Glutamate transporters regulate synaptic concentrations of this neurotransmitter by coupling its flux to that of sodium and other cations. Available crystal structures of an archeal homologue of these transporters, GltPh, resemble an extracellular-facing state, in which the bound substrate is occluded only by a small helical hairpin segment called HP2. However, a pathway to the cytoplasmic side of the membrane is not clearly apparent. We previously modeled an alternate state of a transporter from the neurotransmitter:sodium symporter family, which has an entirely different fold, solely on the presence of inverted-topology structural repeats. In GltPh, we identified two distinct sets of inverted-topology repeats and used these repeats to model an inward-facing conformation of the protein. To test this model, we introduced pairs of cysteines into the neuronal glutamate transporter EAAC1, at positions that are >27 Å apart in the crystal structures of GltPh, but Ϸ10 Å apart in the inward-facing model. Transport by these mutants was activated by pretreatment with the reducing agent dithithreitol. Subsequent treatment with the oxidizing agent copper(II)(1,10-phenantroline) 3 abolished this activation. The inhibition of transport was potentiated under conditions thought to promote the inward-facing conformation of the transporter. By contrast, the inhibition was reduced in the presence of the nontransportable substrate analogue D,L-threo-␤-benzyloxyaspartate, which favors the outward-facing conformation. Other conformation-sensitive accessibility measurements are also accommodated by our inward-facing model. These results suggest that the inclusion of inverted-topology repeats in transporters may provide a general solution to the requirement for two symmetry-related states in a single protein.alternating access ͉ conformationally sensitive cross-linking ͉ homology modeling ͉ neurotransmitter ͉ secondary transport

SUMMARY Axon regeneration in the central nervous system (CNS) requires reactivating injured neurons’ intrinsic growth state and enabling growth in an inhibitory environment. Using an inbred mouse neuronal phenotypic screen, we find that CAST/Ei mouse adult dorsal root ganglion neurons extend axons more on CNS myelin than the other eight strains tested, especially when pre-injured. Injury-primed CAST/Ei neurons also regenerate markedly in the spinal cord and optic nerve more than those from C57BL/6 mice and show greater spouting following ischemic stroke. Heritability estimates indicate that extended growth in CAST/Ei neurons on myelin is genetically determined, and two whole-genome expression screens yield the Activin transcript Inhba as most correlated with this ability. Inhibition of Activin signaling in CAST/Ei mice diminishes their CNS regenerative capacity whereas its activation in C57BL/6 animals boosts regeneration. This screen demonstrates that mammalian CNS regeneration can occur and reveals a molecular pathway that contributes to this ability.

This comprehensive assessment reveals advantages and limitations of using gliomaspheres to model GBM biology, and provides a novel strategy for selecting genes for future study.

High throughput screening (HTS) data is often noisy, containing both false positives and negatives. Thus, careful triaging and prioritization of the primary hit list can save time and money by identifying potential false positives before incurring the expense of followup. Of particular concern are cell-based reporter gene assays (RGAs) where the number of hits may be prohibitively high to be scrutinized manually for weeding out erroneous data. Based on statistical models built from chemical structures of 650 000 compounds tested in RGAs, we created "frequent hitter" models that make it possible to prioritize potential false positives. Furthermore, we followed up the frequent hitter evaluation with chemical structure based in silico target predictions to hypothesize a mechanism for the observed "off target" response. It was observed that the predicted cellular targets for the frequent hitters were known to be associated with undesirable effects such as cytotoxicity. More specifically, the most frequently predicted targets relate to apoptosis and cell differentiation, including kinases, topoisomerases, and protein phosphatases. The mechanism-based frequent hitter hypothesis was tested using 160 additional druglike compounds predicted by the model to be nonspecific actives in RGAs. This validation was successful (showing a 50% hit rate compared to a normal hit rate as low as 2%), and it demonstrates the power of computational models toward understanding complex relations between chemical structure and biological function.

In this work we explore the possibilities of using fragment-based screening data to prioritize compounds from a full HTS library, a method we call virtual fragment linking (VFL). The ability of VFL to identify compounds of nanomolar potency based on micromolar fragment binding data was tested on 75 target classes from the WOMBAT database and succeeded in 57 cases. Further, the method was demonstrated for seven drug targets from in-house screening programs that performed both FBS of 8800 fragments and screens of the full library. VFL captured between 28% and 67% of the hits (IC 50 < 10microM) in the top 5% of the ranked library for four of the targets (enrichment between 5-fold and 13-fold). Our findings lead us to conclude that proper coverage of chemical space by the fragment library is crucial for the VFL methodology to be successful in prioritizing HTS libraries from fragment-based screening data.

A methodology is introduced to assign energy-based scores to two-dimensional (2D) structural features based on three-dimensional (3D) ligand-target interaction information and utilize interaction-annotated features in virtual screening. Database molecules containing such fragments are assigned cumulative scores that serve as a measure of similarity to active reference compounds. The Interaction Annotated Structural Features (IASF) method is applied to mine five high-throughput screening (HTS) data sets and often identifies more hits than conventional fragment-based similarity searching or ligand-protein docking.

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