Two inhibitors of the cellular uptake of the endocannabinoid anandamide, (R)-N-oleoyl-(1'-hydroxybenzyl)-2'-ethanolamine and (S)-N-oleoyl-(1'-hydroxybenzyl)-2'-ethanolamine (OMDM-1 and OMDM-2, respectively), were recently synthesized, and their in vitro pharmacological activity described. Here we have assessed their activity in two typical pharmacological responses of cannabimimetic compounds. We first examined whether these compounds exert any effect per se on locomotion and pain perception in rats, and/or enhance the effects of anandamide on these two processes. We compared the effects of the novel compounds with those produced by a previously developed selective inhibitor, N-arachidonoyl-(2-methyl-4-hydroxyphenyl)amine (VDM-11). When assayed alone, OMDM-1 and OMDM-2 (1-10 mg/kg, i.p.) did not affect any of the five motor parameters under investigation, although the former compound exhibited a trend for the inhibition of ambulation, fast movements, and speed in rats. OMDM-2 and, to a lesser extent, VDM-11 (5 mg/kg, i.p.) enhanced the motor-inhibitory effects of a noneffective dose (2 mg/kg, i.p.) of anandamide, while OMDM-1 did not. In a typical test of acute analgesia, OMDM-2 and VDM-11 (1-10 mg/kg, i.p.), but not OMDM-1, significantly enhanced the time spent by rats on a "hot plate." However, the same compounds (5 mg/kg, i.p.) did not enhance the analgesic effect of a subeffective dose (2 mg/kg, i.p.) of anandamide, whereas OMDM-1 exerted a strong trend towards potentiation (P=0.06). We next explored the possible use of the two novel compounds in a pathological condition. Thus, we determined if, like other previously developed anandamide reuptake inhibitors, OMDM-1 and OMDM-2 inhibit spasticity in an animal model of multiple sclerosis-the chronic relapsing experimental allergic encephalomyelitis in mice. As previously shown with a higher dose of VDM-11, both novel compounds (5 mg/kg, i.v.) significantly reduced spasticity of the hindlimb in mice with chronic relapsing experimental allergic encephalomyelitis. We suggest that OMDM-1 and, particularly, OMDM-2 are useful pharmacological tools for the study of the (patho)physiological role of the anandamide cellular uptake process, and represent unique templates for the development of new antispastic drugs.

Cysteine is the most intrinsically nucleophilic amino acid in proteins, where its reactivity is tuned to perform diverse biochemical functions. The absence of a consensus sequence that defines functional cysteines in proteins has hindered their discovery and characterization. Here we describe a proteomics method to profile quantitatively the intrinsic reactivity of cysteine residues en masse directly in native biological systems. Hyper-reactivity was a rare feature among cysteines and it was found to specify a wide range of activities, including nucleophilic and reductive catalysis and sites of oxidative modification. Hyper-reactive cysteines were identified in several proteins of uncharacterized function, including a residue conserved across eukaryotic phylogeny that we show is required for yeast viability and is involved in iron-sulphur protein biogenesis. We also demonstrate that quantitative reactivity profiling can form the basis for screening and functional assignment of cysteines in computationally designed proteins, where it discriminated catalytically active from inactive cysteine hydrolase designs.

Enzymes use substrate-binding energy both to promote ground-state association and to stabilize the reaction transition state selectively. The monomeric homing endonuclease I-AniI cleaves with high sequence specificity in the centre of a 20-base-pair (bp) DNA target site, with the amino (N)-terminal domain of the enzyme making extensive binding interactions with the left (-) side of the target site and the similarly structured carboxy (C)-terminal domain interacting with the right (+) side. Here we show that, despite the approximate twofold symmetry of the enzyme-DNA complex, there is almost complete segregation of interactions responsible for substrate binding to the (-) side of the interface and interactions responsible for transition-state stabilization to the (+) side. Although single base-pair substitutions throughout the entire DNA target site reduce catalytic efficiency, mutations in the (-) DNA half-site almost exclusively increase the dissociation constant (K(D)) and the Michaelis constant under single-turnover conditions (K(M)*), and those in the (+) half-site primarily decrease the turnover number (k(cat)*). The reduction of activity produced by mutations on the (-) side, but not mutations on the (+) side, can be suppressed by tethering the substrate to the endonuclease displayed on the surface of yeast. This dramatic asymmetry in the use of enzyme-substrate binding energy for catalysis has direct relevance to the redesign of endonucleases to cleave genomic target sites for gene therapy and other applications. Computationally redesigned enzymes that achieve new specificities on the (-) side do so by modulating K(M)*, whereas redesigns with altered specificities on the (+) side modulate k(cat)*. Our results illustrate how classical enzymology and modern protein design can each inform the other.

Understanding enzyme catalysis through the analysis of natural enzymes is a daunting challenge-their active sites are complex and combine numerous interactions and catalytic forces that are finely coordinated. Study of more rudimentary (wo)man-made enzymes provides a unique opportunity for better understanding of enzymatic catalysis. KE07, a computationally designed Kemp eliminase that employs a glutamate side chain as the catalytic base for the critical proton abstraction step and an apolar binding site to guide substrate binding, was optimized by seven rounds of random mutagenesis and selection, resulting in a >200-fold increase in catalytic efficiency. Here, we describe the directed evolution process in detail and the biophysical and crystallographic studies of the designed KE07 and its evolved variants. The optimization of KE07's activity to give a k(cat)/K(M) value of approximately 2600 s(-1) M(-1) and an approximately 10(6)-fold rate acceleration (k(cat)/k(uncat)) involved the incorporation of up to eight mutations. These mutations led to a marked decrease in the overall thermodynamic stability of the evolved KE07s and in the configurational stability of their active sites. We identified two primary contributions of the mutations to KE07's improved activity: (i) the introduction of new salt bridges to correct a mistake in the original design that placed a lysine for leaving-group protonation without consideration of its "quenching" interactions with the catalytic glutamate, and (ii) the tuning of the environment, the pK(a) of the catalytic base, and its interactions with the substrate through the evolution of a network of hydrogen bonds consisting of several charged residues surrounding the active site.

Microglial activation in multiple sclerosis has been postulated to contribute to long-term neurodegeneration during disease. Fingolimod has been shown to impact on the relapsing remitting phase of disease by modulating autoreactive T-cell egress from lymph organs. In addition, it is brain penetrant and has been shown to exert multiple effects on nervous system cells.

We describe the identification and characterization of novel homing endonucleases using genome database mining to identify putative target sites, followed by high throughput activity screening in a bacterial selection system. We characterized the substrate specificity and kinetics of these endonucleases by monitoring DNA cleavage events with deep sequencing. The endonuclease specificities revealed by these experiments can be partially recapitulated using 3D structure-based computational models. Analysis of these models together with genome sequence data provide insights into how alternative endonuclease specificities were generated during natural evolution.

We present a de novo model-building approach that combines predicted backbone conformations with side-chain fit to density to accurately assign sequence into density maps. This method yielded accurate models for six of nine experimental maps at 3.3- to 4.8-Å resolution and produced a nearly complete model for an unsolved map containing a 660-residue heterodimeric protein. This method should enable rapid and reliable protein structure determination from near-atomic-resolution cryo-electron microscopy (cryo-EM) maps.

Repeat proteins have considerable potential for use as modular binding reagents or biomaterials in biomedical and nanotechnology applications. Here we describe a general computational method for building idealized repeats that integrates available family sequences and structural information with Rosetta de novo protein design calculations. Idealized designs from six different repeat families were generated and experimentally characterized; 80% of the proteins were expressed and soluble and more than 40% were folded and monomeric with high thermal stability. Crystal structures determined for members of three families are within 1Å root-mean-square deviation to the design models. The method provides a general approach for fast and reliable generation of stable modular repeat protein scaffolds.

Antigenic variation in the globular domain of influenza A virus (IAV) hemagglutinin (HA) precludes effective immunity to this major human pathogen. Although the HA stem is highly conserved between influenza virus strains, HA stem-reactive antibodies (StRAbs) were long considered biologically inert. It is now clear, however, that StRAbs reduce viral replication in animal models and protect against pathogenicity and death, supporting the potential of HA stem-based immunogens as drift-resistant vaccines. Optimally designing StRAb-inducing immunogens and understanding StRAb effector functions require thorough comprehension of HA stem structure and antigenicity. Here, we study the biogenesis of HA stem epitopes recognized in cells infected with various drifted IAV H1N1 strains using mouse and human StRAbs. Using a novel immunofluorescence (IF)-based assay, we find that human StRAbs bind monomeric HA in the endoplasmic reticulum (ER) and trimerized HA in the Golgi complex (GC) with similar high avidity, potentially good news for producing effective monomeric HA stem immunogens. Though HA stem epitopes are nestled among several N-linked oligosaccharides, glycosylation is not required for full antigenicity. Rather, as N-linked glycans increase in size during intracellular transport of HA through the GC, StRAb binding becomes temperature-sensitive, binding poorly to HA at 4°C and well at 37°C. A de novo designed, 65-residue protein binds the mature HA stem independently of temperature, consistent with a lack of N-linked oligosaccharide steric hindrance due to its small size. Likewise, StRAbs bind recombinant HA carrying simple N-linked glycans in a temperature-independent manner. Chemical cross-linking experiments show that N-linked oligosaccharides likely influence StRAb binding by direct local effects rather than by globally modifying the conformational flexibility of HA. Our findings indicate that StRAb binding to HA is precarious, raising the possibility that sufficient immune pressure on the HA stem region could select for viral escape mutants with increased steric hindrance from N-linked glycans.

Many cancers overexpress one or more of the six human pro-survival BCL2 family proteins to evade apoptosis. To determine which BCL2 protein or proteins block apoptosis in different cancers, we computationally designed three-helix bundle protein inhibitors specific for each BCL2 pro-survival protein. Following in vitro optimization, each inhibitor binds its target with high picomolar to low nanomolar affinity and at least 300-fold specificity. Expression of the designed inhibitors in human cancer cell lines revealed unique dependencies on BCL2 proteins for survival which could not be inferred from other BCL2 profiling methods. Our results show that designed inhibitors can be generated for each member of a closely-knit protein family to probe the importance of specific protein-protein interactions in complex biological processes.

Synthetic protein switches controlled with user-defined inputs are powerful tools for studying and controlling dynamic cellular processes. To date, these approaches have relied primarily on intermolecular regulation. Here we report a computationally guided framework for engineering intramolecular regulation of protein function. We utilize this framework to develop chemically inducible activator of RAS (CIAR), a single-component RAS rheostat that directly activates endogenous RAS in response to a small molecule. Using CIAR, we show that direct RAS activation elicits markedly different RAS-ERK signaling dynamics from growth factor stimulation, and that these dynamics differ among cell types. We also found that the clinically approved RAF inhibitor vemurafenib potently primes cells to respond to direct wild-type RAS activation. These results demonstrate the utility of CIAR for quantitatively interrogating RAS signaling. Finally, we demonstrate the general utility of our approach in design of intramolecularly regulated protein tools by applying it to the Rho family of guanine nucleotide exchange factors.

We have found that refinement of protein NMR structures using Rosetta with experimental NMR restraints yields more accurate protein NMR structures than those that have been deposited in the PDB using standard refinement protocols. Using 40 pairs of NMR and X-ray crystal structures determined by the Northeast Structural Genomics Consortium, for proteins ranging in size from 5-22 kDa, restrained Rosetta refined structures fit better to the raw experimental data, are in better agreement with their X-ray counterparts, and have better phasing power compared to conventionally determined NMR structures. For 37 proteins for which NMR ensembles were available and which had similar structures in solution and in the crystal, all of the restrained Rosetta refined NMR structures were sufficiently accurate to be used for solving the corresponding X-ray crystal structures by molecular replacement. The protocol for restrained refinement of protein NMR structures was also compared with restrained CS-Rosetta calculations. For proteins smaller than 10 kDa, restrained CS-Rosetta, starting from extended conformations, provides slightly more accurate structures, while for proteins in the size range of 10-25 kDa the less CPU intensive restrained Rosetta refinement protocols provided equally or more accurate structures. The restrained Rosetta protocols described here can improve the accuracy of protein NMR structures and should find broad and general for studies of protein structure and function.

[corrected] Multiple Sclerosis has two clinical phases reflecting distinct but inter-related pathological processes: focal inflammation drives the relapse-remitting stage and neurodegeneration represents the principal substrate of secondary progression. In contrast to the increasing number of effective anti-inflammatory disease modifying treatments for relapse-remitting disease, the absence of therapies for progressive disease represents a major unmet clinical need. This raises the unanswered question of whether elimination of clinical relapses will prevent subsequent progression and if so how early in the disease course should treatment be initiated. Experimental autoimmune encephalomyelitis in the Biozzi ABH mouse recapitulates the clinical and pathological features of multiple sclerosis including relapse-remitting episodes with inflammatory mediated demyelination and progressive disability with neurodegeneration. To address the relationship between inflammation and neurodegeneration we used an auto-immune tolerance strategy to eliminate clinical relapses in EAE in a manner analogous to the clinical effect of disease modifying treatments.

Homing endonucleases (HEs) can be used to induce targeted genome modification to reduce the fitness of pathogen vectors such as the malaria-transmitting Anopheles gambiae and to correct deleterious mutations in genetic diseases. We describe the creation of an extensive set of HE variants with novel DNA cleavage specificities using an integrated experimental and computational approach. Using computational modeling and an improved selection strategy, which optimizes specificity in addition to activity, we engineered an endonuclease to cleave in a gene associated with Anopheles sterility and another to cleave near a mutation that causes pyruvate kinase deficiency. In the course of this work we observed unanticipated context-dependence between bases which will need to be mechanistically understood for reprogramming of specificity to succeed more generally.

The dynamic range of cerebrospinal fluid (CSF) amyloid β (Aβ1-42) measurement does not parallel to cognitive changes in Alzheimer's disease (AD) and cognitively normal (CN) subjects across different studies. Therefore, identifying novel proteins to characterize symptomatic AD samples is important.

Despite efforts for over 25 years, de novo protein design has not succeeded in achieving the TIM-barrel fold. Here we describe the computational design of four-fold symmetrical (β/α)8 barrels guided by geometrical and chemical principles. Experimental characterization of 33 designs revealed the importance of side chain-backbone hydrogen bonds for defining the strand register between repeat units. The X-ray crystal structure of a designed thermostable 184-residue protein is nearly identical to that of the designed TIM-barrel model. PSI-BLAST searches do not identify sequence similarities to known TIM-barrel proteins, and sensitive profile-profile searches indicate that the design sequence is distant from other naturally occurring TIM-barrel superfamilies, suggesting that Nature has sampled only a subset of the sequence space available to the TIM-barrel fold. The ability to design TIM barrels de novo opens new possibilities for custom-made enzymes.

Current therapies for multiple sclerosis (MS) reduce the frequency of relapses by modulating adaptive immune responses but fail to limit the irreversible neurodegeneration driving progressive disability. Experimental autoimmune encephalomyelitis (EAE) in Biozzi ABH mice recapitulates clinical features of MS including relapsing-remitting episodes and secondary-progressive disability. To address the contribution of recurrent inflammatory events and ageing as factors that amplify progressive neurological disease, we examined EAE in 8- to 12-week-old and 12-month-old ABH mice. Compared with the relapsing-remitting (RREAE) and secondary progressive (SPEAE) EAE observed in young mice, old mice developed progressive disease from onset (PEAE) associated with pronounced axonal damage and increased numbers of CD3(+) T cells and microglia/macrophages, but not B cells. Whereas the clinical neurological features of PEAE and SPEAE were comparable, the pathology was distinct. SPEAE was associated with significantly reduced perivascular infiltrates and T-cell numbers in the central nervous system (CNS) compared with PEAE and the acute phase of RREAE. In contrast to perivascular infiltrates that declined during progression from RREAE into SPEAE, the numbers of microglia clusters remained constant. Similar to what is observed during MS, the microglia clusters emerging during EAE were associated with axonal damage and oligodendrocytes expressing heat-shock protein B5, but not lymphocytes. Taken together, our data reveal that the course of EAE is dependent on the age of the mice. Younger mice show a relapsing-remitting phase followed by progressive disease, whereas old mice immediately show progression. This indicates that recurrent episodes of inflammation in the CNS, as well as age, contribute to progressive neurological disease.

The central nervous system (CNS) and the immune system are known to be engaged in an intense bidirectional crosstalk. In particular, the immune system has the potential to influence the induction of brain plastic phenomena and neuronal networks functioning. During direct CNS inflammation, as well as during systemic, peripheral, inflammation, the modulation exerted by neuroinflammatory mediators on synaptic plasticity might negatively influence brain neuronal networks functioning. The aim of the present study was to investigate, by using electrophysiological techniques, the ability of hippocampal excitatory synapses to undergo synaptic plasticity during the initial clinical phase of an experimental model of CNS (experimental autoimmune encephalomyelitis, EAE) as well as following a systemic inflammatory trigger. Moreover, we compared the morphologic, synaptic and molecular consequences of central neuroinflammation with those accompanying peripheral inflammation. Hippocampal long-term potentiation (LTP) has been studied by extracellular field potential recordings in the CA1 region. Immunohistochemistry was performed to investigate microglia activation. Western blot and ELISA assays have been performed to assess changes in the subunit composition of the synaptic glutamate NMDA receptor and the concentration of pro-inflammatory cytokines in the hippocampus. Significant microglial activation together with an impairment of CA1 LTP was present in the hippocampus of mice with central as well as peripheral inflammation. Interestingly, exclusively during EAE but not during systemic inflammation, the impairment of hippocampal LTP was paralleled by a selective reduction of the NMDA receptor NR2B subunit levels and a selective increase of interleukin-1β (IL1β) levels. Both central and peripheral inflammation-triggered mechanisms can activate CNS microglia and influence the function of CNS synapses. During direct CNS inflammation these events are accompanied by detectable changes in synaptic glutamate receptors subunit composition and in the levels of the pro-inflammatory cytokine IL1β.

The human proteome is rich with protein kinases, and this richness has made the kinase of crucial importance in initiating and maintaining cell behavior. Elucidating cell signaling networks and manipulating their components to understand and alter behavior require well designed inhibitors. These inhibitors are needed in culture to cause and study network perturbations, and the same compounds can be used as drugs to treat disease. Understanding the structural biology of protein kinases in detail, including their commonalities, differences and modes of substrate interaction, is necessary for designing high quality inhibitors that will be of true use for cell biology and disease therapy. To this end, we here report on a structural analysis of all available active-conformation protein kinases, discussing residue conservation, the novel features of such conservation, unique properties of atypical kinases and variability in the context of substrate binding. We also demonstrate how this information can be used for structure prediction. Our findings will be of use not only in understanding protein kinase function and evolution, but they highlight the flaws inherent in kinase drug design as commonly practiced and dictate an appropriate strategy for the sophisticated design of specific inhibitors for use in the laboratory and disease therapy.

The accuracy of a homology model based on the structure of a distant relative or other topologically equivalent protein is primarily limited by the quality of the alignment. Here we describe a systematic approach for sequence-to-structure alignment, called 'K*Sync', in which alignments are generated by dynamic programming using a scoring function that combines information on many protein features, including a novel measure of how obligate a sequence region is to the protein fold. By systematically varying the weights on the different features that contribute to the alignment score, we generate very large ensembles of diverse alignments, each optimal under a particular constellation of weights. We investigate a variety of approaches to select the best models from the ensemble, including consensus of the alignments, a hydrophobic burial measure, low- and high-resolution energy functions, and combinations of these evaluation methods. The effect on model quality and selection resulting from loop modeling and backbone optimization is also studied. The performance of the method on a benchmark set is reported and shows the approach to be effective at both generating and selecting accurate alignments. The method serves as the foundation of the homology modeling module in the Robetta server.