Structures, Substrates, and Regulators of Mammalian Sirtuins – Opportunities and Challenges for Drug Development

Sirtuins are NAD+-dependent protein deacetylases regulating metabolism, stress responses, and aging processes. Mammalia have seven Sirtuin isoforms, Sirt1–7, which differ in their substrate specificities and subcellular localizations. The physiological functions of Sirtuins make them interesting therapeutic targets, which has stimulated extensive efforts on development of small molecule Sirtuin modulators. Yet, most Sirtuin inhibitors show limited potency and/or isoform specificity, and the mechanism of Sirtuin activation by small molecules remains obscure. Accumulating information on Sirtuin substrates, structures, and regulation mechanisms offer new opportunities for the challenging task to develop potent and specific small molecule modulators for mammalian Sirtuins for in vivo studies and therapeutic applications. We therefore recapitulate advances in structural and mechanistic studies on substrate recognition and deacetylation by Sirtuins, and in the characterization of compounds and molecular mechanisms regulating their activity. We then discuss challenges and opportunities from these findings for Sirtuin-targeted drug development efforts

PACE Solver Description: The KaPoCE Exact Cluster Editing Algorithm

The cluster editing problem is to transform an input graph into a cluster graph by performing a minimum number of edge editing operations. A cluster graph is a graph where each connected component is a clique. An edit operation can be either adding a new edge or removing an existing edge. In this write-up we outline the core techniques used in the exact cluster editing algorithm of the KaPoCE framework (contains also a heuristic solver), submitted to the exact track of the 2021 PACE challenge

PACE Solver Description: KaPoCE: A Heuristic Cluster Editing Algorithm

The cluster editing problem is to transform an input graph into a cluster graph by performing a minimum number of edge editing operations. A cluster graph is a graph where each connected component is a clique. An edit operation can be either adding a new edge or removing an existing edge. In this write-up we outline the core techniques used in the heuristic cluster editing algorithm of the Karlsruhe and Potsdam Cluster Editing (KaPoCE) framework, submitted to the heuristic track of the 2021 PACE challenge

PACE solver description: KaPoCE: A heuristic cluster editing algorithm

The cluster editing problem is to transform an input graph into a cluster graph by performing a minimum number of edge editing operations. A cluster graph is a graph where each connected component is a clique. An edit operation can be either adding a new edge or removing an existing edge. In this write-up we outline the core techniques used in the heuristic cluster editing algorithm of the Karlsruhe and Potsdam Cluster Editing (KaPoCE) framework, submitted to the heuristic track of the 2021 PACE challenge

PACE solver description: The KaPoCE exact cluster editing algorithm

The cluster editing problem is to transform an input graph into a cluster graph by performing a minimum number of edge editing operations. A cluster graph is a graph where each connected component is a clique. An edit operation can be either adding a new edge or removing an existing edge. In this write-up we outline the core techniques used in the exact cluster editing algorithm of the KaPoCE framework (contains also a heuristic solver), submitted to the exact track of the 2021 PACE challenge

A Branch-And-Bound Algorithm for Cluster Editing

The cluster editing problem asks to transform a given graph into a disjoint union of cliques by inserting and deleting as few edges as possible. We describe and evaluate an exact branch-and-bound algorithm for cluster editing. For this, we introduce new reduction rules and adapt existing ones. Moreover, we generalize a known packing technique to obtain lower bounds and experimentally show that it contributes significantly to the performance of the solver. Our experiments further evaluate the effectiveness of the different reduction rules and examine the effects of structural properties of the input graph on solver performance. Our solver won the exact track of the 2021 PACE challenge

Lower limb stiffness and maximal sprint speed in 11-16-year-old boys

The purpose of the study was to examine the relationship between vertical stiffness, leg stiffness and maximal sprint speed in a large cohort of 11-16-year-old boys. Three-hundred and thirty-six boys undertook a 30 m sprint test using a floor-level optical measurement system, positioned in the final 15 m section. Measures of speed, step length, step frequency, contact time and flight time were directly measured whilst force, displacement, vertical stiffness and leg stiffness, were modeled from contact and flight times, from the two fastest consecutive steps for each participant over two trials. All force, displacement and stiffness variables were significantly correlated with maximal sprint speed (p 0.7) relationship with sprint speed, while vertical center of mass displacement, absolute vertical stiffness, relative peak force, and maximal leg spring displacement had large (r > 0.5) relationships. Relative vertical stiffness and relative peak force did not significantly change with advancing age (p > 0.05), but together with maximal leg spring displacement accounted for 96% of the variance in maximal speed. It appears that relative vertical stiffness and relative peak force are important determinants of sprint speed in boys aged 11-16 years, but are qualities that may need to be trained due to no apparent increases from natural development. Practitioners may wish to utilize training modalities such as plyometrics and resistance training to enable adaptation to these qualities due to their importance as predictors of speed in youth

Expression capable library for studies of Neisseria gonorrhoeae, version 1.0

Background The sexually transmitted disease, gonorrhea, is a serious health problem in developed as well as in developing countries, for which treatment continues to be a challenge. The recent completion of the genome sequence of the causative agent, Neisseria gonorrhoeae, opens up an entirely new set of approaches for studying this organism and the diseases it causes. Here, we describe the initial phases of the construction of an expression-capable clone set representing the protein-coding ORFs of the gonococcal genome using a recombination-based cloning system. Results The clone set thus far includes 1672 of the 2250 predicted ORFs of the N. gonorrhoeae genome, of which 1393 (83%) are sequence-validated. Included in this set are 48 of the 61 ORFs of the gonococcal genetic island of strain MS11, not present in the sequenced genome of strain FA1090. L-arabinose-inducible glutathione-S-transferase (GST)-fusions were constructed from random clones and each was shown to express a fusion protein of the predicted size following induction, demonstrating the use of the recombination cloning system. PCR amplicons of each ORF used in the cloning reactions were spotted onto glass slides to produce DNA microarrays representing 2035 genes of the gonococcal genome. Pilot experiments indicate that these arrays are suitable for the analysis of global gene expression in gonococci. Conclusion This archived set of Gateway® entry clones will facilitate high-throughput genomic and proteomic studies of gonococcal genes using a variety of expression and analysis systems. In addition, the DNA arrays produced will allow us to generate gene expression profiles of gonococci grown in a wide variety of conditions. Together, the resources produced in this work will facilitate experiments to dissect the molecular mechanisms of gonococcal pathogenesis on a global scale, and ultimately lead to the determination of the functions of unknown genes in the genome