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- Burnum-Johnson, Kristin E., et al.
(författare)
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New Views of Old Proteins : Clarifying the Enigmatic Proteome
- 2022
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Ingår i: Molecular & Cellular Proteomics. - : Elsevier BV. - 1535-9476 .- 1535-9484. ; 21:7
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Tidskriftsartikel (refereegranskat)abstract
- All human diseases involve proteins, yet our current tools to characterize and quantify them are limited. To better elucidate proteins across space, time, and molecular composition, we provide a >10 years of projection for technologies to meet the challenges that protein biology presents. With a broad perspective, we discuss grand opportunities to transition the science of proteomics into a more propulsive enterprise. Extrapolating recent trends, we describe a next generation of approaches to define, quantify, and visualize the multiple dimensions of the proteome, thereby transforming our understanding and interactions with human disease in the coming decade.
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- Mansouri, Kamel, et al.
(författare)
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CERAPP : Collaborative Estrogen Receptor Activity Prediction Project
- 2016
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Ingår i: Journal of Environmental Health Perspectives. - : Environmental Health Perspectives. - 0091-6765 .- 1552-9924. ; 124:7, s. 1023-1033
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Humans are exposed to thousands of man-made chemicals in the environment. Some chemicals mimic natural endocrine hormones and, thus, have the potential to be endocrine disruptors. Most of these chemicals have never been tested for their ability to interact with the estrogen receptor (ER). Risk assessors need tools to prioritize chemicals for evaluation in costly in vivo tests, for instance, within the U.S. EPA Endocrine Disruptor Screening Program. OBJECTIVES: We describe a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project) and demonstrate the efficacy of using predictive computational models trained on high-throughput screening data to evaluate thousands of chemicals for ER-related activity and prioritize them for further testing. METHODS: CERAPP combined multiple models developed in collaboration with 17 groups in the United States and Europe to predict ER activity of a common set of 32,464 chemical structures. Quantitative structure-activity relationship models and docking approaches were employed, mostly using a common training set of 1,677 chemical structures provided by the U.S. EPA, to build a total of 40 categorical and 8 continuous models for binding, agonist, and antagonist ER activity. All predictions were evaluated on a set of 7,522 chemicals curated from the literature. To overcome the limitations of single models, a consensus was built by weighting models on scores based on their evaluated accuracies. RESULTS: Individual model scores ranged from 0.69 to 0.85, showing high prediction reliabilities. Out of the 32,464 chemicals, the consensus model predicted 4,001 chemicals (12.3%) as high priority actives and 6,742 potential actives (20.8%) to be considered for further testing.CONCLUSION: This project demonstrated the possibility to screen large libraries of chemicals using a consensus of different in silico approaches. This concept will be applied in future projects related to other end points.
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- Slavov, Nikolai, et al.
(författare)
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Calmodulin Transduces Ca2+ Oscillations into Differential Regulation of Its Target Proteins
- 2013
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Ingår i: ACS Chemical Neuroscience. - : American Chemical Society (ACS). - 1948-7193. ; 4:4, s. 601-612
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Tidskriftsartikel (refereegranskat)abstract
- Diverse physiological processes are regulated differentially by Ca2+ oscillations through the common regulatory hub calmodulin. The capacity of calmodulin to combine specificity with promiscuity remains to be resolved. Here we propose a mechanism based on the molecular properties of calmodulin, its two domains with separate Ca2+ binding affinities, and target exchange rates that depend on both target identity and Ca2+ occupancy. The binding dynamics among Ca2+ Mg2+, calmodulin, and its targets were modeled with mass-action differential equations based on experimentally determined protein concentrations and rate constants. The model predicts that the activation of calcineurin and nitric oxide synthase depends nonmonotonically on Ca2+-oscillation frequency. Preferential activation reaches a maximum at a target-specific frequency. Differential activation arises from the accumulation of inactive calmodulin-target intermediate complexes between Ca2+ transients. Their accumulation provides the system with hysteresis and favors activation of some targets at the expense of others. The generality of this result was tested by simulating 60 000 networks with two, four, or eight targets with concentrations and rate constants from experimentally determined ranges. Most networks exhibit differential activation that increases in magnitude with the number of targets. Moreover, differential activation increases with decreasing calmodulin concentration due to competition among targets. The results rationalize calmodulin signaling in terms of the network topology and the molecular properties of calmodulin.
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