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

Spinal muscular atrophy type I associated with a novel SMN1 splicing variant that disrupts the expression of the functional transcript

IntroductionSpinal muscular atrophy (SMA) is an autosomal recessive neuromuscular disorder caused by pathogenic variants in the SMN1 gene. The majority of SMA patients harbor a homozygous deletion of SMN1 exon 7 (95%). Heterozygosity for a conventional variant and a deletion is rare (5%) and not easily detected, due to the highly homologous SMN2 gene interference. SMN2 mainly produces a truncated non-functional protein (SMN-d7) instead of the full-length functional (SMN-FL). We hereby report a novel SMN1 splicing variant in an infant with severe SMA.MethodsMLPA was used for SMN1/2 exon dosage determination. Sanger sequencing approaches and long-range PCR were employed to search for an SMN1 variant. Conventional and improved Real-time PCR assays were developed for the qualitative and quantitative SMN1/2 RNA analysis.ResultsThe novel SMN1 splice-site variant c.835-8_835-5delinsG, was identified in compound heterozygosity with SMN1 exons 7/8 deletion. RNA studies revealed complete absence of SMN1 exon 7, thus confirming a disruptive effect of the variant on SMN1 splicing. No expression of the functional SMN1-FL transcript, remarkable expression of the SMN1-d7 and increased levels of the SMN2-FL/SMN2-d7 transcripts were observed.DiscussionWe verified the occurrence of a non-deletion SMN1 variant and supported its pathogenicity, thus expanding the SMN1 variants spectrum. We discuss the updated SMA genetic findings in the Cypriot population, highlighting an increased percentage of intragenic variants compared to other populations

Annotation of gene product function from high-throughput studies using the Gene Ontology.

High-throughput studies constitute an essential and valued source of information for researchers. However, high-throughput experimental workflows are often complex, with multiple data sets that may contain large numbers of false positives. The representation of high-throughput data in the Gene Ontology (GO) therefore presents a challenging annotation problem, when the overarching goal of GO curation is to provide the most precise view of a gene's role in biology. To address this, representatives from annotation teams within the GO Consortium reviewed high-throughput data annotation practices. We present an annotation framework for high-throughput studies that will facilitate good standards in GO curation and, through the use of new high-throughput evidence codes, increase the visibility of these annotations to the research community