Highly Specific, Bi-substrate-Competitive Src Inhibitors from DNA-Templated Macrocycles

Protein kinases are attractive therapeutic targets, but their high sequence and structural conservation complicates the development of specific inhibitors. We recently discovered from a DNA-templated macrocycle library inhibitors with unusually high selectivity among Src-family kinases. Starting from these compounds, we developed and characterized in molecular detail potent macrocyclic inhibitors of Src kinase and its cancer-associated gatekeeper mutant. We solved two co-crystal structures of macrocycles bound to Src kinase. These structures reveal the molecular basis of the combined ATP- and substrate peptide-competitive inhibitory mechanism and the remarkable kinase specificity of the compounds. The most potent compounds inhibit Src activity in cultured mammalian cells. Our work establishes that macrocycles can inhibit protein kinases through a bi-substrate competitive mechanism with high potency and exceptional specificity, reveals the precise molecular basis for their desirable properties, and provides new insights into the development of Src-specific inhibitors with potential therapeutic relevance.Chemistry and Chemical Biolog

Stability Studies for Photovoltaic Integration using Power Hardware-in-the-Loop Experiments

The electrical power network is gradually migrating from a centralized generation approach to a decentralized generation with high shares of renewable energy sources (RES). However, power systems with low shares of synchronous generation and consequently low total system inertia, are vulnerable to power imbalances. Such systems can experience frequency stability problems, such as high frequency excursions and higher rates of change of frequency even under small disturbances. This phenomenon is intensified when the grid under investigation has low or no interconnections (islanded) and thus the challenge for stable operation becomes more significant for the operators. This work focuses on how the frequency stability is affected when a photovoltaic (PV) inverter is integrated into a real non-interconnected distribution grid in Cyprus. In order to capture the realistic interactions of this integration, stability experiments in a hardware-in-the-loop (HIL) environment are performed with the aim to provide insightful results for the grid operator.Comment: The 12th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion (MEDPOWER 2020

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

Background The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Results Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory. Conclusion We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens.Peer reviewe

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

BackgroundThe Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function.ResultsHere, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory.ConclusionWe conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens.</p

A Decentralized, Hybrid Photovoltaic-Solid Oxide Fuel Cell System for Application to a Commercial Building

New energy solutions are needed to decrease the currently high electricity costs from conventional electricity-only central power plants in Cyprus. A promising solution is a decentralized, hybrid photovoltaic-solid oxide fuel cell (PV-SOFC) system. In this study a decentralized, hybrid PV-SOFC system is investigated as a solution for useful energy supply to a commercial building (small hotel). An actual load profile and solar/weather data are fed to the system model to determine the thermoeconomic characteristics of the proposed system. The maximum power outputs for the PV and SOFC subsystems are 70 and 152 kWe, respectively. The average net electrical and total efficiencies for the SOFC subsystem are 0.303 and 0.700, respectively. Maximum net electrical and total efficiencies reach up to 0.375 and 0.756, respectively. The lifecycle cost for the system is 1.24 million USD, with a unit cost of electricity at 0.1057 USD/kWh. In comparison to the conventional case, the unit cost of electricity is about 50% lower, while the reduction in CO2 emissions is about 36%. The proposed system is capable of power and heat generation at a lower cost, owing to the recent progress in both PV and fuel cell technologies, namely longer lifetime and lower specific cost