contribution of thumb was artificially reduced. We also computed the safety margin of the individual fingers and thumb.MethodologyFifteen participants used five-finger prismatic precision grip to hold a custom-built handle with a vertical railing on the thumb side. A slider platform was placed on the railing such that the thumb sensor could move either up or down. There were two experimental conditions. In the "Fixed" condition, the slider was mechanically fixed, and hence the thumb sensor could not move. In the "Free" condition, the slider platform on which the thumb sensor was placed could freely move. In both conditions, the instruction was to grasp and hold the handle (and the platform) in static equilibrium. We recorded tangential and normal forces of all the fingers.ResultsThe distribution of fingertip forces and moments changed depending on whether the thumb platform was movable (or not). In the free condition, the drop in the tangential force of thumb was counteracted by an increase in the normal force of the ring and little finger. Critically, the normal forces of the ring and little finger were statistically equivalent. The safety margin of the index and middle finger did not show a significant drop in the free condition when compared to fixed condition.ConclusionWe conclude that our results does not support the mechanical advantage hypothesis at least for the specific mechanical task considered in our study. In the free condition, the normal force of little finger was comparable to the normal force of the ring finger. Also, the safety margin of the thumb and ring finger increased to prevent slipping of the thumb platform and to maintain the handle in static equilibrium during the free condition. However, the rise in the safety margin of the ring finger was not compensated by a drop in the safety margin of the index and middle finger.

Project description:PurposeTo develop an artificial intelligence (AI) dashboard for monitoring glaucomatous functional loss.DesignRetrospective, cross-sectional, longitudinal cohort study.ParticipantsOf 31 591 visual fields (VFs) on 8077 subjects, 13 231 VFs from the most recent visit of each patient were included to develop the AI dashboard. Longitudinal VFs from 287 eyes with glaucoma were used to validate the models.MethodWe entered VF data from the most recent visit of glaucomatous and nonglaucomatous patients into a "pipeline" that included principal component analysis (PCA), manifold learning, and unsupervised clustering to identify eyes with similar global, hemifield, and local patterns of VF loss. We visualized the results on a map, which we refer to as an "AI-enabled glaucoma dashboard." We used density-based clustering and the VF decomposition method called "archetypal analysis" to annotate the dashboard. Finally, we used 2 separate benchmark datasets-one representing "likely nonprogression" and the other representing "likely progression"-to validate the dashboard and assess its ability to portray functional change over time in glaucoma.Main outcome measuresThe severity and extent of functional loss and characteristic patterns of VF loss in patients with glaucoma.ResultsAfter building the dashboard, we identified 32 nonoverlapping clusters. Each cluster on the dashboard corresponded to a particular global functional severity, an extent of VF loss into different hemifields, and characteristic local patterns of VF loss. By using 2 independent benchmark datasets and a definition of stability as trajectories not passing through over 2 clusters in a left or downward direction, the specificity for detecting "likely nonprogression" was 94% and the sensitivity for detecting "likely progression" was 77%.ConclusionsThe AI-enabled glaucoma dashboard, developed using a large VF dataset containing a broad spectrum of visual deficit types, has the potential to provide clinicians with a user-friendly tool for determination of the severity of glaucomatous vision deficit, the spatial extent of the damage, and a means for monitoring the disease progression.

Dataset Information

Concise machinery for monitoring ubiquitination activities using novel artificial RING fingers.

Publications

Concise machinery for monitoring ubiquitination activities using novel artificial RING fingers.

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