Genome-wide screen for genes involved in Caenorhabditis elegans developmentally timed sleep

In Caenorhabditis elegans, Notch signaling regulates developmentally timed sleep during the transition from L4 larval stage to adulthood (L4/A) . To identify core sleep pathways and to find genes acting downstream of Notch signaling, we undertook the first genome-wide, classical genetic screen focused on C. elegans developmentally timed sleep. To increase screen efficiency, we first looked for mutations that suppressed inappropriate anachronistic sleep in adult hsp::osm-11 animals overexpressing the Notch coligand OSM-11 after heat shock. We retained suppressor lines that also had defects in L4/A developmentally timed sleep, without heat shock overexpression of the Notch coligand. Sixteen suppressor lines with defects in developmentally timed sleep were identified. One line carried a new allele of goa-1; loss of GOA-1 Gαo decreased C. elegans sleep. Another line carried a new allele of gpb-2, encoding a Gβ5 protein; Gβ5 proteins have not been previously implicated in sleep. In other scenarios, Gβ5 GPB-2 acts with regulators of G protein signaling (RGS proteins) EAT-16 and EGL-10 to terminate either EGL-30 Gαq signaling or GOA-1 Gαo signaling, respectively. We found that loss of Gβ5 GPB-2 or RGS EAT-16 decreased L4/A sleep. By contrast, EGL-10 loss had no impact. Instead, loss of RGS-1 and RGS-2 increased sleep. Combined, our results suggest that, in the context of L4/A sleep, GPB-2 predominantly acts with EAT-16 RGS to inhibit EGL-30 Gαq signaling. These results confirm the importance of G protein signaling in sleep and demonstrate that these core sleep pathways function genetically downstream of the Notch signaling events promoting sleep

Generalized Points-to Graphs: A New Abstraction of Memory in the Presence of Pointers

Flow- and context-sensitive points-to analysis is difficult to scale; for top-down approaches, the problem centers on repeated analysis of the same procedure; for bottom-up approaches, the abstractions used to represent procedure summaries have not scaled while preserving precision. We propose a novel abstraction called the Generalized Points-to Graph (GPG) which views points-to relations as memory updates and generalizes them using the counts of indirection levels leaving the unknown pointees implicit. This allows us to construct GPGs as compact representations of bottom-up procedure summaries in terms of memory updates and control flow between them. Their compactness is ensured by the following optimizations: strength reduction reduces the indirection levels, redundancy elimination removes redundant memory updates and minimizes control flow (without over-approximating data dependence between memory updates), and call inlining enhances the opportunities of these optimizations. We devise novel operations and data flow analyses for these optimizations. Our quest for scalability of points-to analysis leads to the following insight: The real killer of scalability in program analysis is not the amount of data but the amount of control flow that it may be subjected to in search of precision. The effectiveness of GPGs lies in the fact that they discard as much control flow as possible without losing precision (i.e., by preserving data dependence without over-approximation). This is the reason why the GPGs are very small even for main procedures that contain the effect of the entire program. This allows our implementation to scale to 158kLoC for C programs

Structure based inhibitor design targeting glycogen phosphorylase b. Virtual screening, synthesis, biochemical and biological assessment of novel N-acyl-β-d-glucopyranosylamines

Glycogen phosphorylase (GP) is a validated target for the development of new type 2 diabetes treatments. Exploiting the Zinc docking database, we report the in silico screening of 1888 β- D-glucopyranose-NH-CO-R putative GP inhibitors differing only in their R groups. CombiGlide and GOLD docking programs with different scoring functions were employed with the best performing methods combined in a “consensus scoring” approach to ranking of ligand binding affinities for the active site. Six selected candidates from the screening were then synthesized and their inhibitory potency was assessed both in vitro and ex vivo. Their inhibition constants’ values, in vitro, ranged from 5 to 377 µM while two of them were effective at causing inactivation of GP in rat hepatocytes at low µM concentrations. The crystal structures of GP in complex with the inhibitors were defined and provided the structural basis for their inhibitory potency and data for further structure based design of more potent inhibitors

An integrated native mass spectrometry and top-down proteomics method that connects sequence to structure and function of macromolecular complexes.

Mass spectrometry (MS) has become a crucial technique for the analysis of protein complexes. Native MS has traditionally examined protein subunit arrangements, while proteomics MS has focused on sequence identification. These two techniques are usually performed separately without taking advantage of the synergies between them. Here we describe the development of an integrated native MS and top-down proteomics method using Fourier-transform ion cyclotron resonance (FTICR) to analyse macromolecular protein complexes in a single experiment. We address previous concerns of employing FTICR MS to measure large macromolecular complexes by demonstrating the detection of complexes up to 1.8 MDa, and we demonstrate the efficacy of this technique for direct acquirement of sequence to higher-order structural information with several large complexes. We then summarize the unique functionalities of different activation/dissociation techniques. The platform expands the ability of MS to integrate proteomics and structural biology to provide insights into protein structure, function and regulation