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KAMO and BLEND provide particularly effective tools to automatically manage the merging of large numbers of data sets from serial crystallography. The requirement for manual intervention in the process can be reduced by extending BLEND to support additional clustering options such as the use of more accurate cell distance metrics and the use of reflection-intensity correlation coefficients to infer `distances' among sets of reflections. This increases the sensitivity to differences in unit-cell parameters and allows clustering to assemble nearly complete data sets on the basis of intensity or amplitude differences. If the data sets are already sufficiently complete to permit it, one applies KAMO once and clusters the data using intensities only. When starting from incomplete data sets, one applies KAMO twice, first using unit-cell parameters. In this step, either the simple cell vector distance of the original BLEND or the more sensitive NCDist is used. This step tends to find clusters of sufficient size such that, when merged, each cluster is sufficiently complete to allow reflection intensities or amplitudes to be compared. One then uses KAMO again using the correlation between reflections with a common hkl to merge clusters in a way that is sensitive to structural differences that may not have perturbed the unit-cell parameters sufficiently to make meaningful clusters. Many groups have developed effective clustering algorithms that use a measurable physical parameter from each diffraction still or wedge to cluster the data into categories which then can be merged, one hopes, to yield the electron density from a single protein form. Since these physical parameters are often largely independent of one another, it should be possible to greatly improve the efficacy of data-clustering software by using a multi-stage partitioning strategy. Here, one possible approach to multi-stage data clustering is demonstrated. The strategy is to use unit-cell clustering until the merged data are sufficiently complete and then to use intensity-based clustering. Using this strategy, it is demonstrated that it is possible to accurately cluster data sets from crystals that have subtle differences.

Apocarotenoids are important signaling molecules generated from carotenoids through the action of carotenoid cleavage dioxygenases (CCDs). These enzymes have a remarkable ability to cleave carotenoids at specific alkene bonds while leaving chemically similar sites within the polyene intact. Although several bacterial and eukaryotic CCDs have been characterized, the long-standing goal of experimentally visualizing a CCD–carotenoid complex at high resolution to explain this exquisite regioselectivity remains unfulfilled. CCD genes are also present in some archaeal genomes, but the encoded enzymes remain uninvestigated. Here, we address this knowledge gap through analysis of a metazoan-like archaeal CCD from Candidatus Nitrosotalea devanaterra (NdCCD). NdCCD was active toward β-apocarotenoids but did not cleave bicyclic carotenoids. It exhibited an unusual regiospecificity, cleaving apocarotenoids solely at the C14′–C13′ alkene bond to produce β-apo-14′-carotenals. The structure of NdCCD revealed a tapered active site cavity markedly different from the broad active site observed for the retinal-forming Synechocystis apocarotenoid oxygenase (SynACO) but similar to the vertebrate retinoid isomerase RPE65. The structure of NdCCD in complex with its apocarotenoid product demonstrated that the site of cleavage is defined by interactions along the substrate binding cleft as well as selective stabilization of reaction intermediates at the scissile alkene. These data on the molecular basis of CCD catalysis shed light on the origins of the varied catalytic activities found in metazoan CCDs, opening the possibility of modifying their activity through rational chemical or genetic approaches.

The applications of artificial intelligence (AI) and machine learning (ML) technologies in wireless communications have drawn significant attention recently. AI has demonstrated real success in speech understanding, image identification, and natural language processing domains, thus exhibiting its great potential in solving problems that cannot be easily modeled. AI techniques have become an enabler in wireless communications to fulfill the increasing and diverse requirements across a large range of application scenarios. In this paper, we elaborate on several typical wireless scenarios, such as channel modeling, channel decoding and signal detection, and channel coding design, in which AI plays an important role in wireless communications. Then, AI and information theory are discussed from the viewpoint of the information bottleneck. Finally, we discuss some ideas about how AI techniques can be deeply integrated with wireless communication systems.

A distributed lossy compression network with $L$ encoders and a decoder is considered. Each encoder observes a source and sends a compressed version to the decoder. The decoder produces a joint reconstruction of target signals with the mean squared error distortion below a given threshold. It is assumed that the observed sources can be expressed as the sum of target signals and corruptive noises which are independently generated from two symmetric multivariate Gaussian distributions. The minimum compression rate of this network versus the distortion threshold is referred to as the rate-distortion function, for which an explicit lower bound is established by solving a minimization problem. Our lower bound matches the well-known Berger-Tung upper bound for some values of the distortion threshold. The asymptotic gap between the upper and lower bounds is characterized in the large $L$ limit.

Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), threatens global public health. The world needs rapid development of new antivirals and vaccines to control the current pandemic and to control the spread of the variants. Among the proteins synthesized by the SARS-CoV-2 genome, main protease (Mpro also known as 3CLpro) is a primary drug target, due to its essential role in maturation of the viral polyproteins. In this study, we provide crystallographic evidence, along with some binding assay data, that three clinically approved anti hepatitis C virus drugs and two other drug-like compounds covalently bind to the Mpro Cys145 catalytic residue in the active site. Also, molecular docking studies can provide additional insight for the design of new antiviral inhibitors for SARS-CoV-2 using these drugs as lead compounds. One might consider derivatives of these lead compounds with higher affinity to the Mpro as potential COVID-19 therapeutics for further testing and possibly clinical trials.

The metalloenzyme protein phosphatase 1 (PP1), which is responsible for ≥50% of all dephosphorylation reactions, is regulated by scores of regulatory proteins, including the highly conserved SDS22 protein. SDS22 has numerous diverse functions, surprisingly acting as both a PP1 inhibitor and as an activator. Here, we integrate cellular, biophysical, and crystallographic studies to address this conundrum. We discovered that SDS22 selectively binds a unique conformation of PP1 that contains a single metal (M2) at its active site, i.e., SDS22 traps metal-deficient inactive PP1. Furthermore, we showed that SDS22 dissociation is accompanied by a second metal (M1) being loaded into PP1, as free metal cannot dissociate the complex and M1-deficient mutants remain constitutively trapped by SDS22. Together, our findings reveal that M1 metal loading and loss are essential for PP1 regulation in cells, which has broad implications for PP1 maturation, activity, and holoenzyme subunit exchange.

Carotenoid cleavage dioxygenases (CCDs) use a nonheme Fe(II) cofactor to split alkene bonds of carotenoid and stilbenoid substrates. The iron centers of CCDs are typically five-coordinate in their resting states, with solvent occupying an exchangeable site. The involvement of this iron-bound solvent in CCD catalysis has not been experimentally addressed, but computational studies suggest two possible roles. 1) Solvent dissociation provides a coordination site for O(2), or 2) solvent remains bound to iron but changes its equilibrium position to allow O(2) binding and potentially acts as a proton source. To test these predictions, we investigated isotope effects (H(2)O versus D(2)O) on two stilbenoid-cleaving CCDs, Novosphingobium aromaticivorans oxygenase 2 (NOV2) and Neurospora crassa carotenoid oxygenase 1 (CAO1), using piceatannol as a substrate. NOV2 exhibited an inverse isotope effect (k(H)/k(D) ∼ 0.6) in an air-saturated buffer, suggesting that solvent dissociates from iron during the catalytic cycle. By contrast, CAO1 displayed a normal isotope effect (k(H)/k(D) ∼ 1.7), suggesting proton transfer in the rate-limiting step. X-ray absorption spectroscopy on NOV2 and CAO1 indicated that the protonation states of the iron ligands are unchanged within pH 6.5–8.5 and that the Fe(II)–aquo bond is minimally altered by substrate binding. We pinpointed the origin of the differential kinetic behaviors of NOV2 and CAO1 to a single amino acid difference near the solvent-binding site of iron, and X-ray crystallography revealed that the substitution alters binding of diffusible ligands to the iron center. We conclude that solvent-iron dissociation and proton transfer are both associated with the CCD catalytic mechanism.

Low-energy native-SAD phasing from microcrystals of less than 10 micrometres in size is demonstrated at a synchrotron microdiffraction beamline., De novo structural evaluation of native biomolecules from single-wavelength anomalous diffraction (SAD) is a challenge because of the weakness of the anomalous scattering. The anomalous scattering from relevant native elements – primarily sulfur in proteins and phospho­rus in nucleic acids – increases as the X-ray energy decreases toward their K-edge transitions. Thus, measurements at a lowered X-ray energy are promising for making native SAD routine and robust. For microcrystals with sizes less than 10 µm, native-SAD phasing at synchrotron microdiffraction beamlines is even more challenging because of difficulties in sample manipulation, diffraction data collection and data analysis. Native-SAD analysis from microcrystals by using X-ray free-electron lasers has been demonstrated but has required use of thousands of thousands of microcrystals to achieve the necessary accuracy. Here it is shown that by exploitation of anomalous microdiffraction signals obtained at 5 keV, by the use of polyimide wellmounts, and by an iterative crystal and frame-rejection method, microcrystal native-SAD phasing is possible from as few as about 1 200 crystals. Our results show the utility of low-energy native-SAD phasing with microcrystals at synchrotron microdiffraction beamlines.

Two new macromolecular crystallography (MX) beamlines at the National Synchrotron Light Source II, FMX and AMX, opened for general user operation in February 2017 [Schneider et al. (2013). J. Phys. Conf. Ser. 425, 012003; Fuchs et al. (2014). J. Phys. Conf. Ser. 493, 012021; Fuchs et al. (2016). AIP Conf. Proc. SRI2015, 1741, 030006]. FMX, the micro-focusing Frontier MX beamline in sector 17-ID-2 at NSLS-II, covers a 5–30 keV photon energy range and delivers a flux of 4.0 × 1012 photons s−1 at 1 Å into a 1 µm × 1.5 µm to 10 µm × 10 µm (V × H) variable focus, expected to reach 5 × 1012 photons s−1 at final storage-ring current. This flux density surpasses most MX beamlines by nearly two orders of magnitude. The high brightness and microbeam capability of FMX are focused on solving difficult crystallographic challenges. The beamline's flexible design supports a wide range of structure determination methods – serial crystallography on micrometre-sized crystals, raster optimization of diffraction from inhomogeneous crystals, high-resolution data collection from large-unit-cell crystals, room-temperature data collection for crystals that are difficult to freeze and for studying conformational dynamics, and fully automated data collection for sample-screening and ligand-binding studies. FMX's high dose rate reduces data collection times for applications like serial crystallography to minutes rather than hours. With associated sample lifetimes as short as a few milliseconds, new rapid sample-delivery methods have been implemented, such as an ultra-high-speed high-precision piezo scanner goniometer [Gao et al. (2018). J. Synchrotron Rad. 25, 1362–1370], new microcrystal-optimized micromesh well sample holders [Guo et al. (2018). IUCrJ, 5, 238–246] and highly viscous media injectors [Weierstall et al. (2014). Nat. Commun. 5, 3309]. The new beamline pushes the frontier of synchrotron crystallography and enables users to determine structures from difficult-to-crystallize targets like membrane proteins, using previously intractable crystals of a few micrometres in size, and to obtain quality structures from irregular larger crystals.

Carotenoid cleavage oxygenases (CCO) are non-heme iron enzymes that catalyze oxidative cleavage of alkene bonds in carotenoid and stilbenoid substrates. Previously, we showed that the iron cofactor of CAO1, a resveratrol-cleaving member of this family, can be substituted with cobalt to yield a catalytically inert enzyme useful for trapping active site-bound stilbenoid substrates for structural characterization. Metal substitution may provide a general method for identifying the natural substrates for CCOs in addition to facilitating structural and biophysical characterization of CCO-carotenoid complexes under normal aerobic conditions. Here, we demonstrate the general applicability of cobalt substitution in a prototypical carotenoid cleaving CCO, apocarotenoid oxygenase (ACO) from Synechocystis. Among the non-native divalent metals investigated, cobalt was uniquely able to stably occupy the ACO metal binding site and inhibit catalysis. Analysis by X-ray crystallography and X-ray absorption spectroscopy demonstrate that the Co(II) forms of both ACO and CAO1 exhibit a close structural correspondence to the native Fe(II) enzyme forms. Hence, cobalt substitution is an effective strategy for generating catalytically inert but structurally intact forms of CCOs. Electronic supplementary material The online version of this article (10.1007/s00775-018-1586-0) contains supplementary material, which is available to authorized users.

The inflammasomes are signaling platforms that promote the activation of inflammatory caspases such as caspases-1, -4, -5, and -11. Recent studies identified gasdermin D (GSDMD) as an effector for pyroptosis downstream of the inflammasome signaling pathways. Cleavage of GSDMD by inflammatory caspases allows its N-terminal domain to associate with membrane lipids and form pores that induce pyroptotic cell death. Despite the important role of GSDMD in pyroptosis, the molecular mechanisms of GSDMD recognition and cleavage by inflammatory caspases that trigger pyroptosis are poorly understood. Here, we demonstrate that the catalytic domains of inflammatory caspases can directly bind to both the full-length GSDMD and its cleavage site peptide, FLTD. A GSDMD-derived inhibitor, N-acetyl-Phe-Leu-Thr-Asp-chloromethylketone (Ac-FLTD-CMK), inhibits GSDMD cleavage by caspases-1, -4, -5, and -11 in vitro, suppresses pyroptosis downstream of both canonical and noncanonical inflammasomes, as well as reduces IL-1β release following activation of the NLRP3 inflammasome in macrophages. By contrast, the inhibitor does not target caspase-3 or apoptotic cell death, suggesting that Ac-FLTD-CMK is a specific inhibitor for inflammatory caspases. Crystal structure of caspase-1 in complex with Ac-FLTD-CMK reveals extensive enzyme–inhibitor interactions involving both hydrogen bonds and hydrophobic contacts. Comparison with other caspase-1 structures demonstrates drastic conformational changes at the four active-site loops that assemble the catalytic groove. The present study not only contributes to our understanding of GSDMD recognition by inflammatory caspases but also reports a specific inhibitor for these caspases that can serve as a tool for investigating inflammasome signaling.

Micro-sized polyimide well-mounts for the manipulation of microcrystals and a data-assembly method for rotation data sets from many microcrystals are described., With the recent developments in microcrystal handling, synchrotron microdiffraction beamline instrumentation and data analysis, microcrystal crystallo­graphy with crystal sizes of less than 10 µm is appealing at synchrotrons. However, challenges remain in sample manipulation and data assembly for robust microcrystal synchrotron crystallography. Here, the development of micro-sized polyimide well-mounts for the manipulation of microcrystals of a few micrometres in size and the implementation of a robust data-analysis method for the assembly of rotational microdiffraction data sets from many microcrystals are described. The method demonstrates that microcrystals may be routinely utilized for the acquisition and assembly of complete data sets from synchrotron microdiffraction beamlines.

Dihydrolipoamide succinyltransferase, a protein crystallization contaminant, was crystallized in a new crystal form in space group I4 and its structure was determined., The crystallization of amidase, the ultimate enzyme in the Trp-dependent auxin-biosynthesis pathway, from Arabidopsis thaliana was attempted using protein samples with at least 95% purity. Cube-shaped crystals that were assumed to be amidase crystals that belonged to space group I4 (unit-cell parameters a = b = 128.6, c = 249.7 Å) were obtained and diffracted to 3.0 Å resolution. Molecular replacement using structures from the PDB containing the amidase signature fold as search models was unsuccessful in yielding a convincing solution. Using the Sequence-Independent Molecular replacement Based on Available Databases (SIMBAD) program, it was discovered that the structure corresponded to dihydrolipoamide succinyltransferase from Escherichia coli (PDB entry 1c4t), which is considered to be a common crystallization contaminant protein. The structure was refined to an R work of 23.0% and an R free of 27.2% at 3.0 Å resolution. The structure was compared with others of the same protein deposited in the PDB. This is the first report of the structure of dihydrolipo­amide succinyltransferase isolated without an expression tag and in this novel crystal form.

The paper presents an enhanced bit-flipping (BF) successive cancellation (SC) decoding method under limited cyclic redundancy checks (CRC). Although BF-SC decoding achieves comparable performance to SC list decoding via a series of SC decodings, the existing methods are inevitably impaired under limited CRC checks, which is the case during blind detection in physical downlink control channel. To this end, we propose a path-metric-assisted BF-SC method, which before CRC checks filters the clearly erroneous decodings and further prioritizes the ones more likely to be correct. Combined with convolutional polar codes - a recently-proposed encoding method with substantial coding gain but same $2x2$ kernel as the original polar, the proposed method is demonstrated to outperform the reference polar code settings in the current 5G standard even with limited CRC checks.

The paper studies rate matching for polar codes with Reed-Solomon (RS) kernels. A low-complexity rate matching scheme, referred to as smallest index puncturing, is put forward with validity proof. To resolve the dramatically increased complexity of reliability sequence generation due to rate matching, a piecewise sequence adaptation method is designed. The method significantly cuts down the computation complexity while keeping a negligible performance loss. Simulation results demonstrate the performance gain of the 4-dimension RS kernel over the original binary 2-by-2 kernel under rate matching, and verify the efficacy of the proposed piecewise method.

Recently convolutional polar (cpolar) codes have been proposed. A tensor-network-based successive cancellation (SC) decoding was proposed for them under which cpolar codes were shown to outperform polar codes. In this paper we present the notion of m-bit-channels for cpolar codes and give the recursive construction of m-bit-channels for $m=3$ . Then a log likelihood ratio(LLR)-based SC decoding of complexity order $\mathcal{O}(Nlog(N))$ for cpolar codes is presented. We also present the numerical results for performance evaluation of cpolar codes under SC list (SCL) decoding. Our simulation results show that cpolar codes can achieve the performance of polar codes with a list size reduced by a factor of 4.

The N-terminal transactivation domain (NTD) of estrogen receptor alpha, a well-known member of the family of intrinsically disordered proteins (IDPs), mediates the receptor’s transactivation function to regulate gene expression. However, an accurate molecular dissection of NTD’s structure-function relationships remains elusive. Here, using small-angle X-ray scattering (SAXS), nuclear magnetic resonance (NMR), circular dichroism, and hydrogen exchange mass spectrometry, we show that NTD adopts a mostly disordered, unexpectedly compact conformation that undergoes structural expansion upon chemical denaturation. By combining SAXS, hydroxyl radical protein footprinting and computational modeling, we derive the ensemble-structures of the NTD and determine its ensemble-contact map that reveals metastable regional and long-range contacts, including interactions between residues I33 and S118. We show that mutation at S118, a known phosphorylation site, promotes conformational changes and increases coactivator binding. We further demonstrate via fluorine-19 (19F) NMR that mutations near residue I33 alter 19F chemical shifts at residue S118, confirming the proposed I33-S118 contact in the ensemble of structural disorder. These findings extend our understanding of IDPs’ structure-function relationship, and how specific metastable contacts mediate critical functions of disordered proteins. Highlights A compact disorder is observed for the N-terminal domain (NTD) of estrogen receptor Multi-technique modeling elucidates the NTD ensemble structures Ensemble-based contact map reveals metastable contacts between I33 and S118 19F-NMR data validate the proposed I33-S118 contact in the IDP

In this paper, a localization-based polar construction method is proposed to directly find the set of synthetic channels for information bits given a code configuration. Taking advantage of the partial order of polar codes, only a small number of synthetic channels need to be ordered, which scales as $\mathcal{O} (N/\log_2^{3/2}{N})$, resulting in a sublinear complexity to construct a polar code. Specifically, a practical method is put forward first to fast construct a group-based partial order diagram. A local area in the diagram with adaptive boundaries is then identified. By ordering the synthetic channels within the local area and combining selected ones with all the synthetic channels beyond the local area, the final set of synthetic channels for information bits are determined. Simulation results demonstrate how to adapt the boundary settings to different rate matching schemes and code configurations, and validate the effectiveness of the proposed method compared with the density evolution based methods.

The Frontier Microfocus Macromolecular Crystallography (FMX) beamline at the National Synchrotron Light Source II with its 1 µm beam size and photon flux of 3 × 1012 photons s−1 at a photon energy of 12.66 keV has reached unprecedented dose rates for a structural biology beamline. The high dose rate presents a great advantage for serial microcrystallography in cutting measurement time from hours to minutes. To provide the instrumentation basis for such measurements at the full flux of the FMX beamline, a high-speed, high-precision goniometer based on a unique XYZ piezo positioner has been designed and constructed. The piezo-based goniometer is able to achieve sub-100 nm raster-scanning precision at over 10 grid-linepairs s−1 frequency for fly scans of a 200 µm-wide raster. The performance of the scanner in both laboratory and serial crystallography measurements up to the maximum frame rate of 750 Hz of the Eiger 16M's 4M region-of-interest mode has been verified in this work. This unprecedented experimental speed significantly reduces serial-crystallography data collection time at synchrotrons, allowing utilization of the full brightness of the emerging synchrotron radiation facilities.

RPE65 is the essential trans-cis isomerase of the classical retinoid (visual) cycle. Mutations in RPE65 give rise to severe retinal dystrophies, most of which are associated with loss of protein function and recessive inheritance. The only known exception is a c.1430G>A (D477G) mutation that gives rise to dominant retinitis pigmentosa with delayed onset and choroidal and macular involvement. Position 477 is distant from functionally critical regions of RPE65. Hence, the mechanism of D477G pathogenicity remains unclear, although protein misfolding and aggregation mechanisms have been suggested. We characterized a D477G knock-in mouse model which exhibited mild age-dependent changes in retinal structure and function. Immunoblot analysis of protein extracts from the eyes of these knock-in mice demonstrated the presence of ubiquitinated RPE65 and reduced RPE65 expression. We observed an accumulation of retinyl esters in the knock-in mice as well as a delay in rhodopsin regeneration kinetics and diminished electroretinography responses, indicative of RPE65 functional impairment induced by the D477G mutation in vivo. However, a cell line expressing D477G RPE65 revealed protein expression levels, cellular localization and retinoid isomerase activity comparable to cells expressing wild-type protein. Structural analysis of an RPE65 chimera suggested that the D477G mutation does not perturb protein folding or tertiary structure. Instead, the mutation generates an aggregation-prone surface that could induce cellular toxicity through abnormal complex formation as suggested by crystal packing analysis. These results indicate that a toxic gain-of-function induced by the D477G RPE65 substitution may play a role in the pathogenesis of this form of dominant retinitis pigmentosa.

Structural characterization of proteins and their antigen complexes is essential to the development of new biologic-based medicines. Amino acid-specific covalent labeling (CL) is well suited to probe such structures, especially for cases that are difficult to examine by alternative means due to size, complexity, or instability. We present here a detailed account of carboxyl group labeling (with glycine ethyl ester (GEE) tagging) applied to a glycosylated monoclonal antibody therapeutic (mAb). The experiments were optimized to preserve the structural integrity of the mAb, and experimental conditions were varied and replicated to establish the reproducibility of the technique. Homology-based models were generated and used to compare the solvent accessibility of the labeled residues, which include aspartic acid (D), glutamic acid (E), and the C-terminus (i.e., the target probes), with the experimental data in order to understand the accuracy of the approach. Data from the mAb were compared to reactivity measures of several model peptides to explain observed variations in reactivity. Attenuation of reactivity in otherwise solvent accessible probes is documented as arising from the effects of positive charge or bond formation between adjacent amine and carboxyl groups, the latter accompanied by observed water loss. A comparison of results with previously published data by Deperalta et al using hydroxyl radical footprinting showed that 55% (32/58) of target residues were GEE labeled in this study whereas the previous study reported 21% of the targets were labeled. Although the number of target residues in GEE labeling is fewer, the two approaches provide complementary information. The results highlight advantages of this approach, such as the ease of use at the bench top, the linearity of the dose response plots at high levels of labeling, reproducibility of replicate experiments (

KAMO and Blend provide particularly effective tools to manage automatically the merging of large numbers of datasets from serial crystallography. The requirement for manual intervention in the process can be reduced by extending Blend to support additional clustering options such as use of more accurate cell distance metrics and use of reflection-intensity correlation coefficients to infer “distances” among sets of reflec- tions. This increases the sensitivity to differences in unit cell parameters and allows for clustering to assemble nearly complete datasets on the basis of intensity or ampli- tude differences. If datasets are already sufficiently complete to permit it, one applies KAMO once and clusters the data using intensities only. If starting from incomplete datasets, one applies KAMO twice, first using cell parameters. In this step we use either the simple cell vector distance of the original Blend, or we use the more sensi- tive NCDist. This step tends to find clusters of sufficient size so that, when merged, each cluster is sufficiently complete to allow reflection intensities or amplitudes to be compared. One then uses KAMO again using the correlation between the reflections having a common hkl to merge clusters in a way sensitive to structural differences that may not have perturbed the cell parameters sufficiently to make meaningful clusters.Many groups have developed effective clustering algorithms that use a measurable physical parameter from each diffraction still or wedge to cluster the data into cate- gories which then can be merged, one hopes, to yield the electron density from a single protein form. Since these physical parameters are often largely independent from one another, it should be possible to greatly improve the efficacy of data clustering software by using a multi-stage partitioning strategy. Here, we have demonstrated one possible approach to multi-stage data clustering. Our strategy is to use unit-cell clustering until merged data is sufficiently complete then to use intensity-based clustering. We have demonstrated that, using this strategy, we are able to accurately cluster datasets from crystals that have subtle differences.

Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) catalyzes the oxidative phosphorylation of d-glyceraldehyde 3-phosphate (G3P) into 1,3-diphosphoglycerate (BGP) in the presence of the NAD cofactor. GAPDH is an important drug target because of its central role in glycolysis, and nonglycolytic processes such as nuclear RNA transport, DNA replication/repair, membrane fusion and cellular apoptosis. Recent studies found that GAPDH participates in the development of diabetic retinopathy and its progression after the cessation of hyperglycemia. Here, we report two structures for native bovine photoreceptor GAPDH as a homotetramer with differing occupancy by NAD, bGAPDH(NAD)4, and bGAPDH(NAD)3. The bGAPDH(NAD)4 was solved at 1.52 A, the highest resolution for GAPDH. Structural comparison of the bGAPDH(NAD)4 and bGAPDH(NAD)3 models revealed novel details of conformational changes induced by cofactor binding, including a loop region (residues 54–56). Structure analysis of bGAPDH confirmed the importance of Phe34 in NAD binding, and demonstrated that Phe34 was stabilized in the presence of NAD but displayed greater mobility in its absence. The oxidative state of the active site Cys149 residue is regulated by NAD binding, because this residue was found oxidized in the absence of dinucleotide. The distance between Cys149 and His176 decreased upon NAD binding and Cys149 remained in a reduced state when NAD was bound. These findings provide an important structural step for understanding the mechanism of GAPDH activity in vision and its pathological role in retinopathies.

Advances in synchrotron technology are changing the landscape of macromolecular crystallography. The two recently opened beamlines at NSLS-II&mdash, AMX and FMX&mdash, deliver high-flux microfocus beams that open new possibilities for crystallographic data collection. They are equipped with state-of-the-art experimental stations and automation to allow data collection on previously intractable crystals. Optimized data collection strategies allow users to tailor crystal positioning to optimally distribute the X-ray dose over its volume. Vector data collection allows the user to define a linear trajectory along a well diffracting volume of the crystal and perform rotational data collection while moving along the vector. This is particularly well suited to long, thin crystals. We describe vector data collection of three proteins&mdash, Akt1, PI3K&alpha, and CDP-Chase&mdash, to demonstrate its application and utility. For smaller crystals, we describe two methods for multicrystal data collection in a single loop, either manually selecting multiple centers (using H108A-PHM as an example), or &ldquo, raster-collect&rdquo, a more automated approach for a larger number of crystals (using CDP-Chase as an example).