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Machine learning is an important applied research area in particle physics, beginning with applications to high-level physics analysis in the 1990s and 2000s, followed by an explosion of applications in particle and event identification and reconstruction in the 2010s. In this document we discuss promising future research and development areas in machine learning in particle physics with a roadmap for their implementation, software and hardware resource requirements, collaborative initiatives with the data science community, academia and industry, and training the particle physics community in data science. The main objective of the document is to connect and motivate these areas of research and development with the physics drivers of the High-Luminosity Large Hadron Collider and future neutrino experiments and identify the resource needs for their implementation. Additionally we identify areas where collaboration with external communities will be of great benefit.

In magnetic fusion plasmas, a significant fraction of the kinetic pressure is contributed by superthermal charged particles produced by auxiliary heating (fast ions and electrons) and fusion reactions (a-particles). Since these energetic particles are often far away from thermal equilibrium due to their non-Maxwellian distribution and steep pressure gradients, the free energy can excite electromagnetic instabilities to intensity levels well above the thermal fluctuations. The resultant electromagnetic turbulence could induce large transport of energetic particles, which could reduce heating efficiency, degrade overall plasma confinement, and damage fusion devices. Therefore, understanding and predicting energetic particle confinement properties are critical to the success of burning plasma experiments such as ITER since the ignition relies on plasma self-heating by a-particles. To promote international exchanges and collaborations on energetic particle physics, the biannual conference series under the auspices of the International Atomic Energy Agency (IAEA) were help in Kyiv (1989), Aspenas (1991), Trieste (1993), Princeton (1995), JET/Abingdon (1997), Naka (1999), Gothenburg (2001), San Diego (2003), Takayama (2005), Kloster Seeon (2007), Kyiv (2009), and Austin (2011). The papers in this special section were presented at the most recent meeting, the 13th IAEA Technical Meeting on Energetic Particles in Magnetic Confinement Systems, which was hosted by the Fusion Simulation Center, Peking University, Beijing, China (17–20 September 2013). The program of the meeting consisted of 71 presentations, including 13 invited talks, 26 oral contributed talks, 30 posters, and 2 summary talks, which were selected by the International Advisory Committee (IAC). The IAC members include H. Berk, L.G. Eriksson, A. Fasoli, W. Heidbrink, Ya. Kolesnichenko, Ph. Lauber, Z. Lin, R. Nazikian, S. Pinches, S. Sharapov, K. Shinohara, K. Toi, G. Vlad, and X.T. Ding. The conference program, abstracts of all papers, and slides of oral presentations are available at the conference website:www.phy.pku.edu.cn/fsc/w18419.jsp As a measure of the breadth in current research activities, a wide range of topics in energetic particle physics were covered in the meeting program, including dynamics of various Alfven eigenmodes and energetic particle modes, energetic particle transport, energetic particle effects on magnetohydrodynamic (MHD) modes, runaway electrons, and diagnostics of energetic particles and neutrons. Energetic particle experiments were reported on tokamaks, stellarators, spherical tori, reversed field pinches, and linear devices. Most of the papers have direct comparisons between experimental data and simulation results, a very healthy trend in the research of energetic particle physics. As an indication for the depth in current research activities and possible future directions in energetic particle physics, some exciting progress reported at the meeting is highlighted here. The 3D fields of resonant magnetic perturbations (RMP) for controlling edge localized modes (ELM) are found to drive significant ripple loss of fast ions in DIII-D and ASDEX-U experiments. Similar loss is predicted for ITER RMP fields in the vacuum approximation. Fortunately, plasma response to RMP fields is found by the simulation to reduce the loss of fast ions and α-particles to a benign level. These results call for more accurate measurements and more reliable modeling of the plasma response to RMP fields in existing tokamak experiments and in future ITER experiments. Interesting progress on energetic particle transport by Alfven eigenmodes was made in reduced 1D models based on the critical gradients model, in which energetic particle pressure gradients are relaxed to the local threshold of Alfven eigenmode stability. Some experimental support for the critical gradient model was reported in DIII-D off-axis neutral beam injection (NBI) experiments, in which the fast-ion density relaxes to similar profiles for all injection angles. Further verification and validation of these reduced models by existing tokamak experiments and nonlinear simulations are needed. Impressive progress in first-principles simulations of Alfven eigenmodes and energetic particle transport was prominently featured at the meeting. Rigorous verification and validation have been successfully carried out for global gyrokinetic simulations of Alfven eigenmodes with kinetic effects of thermal plasmas and non-perturbative contributions by energetic particles. The gyrokinetic turbulence simulation provides an indispensable new capability for studying the nonlinear physics of energetic particles and Alfven eigenmodes by incorporating important physics of radial variations and toroidal mode coupling. For example, gyrokinetic simulations have found nonlinear oscillations of Alfven eigenmode amplitude and frequency consistent with experimental observations. With better understanding of linear and nonlinear properties of Alfven eigenmodes, a fruitful future direction is the self-consistent simulation of energetic particle transport, which requires long time simulations of nonlinear interactions between multiple Alfven eigenmodes. A significant step in this direction has been taken by MHD-gyrokinetic hybrid simulations, which have demonstrated that fast ion profile is flattened by enhanced transport due to resonance overlaps in multiple interacting Alfven eigenmodes with realistic amplitudes. A very interesting physics here is that the re-distribution of the energetic particle profile by an initially dominant Alfven eigenmode leads to the excitation of other Alfven eigenmodes. The broaden phase space volume for the extraction of free energy can then drive large fluctuation amplitudes and enhanced energetic particle transport. Some experimental evidences of such indirect interaction of multiple modes through energetic particles were observed in JT-60U and ASDEX-U experiments. Thirteen papers presented at the meeting were reviewed to the usual high standard of Nuclear Fusion and published in this special section. On behalf of the IAC, I would like to thank all participants for their contributions to this conference and to thank Nuclear Fusion for publishing this special section. The next meeting of this series will be organized by Simon Pinches and will be held at the IAEA headquarters in Vienna, in the fall of 2015.

AlphaFold has recently become an important tool in providing models for experimental structure determination by X-ray crystallography and cryo-EM. Large parts of the predicted models typically approach the accuracy of experimentally determined structures, although there are frequently local errors and errors in the relative orientations of domains. Importantly, residues in the model of a protein predicted by AlphaFold are tagged with a predicted local distance difference test score, informing users about which regions of the structure are predicted with less confidence. AlphaFold also produces a predicted aligned error matrix indicating its confidence in the relative positions of each pair of residues in the predicted model. The phenix.process_predicted_model tool downweights or removes low-confidence residues and can break a model into confidently predicted domains in preparation for molecular replacement or cryo-EM docking. These confidence metrics are further used in ISOLDE to weight torsion and atom-atom distance restraints, allowing the complete AlphaFold model to be interactively rearranged to match the docked fragments and reducing the need for the rebuilding of connecting regions.

Atomic structures of amyloid oligomers that capture the neurodegenerative disease pathology are essential to understand disease‐state causes and finding cures. Here we investigate the G6W mutation of the cytotoxic, hexameric amyloid model KV11. The mutation results into an asymmetric dodecamer composed of a pair of 30° twisted antiparallel β‐sheets. The complete break between adjacent β‐strands is unprecedented among amyloid fibril crystal structures and supports that our structure is an oligomer. The poor shape complementarity between mated sheets reveals an interior channel for binding lipids, suggesting that the toxicity may be due to a perturbation of lipid transport rather than a direct disruption of membrane integrity. Viability assays on mouse suprachiasmatic nucleus, anterior hypothalamus, and cerebral cortex demonstrated selective regional vulnerability consistent with Alzheimer's disease. Neuropeptides released from the brain slices may provide clues to how G6W initiates cellular injury.

Author(s): Carlip, S | Abstract: In an earlier short paper [Phys. Rev. Lett. 120, 101301 (2018)PRLTAO0031-900710.1103/PhysRevLett.120.101301], I argued that the horizon-preserving diffeomorphisms of a generic black hole are enhanced to a larger three-dimensional Bondi-Metzner-Sachs symmetry, which is powerful enough to determine the Bekenstein-Hawking entropy. Here, I provide details and extensions of that argument, including a loosening of horizon boundary conditions and a more thorough treatment of dimensional reduction and meaning of a "near-horizon symmetry."

In this brief essay, we combine biological, historical, philosophical and anthropological perspectives to ask anew the question about the nature of the virus. How should we understand Sars-CoV-2 and why does it matter? The argument we present is that the virus undermines any neat distinction between the natural and the human-made, the biological and the social. Rather, to understand the virus and the pandemic we need to understand both as intimately connected to our own social and historical condition. What started as a reflection on the nature of the virus thus turns into a reflection on the human condition as refracted in this pandemic or an anthropology of the virus.

Pyridine phase III, which forms at 1.69 GPa, is tetragonal and related to the previously characterized orthorhombic form II by a displacive phase transition. Phase III is similar to a high-pressure form of benzene. The soft mode governing the III→II transition has been identified using a combination of symmetry mode analysis and periodic density functional theory. A combination of single-crystal X-ray diffraction and Raman spectroscopy is used to resolve ambiguities in previous work on pyridine., Single crystals of the high-pressure phases II and III of pyridine have been obtained by in situ crystallization at 1.09 and 1.69 GPa, revealing the crystal structure of phase III for the first time using X-ray diffraction. Phase II crystallizes in P212121 with Z′ = 1 and phase III in P41212 with Z′ = ½. Neutron powder diffraction experiments using pyridine-d5 establish approximate equations of state of both phases. The space group and unit-cell dimensions of phase III are similar to the structures of other simple compounds with C 2v molecular symmetry, and the phase becomes stable at high pressure because it is topologically close-packed, resulting in a lower molar volume than the topologically body-centred cubic phase II. Phases II and III have been observed previously by Raman spectroscopy, but have been mis-identified or inconsistently named. Raman spectra collected on the same samples as used in the X-ray experiments establish the vibrational characteristics of both phases unambiguously. The pyridine molecules interact in both phases through CH⋯π and CH⋯N interactions. The nature of individual contacts is preserved through the phase transition between phases III and II, which occurs on decompression. A combination of rigid-body symmetry mode analysis and density functional theory calculations enables the soft vibrational lattice mode which governs the transformation to be identified.

© 2018 The Authors. New Phytologist © 2018 New Phytologist Trust Insights into the evolution of plant cell walls have important implications for comprehending these diverse and abundant biological structures. In order to understand the evolving structure–function relationships of the plant cell wall, it is imperative to trace the origin of its different components. The present study is focused on plant 1,4-β-xylan, tracing its evolutionary origin by genome and transcriptome mining followed by phylogenetic analysis, utilizing a large selection of plants and algae. It substantiates the findings by heterologous expression and biochemical characterization of a charophyte alga xylan synthase. Of the 12 known gene classes involved in 1,4-β-xylan formation, XYS1/IRX10 in plants, IRX7, IRX8, IRX9, IRX14 and GUX occurred for the first time in charophyte algae. An XYS1/IRX10 ortholog from Klebsormidium flaccidum, designated K. flaccidumXYLAN SYNTHASE-1 (KfXYS1), possesses 1,4-β-xylan synthase activity, and 1,4-β-xylan occurs in the K. flaccidum cell wall. These data suggest that plant 1,4-β-xylan originated in charophytes and shed light on the origin of one of the key cell wall innovations to occur in charophyte algae, facilitating terrestrialization and emergence of polysaccharide-based plant cell walls.

Engineered polyketide synthases (PKSs) are promising synthetic biology platforms for the production of chemicals with diverse applications. The dehydratase (DH) domain within modular type I PKSs generates an α,β-unsaturated bond in nascent polyketide intermediates through a dehydration reaction. Several crystal structures of DH domains have been solved, providing important structural insights into substrate selection and dehydration. Here, we present two DH domain structures from two chemically diverse PKSs. The first DH domain, isolated from the third module in the borrelidin PKS, is specific towards a trans-cyclopentane-carboxylate-containing polyketide substrate. The second DH domain, isolated from the first module in the fluvirucin B1 PKS, accepts an amide-containing polyketide intermediate. Sequence-structure analysis of these domains, in addition to previously published DH structures, display many significant similarities and key differences pertaining to substrate selection. The two major differences between BorA DH M3, FluA DH M1 and other DH domains are found in regions of unmodeled residues or residues containing high B-factors. These two regions are located between α3–β11 and β7–α2. From the catalytic Asp located in α3 to a conserved Pro in β11, the residues between them form part of the bottom of the substrate-binding cavity responsible for binding to acyl-ACP intermediates. Electronic supplementary material The online version of this article (10.1007/s10295-019-02189-z) contains supplementary material, which is available to authorized users.

The double-stranded telomeric binding protein TRF2 is expressed in many human cancers at elevated levels. Moreover, experimental overexpression of TRF2 in human cells causes replication stalling in telomeric tracts, which leads to drastic telomere shortening and fusion of deprotected chromosome ends. To understand which end joining pathway is involved in mediating these chromosome fusions, we overexpressed TRF2 in human HCT116 cell lines that were deficient for the DNA Ligase 4 (Lig4)-dependent classical non-homologous end joining (C-NHEJ) or the DNA Ligase 3 (Lig3)-dependent alternative non-homologous end joining (A-NHEJ) pathway. Surprisingly, abrogation of either Lig4 or nuclear Lig3 significantly reduced inter-chromosomal fusion of drastically shortened telomeres, suggesting that both the C-NHEJ and A-NHEJ pathways are involved in mediating this type of fusion. Fusion between deprotected sister chromatids, however, only required the Lig3-dependent A-NHEJ pathway. Interestingly, a previous study reported similar end joining pathway requirements for the fusion of critically shortened telomeres during a telomere attrition-based cellular crisis. We speculate that, as in cellular crisis, the same repair pathway(s) may drive clonal and genomic evolution in human cancers containing elevated TRF2 levels.

Molecular-replacement phasing of macromolecular crystal structures is often fast, but if a molecular-replacement solution is not immediately obtained the crystallographer must judge whether to pursue molecular replacement or to attempt experimental phasing as the quickest path to structure solution. The introduction of the expected log-likelihood gain [eLLG; McCoy et al. (2017), Proc. Natl Acad. Sci. USA, 114, 3637–3641] has given the crystallographer a powerful new tool to aid in making this decision. The eLLG is the log-likelihood gain on intensity [LLGI; Read & McCoy (2016), Acta Cryst. D72, 375–387] expected from a correctly placed model. It is calculated as a sum over the reflections of a function dependent on the fraction of the scattering for which the model accounts, the estimated model coordinate error and the measurement errors in the data. It is shown how the eLLG may be used to answer the question ‘can I solve my structure by molecular replacement?’. However, this is only the most obvious of the applications of the eLLG. It is also discussed how the eLLG may be used to determine the search order and minimal data requirements for obtaining a molecular-replacement solution using a given model, and for decision making in fragment-based molecular replacement, single-atom molecular replacement and likelihood-guided model pruning., Funding for this research was provided by: Wellcome Trust (grant No. 082961/Z/07/Z to Randy J. Read); BBSRC (grant No. BB/L006014/1 to Randy J. Read; bursary No. BB/L006014/ 1 to Claudia Milla´n, Massimo Sammito); Spanish Ministry of Economy and Competitiveness (grant No. BIO2015-64216-P to Isabel Uso´n; grant No. BIO2013-49604-EXP to Isabel Usón; grant No. MDM2014-0435-01 to Isabel Usón; scholarship No. BES-2015-071397 to Claudia Millán); National Institutes of Health (grant No. P01GM063210 to Randy J. Read).

Motivation Advances in sequencing technology continue to deliver increasingly large molecular sequence datasets that are often heavily partitioned in order to accurately model the underlying evolutionary processes. In phylogenetic analyses, partitioning strategies involve estimating conditionally independent models of molecular evolution for different genes and different positions within those genes, requiring a large number of evolutionary parameters that have to be estimated, leading to an increased computational burden for such analyses. The past two decades have also seen the rise of multi-core processors, both in the central processing unit (CPU) and Graphics processing unit processor markets, enabling massively parallel computations that are not yet fully exploited by many software packages for multipartite analyses. Results We here propose a Markov chain Monte Carlo (MCMC) approach using an adaptive multivariate transition kernel to estimate in parallel a large number of parameters, split across partitioned data, by exploiting multi-core processing. Across several real-world examples, we demonstrate that our approach enables the estimation of these multipartite parameters more efficiently than standard approaches that typically use a mixture of univariate transition kernels. In one case, when estimating the relative rate parameter of the non-coding partition in a heterochronous dataset, MCMC integration efficiency improves by > 14-fold. Availability and Implementation Our implementation is part of the BEAST code base, a widely used open source software package to perform Bayesian phylogenetic inference. Supplementary information Supplementary data are available at Bioinformatics online.

Obtaining a restraint dictionary for novel ligands or improving restraints for known ligands can require their manual modification. This can be tedious and error-prone. REEL is a restraints editor that provides quick, easy and accurate development, allowing global changes and fine-tuning of individual restraints., Chemical restraints for use in macromolecular structure refinement are produced by a variety of methods, including a number of programs that use chemical information to generate the required bond, angle, dihedral, chiral and planar restraints. These programs help to automate the process and therefore minimize the errors that could otherwise occur if it were performed manually. Furthermore, restraint-dictionary generation programs can incorporate chemical and other prior knowledge to provide reasonable choices of types and values. However, the use of restraints to define the geometry of a molecule is an approximation introduced with efficiency in mind. The representation of a bond as a parabolic function is a convenience and does not reflect the true variability in even the simplest of molecules. Another complicating factor is the interplay of the molecule with other parts of the macromolecular model. Finally, difficult situations arise from molecules with rare or unusual moieties that may not have their conformational space fully explored. These factors give rise to the need for an interactive editor for WYSIWYG interactions with the restraints and molecule. Restraints Editor, Especially Ligands (REEL) is a graphical user interface for simple and error-free editing along with additional features to provide greater control of the restraint dictionaries in macromolecular refinement.

phenix.refine is a program within the PHENIX package that supports crystallographic structure refinement against experimental data with a wide range of upper resolution limits using a large repertoire of model parameterizations. This paper presents an overview of the major phenix.refine features, with extensive literature references for readers interested in more detailed discussions of the methods., phenix.refine is a program within the PHENIX package that supports crystallographic structure refinement against experimental data with a wide range of upper resolution limits using a large repertoire of model parameterizations. It has several automation features and is also highly flexible. Several hundred parameters enable extensive customizations for complex use cases. Multiple user-defined refinement strategies can be applied to specific parts of the model in a single refinement run. An intuitive graphical user interface is available to guide novice users and to assist advanced users in managing refinement projects. X-ray or neutron diffraction data can be used separately or jointly in refinement. phenix.refine is tightly integrated into the PHENIX suite, where it serves as a critical component in automated model building, final structure refinement, structure validation and deposition to the wwPDB. This paper presents an overview of the major phenix.refine features, with extensive literature references for readers interested in more detailed discussions of the methods.

A method for the more accurate refinement of small molecules and ligands in biomolecular structures is provided. Improved ligand geometry is obtained via an all-atom molecular-mechanics force field., Modern crystal structure refinement programs rely on geometry restraints to overcome the challenge of a low data-to-parameter ratio. While the classical Engh and Huber restraints work well for standard amino-acid residues, the chemical complexity of small-molecule ligands presents a particular challenge. Most current approaches either limit ligand restraints to those that can be readily described in the Crystallographic Information File (CIF) format, thus sacrificing chemical flexibility and energetic accuracy, or they employ protocols that substantially lengthen the refinement time, potentially hindering rapid automated refinement workflows. PHENIX–AFITT refinement uses a full molecular-mechanics force field for user-selected small-molecule ligands during refinement, eliminating the potentially difficult problem of finding or generating high-quality geometry restraints. It is fully integrated with a standard refinement protocol and requires practically no additional steps from the user, making it ideal for high-throughput workflows. PHENIX–AFITT refinements also handle multiple ligands in a single model, alternate conformations and covalently bound ligands. Here, the results of combining AFITT and the PHENIX software suite on a data set of 189 protein–ligand PDB structures are presented. Refinements using PHENIX–AFITT significantly reduce ligand conformational energy and lead to improved geometries without detriment to the fit to the experimental data. For the data presented, PHENIX–AFITT refinements result in more chemically accurate models for small-molecule ligands.

Phylodynamic reconstructions rely on a measurable molecular footprint of epidemic processes in pathogen genomes. Identifying the factors that govern the tempo and mode by which these processes leave a footprint in pathogen genomes represents an important goal towards understanding infectious disease evolution. Discriminating between synonymous and non-synonymous substitution rates is crucial for testing hypotheses about the sources of evolutionary rate variation. Here, we implement a codon substitution model in a Bayesian statistical framework to estimate absolute rates of synonymous and non-synonymous substitution in unknown evolutionary histories. To demonstrate how this model can provide critical insights into pathogen evolutionary dynamics, we adopt hierarchical phylogenetic modelling with fixed effects and apply it to two viral examples. Using within-host HIV-1 data from patients with different host genetic background and different disease progression rates, we show that viral populations undergo faster absolute synonymous substitution rates in patients with faster disease progression, probably reflecting faster replication rates. We also re-analyse rabies data from different bat species in the Americas to demonstrate that climate predicts absolute synonymous substitution rates, which can be attributed to climate-associated bat activity and viral transmission dynamics. In conclusion, our model to estimate absolute rates of synonymous and non-synonymous substitution can provide a powerful approach to investigate how host ecology can shape the tempo of pathogen evolution. ispartof: MICROBIAL GENOMICS vol:2 issue:6 ispartof: location:England status: published

Highlight Analysis of the first known viable RNA polymerase III subunit mutant in Arabidopsis reveals novel roles for this complex in maintaining RNA homeostasis, adjusting the expression of a diverse suite of genes, and indirectly modulating alternative splicing., Plants employ five DNA-dependent RNA polymerases (Pols) in transcription. One of these polymerases, Pol III, has previously been reported to transcribe 5S rRNA, tRNAs, and a number of small RNAs. However, in-depth functional analysis is complicated by the fact that knockout mutations in Pol subunits are typically lethal. Here, we report the characterization of the first known viable Pol III subunit mutant, nrpc7-1. This mutant was originally isolated from a forward genetic screen designed to identify enhancers of the autoimmune mutant snc1, which contains a gain-of-function mutation in a nucleotide-binding leucine-rich repeat (NLR) immune receptor-encoding gene. The nrpc7-1 mutation occurs in an intron–exon splice site and results in intron retention in some NRPC7 transcripts. There is a global disruption in RNA equilibrium in nrpc7-1, exemplified by the altered expression of a number of RNA molecules, some of which are not reported to be transcribed by Pol III. There are developmental defects associated with the mutation, as homozygous mutant plants are dwarf, have stunted roots and siliques, and possess serrated leaves. These defects are possibly due to altered small RNA stability or activity. Additionally, the nrpc7-1 mutation confers an NLR-specific alternative splicing defect that correlates with enhanced disease resistance, highlighting the importance of alternative splicing in regulating NLR activity. Altogether, these results reveal novel roles for Pol III in maintaining RNA homeostasis, adjusting the expression of a diverse suite of genes, and indirectly modulating gene splicing. Future analyses using the nrpc7-1 mutant will be instrumental in examining other unknown Pol III functions.

© The Author 2016. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. Lignin poses a major challenge in the processing of plant biomass for agro-industrial applications. For bioengineering purposes, there is a pressing interest in identifying and characterizing the enzymes responsible for the biosynthesis of lignin. Hydroxycinnamoyl-CoA:shikimate hydroxycinnamoyl transferase (HCT; EC 2.3.1.133) is a key metabolic entry point for the synthesis of the most important lignin monomers: coniferyl and sinapyl alcohols. In this study, we investigated the substrate promiscuity of HCT from a bryophyte (Physcomitrella) and from five representatives of vascular plants (Arabidopsis, poplar, switchgrass, pine and Selaginella) using a yeast expression system. We demonstrate for these HCTs a conserved capacity to acylate with p-coumaroyl-CoA several phenolic compounds in addition to the canonical acceptor shikimate normally used during lignin biosynthesis. Using either recombinant HCT from switchgrass (PvHCT2a) or an Arabidopsis stem protein extract, we show evidence of the inhibitory effect of these phenolics on the synthesis of p-coumaroyl shikimate in vitro, which presumably occurs via a mechanism of competitive inhibition. A structural study of PvHCT2a confirmed the binding of a non-canonical acceptor in a similar manner to shikimate in the active site of the enzyme. Finally, we exploited in Arabidopsis the substrate flexibility of HCT to reduce lignin content and improve biomass saccharification by engineering transgenic lines that overproduce one of the HCT non-canonical acceptors. Our results demonstrate conservation of HCT substrate promiscuity and provide support for a new strategy for lignin reduction in the effort to improve the quality of plant biomass for forage and cellulosic biofuels.

An updated partiality model and post-refinement algorithm for XFEL snapshot diffraction data is presented and confirmed by observing anomalous density for S atoms at an X-ray wavelength of 1.3 Å., Research towards using X-ray free-electron laser (XFEL) data to solve structures using experimental phasing methods such as sulfur single-wavelength anomalous dispersion (SAD) has been hampered by shortcomings in the diffraction models for X-ray diffraction from FELs. Owing to errors in the orientation matrix and overly simple partiality models, researchers have required large numbers of images to converge to reliable estimates for the structure-factor amplitudes, which may not be feasible for all biological systems. Here, data for cytoplasmic polyhedrosis virus type 17 (CPV17) collected at 1.3 Å wavelength at the Linac Coherent Light Source (LCLS) are revisited. A previously published definition of a partiality model for reflections illuminated by self-amplified spontaneous emission (SASE) pulses is built upon, which defines a fraction between 0 and 1 based on the intersection of a reflection with a spread of Ewald spheres modelled by a super-Gaussian wavelength distribution in the X-ray beam. A method of post-refinement to refine the parameters of this model is suggested. This has generated a merged data set with an overall discrepancy (by calculating the R split value) of 3.15% to 1.46 Å resolution from a 7225-image data set. The atomic numbers of C, N and O atoms in the structure are distinguishable in the electron-density map. There are 13 S atoms within the 237 residues of CPV17, excluding the initial disordered methionine. These only possess 0.42 anomalous scattering electrons each at 1.3 Å wavelength, but the 12 that have single predominant positions are easily detectable in the anomalous difference Fourier map. It is hoped that these improvements will lead towards XFEL experimental phase determination and structure determination by sulfur SAD and will generally increase the utility of the method for difficult cases.

We hypothesized that aberrations activating epidermal growth factor receptor (EGFR) via dimerization would be more sensitive to anti-dimerization agents (e.g., cetuximab). EGFR exon 19 abnormalities (L747_A750del; deletes amino acids LREA) respond to reversible EGFR kinase inhibitors (TKIs). Exon 20 in-frame insertions and/or duplications (codons 767 to 774) and T790M mutations are clinically resistant to reversible/some irreversible TKIs. Their impact on protein function/therapeutic actionability are not fully elucidated.In our study, the index patient with non-small cell lung cancer (NSCLC) harbored EGFR D770_P772del_insKG (exon 20). A twenty patient trial (NSCLC cohort) (cetuximab-based regimen) included two participants with EGFR TKI-resistant mutations ((i) exon 20 D770>GY; and (ii) exon 19 LREA plus exon 20 T790M mutations). Structural modeling predicted that EGFR exon 20 anomalies (D770_P772del_insKG and D770>GY), but not T790M mutations, stabilize the active dimer configuration by increasing the interaction between the kinase domains, hence sensitizing to an agent preventing dimerization. Consistent with predictions, the two patients harboring D770_P772del_insKG and D770>GY, respectively, responded to an EGFR antibody (cetuximab)-based regimen; the T790M-bearing patient showed no response to cetuximab combined with erlotinib. In silico modeling merits investigation of its ability to optimize therapeutic selection based on structural/functional implications of different aberrations within the same gene.

Expression of hTS (human thymidylate synthase), a key enzyme in thymidine biosynthesis, is regulated on the translational level through a feedback mechanism that is rarely found in eukaryotes. At low substrate concentrations, the ligand-free enzyme binds to its own mRNA and stabilizes a hairpin structure that sequesters the start codon. When in complex with dUMP (2′-deoxyuridine-5′-monophosphate) and a THF (tetrahydrofolate) cofactor, the enzyme adopts a conformation that is unable to bind and repress expression of mRNA. Here, we have used a combination of X-ray crystallography, RNA mutagenesis and site-specific cross-linking studies to investigate the molecular recognition of TS mRNA by the hTS enzyme. The interacting mRNA region was narrowed to the start codon and immediately flanking sequences. In the hTS enzyme, a helix–loop–helix domain on the protein surface was identified as the putative RNA-binding site., We used crystallography and site-specific cross-linking to study interacting regions of the human thymidylate synthase and its cognate mRNA, which form a complex that represses translation of the enzyme and is implicated in resistance of tumours to antimetabolite chemotherapy.

Flexible torsion angle-based NCS restraints have been implemented in phenix.refine, allowing improved model refinement at all resolutions. Rotamer correction and rotamer consistency checks between NCS-related amino-acid side chains further improve the final model quality., One of the great challenges in refining macromolecular crystal structures is a low data-to-parameter ratio. Historically, knowledge from chemistry has been used to help to improve this ratio. When a macromolecule crystallizes with more than one copy in the asymmetric unit, the noncrystallographic symmetry relationships can be exploited to provide additional restraints when refining the working model. However, although globally similar, NCS-related chains often have local differences. To allow for local differences between NCS-related molecules, flexible torsion-based NCS restraints have been introduced, coupled with intelligent rotamer handling for protein chains, and are available in phenix.refine for refinement of models at all resolutions.

Yersinia pestis, the causative agent of bubonic plague, is able to survive in both extracellular and intracellular environments within the human host, although its intracellular survival within macrophages is poorly understood. A novelY. pestisthree-generip(required for intracellular proliferation) operon, and in particularripA, has been shown to be essential for survival and replication in interferon γ-induced macrophages. RipA was previously characterized as a putative butyryl-CoA transferase proposed to yield butyrate, a known anti-inflammatory shown to lower macrophage-produced NO levels. RipA belongs to the family I CoA transferases, which share structural homology, a conserved catalytic glutamate which forms a covalent CoA-thioester intermediate and a flexible loop adjacent to the active site known as the G(V/I)G loop. Here, functional and structural analyses of several RipA mutants are presented in an effort to dissect the CoA transferase mechanism of RipA. In particular, E61V, M31G and F60M RipA mutants show increased butyryl-CoA transferase activities when compared with wild-type RipA. Furthermore, the X-ray crystal structures of E61V, M31G and F60M RipA mutants, when compared with the wild-type RipA structure, reveal important conformational changes orchestrated by a conserved acyl-group binding-pocket phenylalanine, Phe85, and the G(V/I)G loop. Binary structures of M31G RipA and F60M RipA with two distinct CoA substrate conformations are also presented. Taken together, these data provide CoA transferase reaction snapshots of an open apo RipA, a closed glutamyl-anhydride intermediate and an open CoA-thioester intermediate. Furthermore, biochemical analyses support essential roles for both the catalytic glutamate and the flexible G(V/I)G loop along the reaction pathway, although further research is required to fully understand the function of the acyl-group binding pocket in substrate specificity.

The use of molecular replacement in solving the structures of G protein-coupled receptors is discussed, with specific examples being described in detail., G protein-coupled receptors (GPCRs) are a large class of integral membrane proteins involved in regulating virtually every aspect of human physiology. Despite their profound importance in human health and disease, structural information regarding GPCRs has been extremely limited until recently. With the advent of a variety of new biochemical and crystallographic techniques, the structural biology of GPCRs has advanced rapidly, offering key molecular insights into GPCR activation and signal transduction. To date, almost all GPCR structures have been solved using molecular-replacement techniques. Here, the unique aspects of molecular replacement as applied to individual GPCRs and to signaling complexes of these important proteins are discussed.

Social Hymenoptera have played a leading role in development and testing of kin selection theory. Inclusive fitness models, following from Hamilton's rule, successfully predict major life history characteristics, such as biased sex investment ratios and conflict over parentage of male offspring. However, kin selection models poorly predict patterns of caste-biasing nepotism and reproductive skew within groups unless kin recognition constraints or group-level selection is also invoked. These successes and failures mirror the underlying kin recognition mechanisms. With reliable environmental cues, such as the sex of offspring or the origin of male eggs, predictions are supported. When only genetic recognition cues are potentially available, predictions are not supported. Mathematical simulations demonstrate that these differing mechanisms for determining kinship produce very different patterns of behavior. Decisions based on environmental cues for relatedness result in a robust mixture of cooperation and noncooperation depending on whether or not Hamilton's rule is met. In contrast, cooperation evolves under a wider range of conditions and to higher frequencies with genetic kin recognition as shared greenbeard traits. This “excess of niceness” matches the existing patterns in caste bias and reproductive skew; individuals often help others at an apparent cost to their inclusive fitness. The results further imply a potential for greenbeard-type kin recognition to create arbitrary runaway social selection for shared genetic traits. Suggestive examples in social evolution may be alloparental care and unicoloniality in ants. Differences in kin recognition mechanisms also can have consequences for maintenance of advantageous genetic diversity within populations.

Coot is a molecular-graphics program designed to assist in the building of protein and other macromolecular models. The current state of development and available features are presented., Coot is a molecular-graphics application for model building and validation of biological macromolecules. The program displays electron-density maps and atomic models and allows model manipulations such as idealization, real-space refinement, manual rotation/translation, rigid-body fitting, ligand search, solvation, mutations, rotamers and Ramachandran idealization. Furthermore, tools are provided for model validation as well as interfaces to external programs for refinement, validation and graphics. The software is designed to be easy to learn for novice users, which is achieved by ensuring that tools for common tasks are ‘discoverable’ through familiar user-interface elements (menus and toolbars) or by intuitive behaviour (mouse controls). Recent developments have focused on providing tools for expert users, with customisable key bindings, extensions and an extensive scripting interface. The software is under rapid development, but has already achieved very widespread use within the crystallographic community. The current state of the software is presented, with a description of the facilities available and of some of the underlying methods employed.

Motivation: The identification of catalytic residues is a key step in understanding the function of enzymes. While a variety of computational methods have been developed for this task, accuracies have remained fairly low. The best existing method exploits information from sequence and structure to achieve a precision (the fraction of predicted catalytic residues that are catalytic) of 18.5% at a corresponding recall (the fraction of catalytic residues identified) of 57% on a standard benchmark. Here we present a new method, Discern, which provides a significant improvement over the state-of-the-art through the use of statistical techniques to derive a model with a small set of features that are jointly predictive of enzyme active sites. Results: In cross-validation experiments on two benchmark datasets from the Catalytic Site Atlas and CATRES resources containing a total of 437 manually curated enzymes spanning 487 SCOP families, Discern increases catalytic site recall between 12% and 20% over methods that combine information from both sequence and structure, and by ≥50% over methods that make use of sequence conservation signal only. Controlled experiments show that Discern's improvement in catalytic residue prediction is derived from the combination of three ingredients: the use of the INTREPID phylogenomic method to extract conservation information; the use of 3D structure data, including features computed for residues that are proximal in the structure; and a statistical regularization procedure to prevent overfitting. Contact: kimmen@berkeley.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Tetraploid sour cherry (Prunus cerasus L.) exhibits gametophytic self-incompatibility (GSI) whereby the specificity of self-pollen rejection is controlled by alleles of the stylar and pollen specificity genes, S-RNase and SFB (S haplotype-specific F-box protein gene), respectively. As sour cherry selections can be either self-compatible (SC) or self-incompatible (SI), polyploidy per se does not result in SC. Instead the genotype-dependent loss of SI in sour cherry is due to the accumulation of non-functional S-haplotypes. The presence of two or more non-functional S-haplotypes within sour cherry 2x pollen renders that pollen SC. Two new S-haplotypes from sour cherry, S(33) and S(34), that are presumed to be contributed by the P. fruticosa species parent, the complete S-RNase and SFB sequences of a third S-haplotype, S(35), plus the presence of two previously identified sweet cherry S-haplotypes, S(14) and S(16) are described here. Genetic segregation data demonstrated that the S(16)-, S(33)-, S(34)-, and S(35)-haplotypes present in sour cherry are fully functional. This result is consistent with our previous finding that 'hetero-allelic' pollen is incompatible in sour cherry. Phylogenetic analyses of the SFB and S-RNase sequences from available Prunus species reveal that the relationships among S-haplotypes show no correspondence to known organismal relationships at any taxonomic level within Prunus, indicating that polymorphisms at the S-locus have been maintained throughout the evolution of the genus. Furthermore, the phylogenetic relationships among SFB sequences are generally incongruent with those among S-RNase sequences for the same S-haplotypes. Hypotheses compatible with these results are discussed.

Insertion of a dangling 5′-uracil and incorporation of synthetic linkers at the domain interface of a minimal hairpin ribozyme have been investigated as means of favorably influencing crystal packing. These modifications lead to changes in the ribozyme’s structural elements that mimic packing within a natural four-way helical junction, thereby providing an example of how knowledge-based design can be used to enhance the diffraction properties of a tertiarily folded RNA., The hairpin ribozyme is a small catalytic RNA comprising two helix–loop–helix domains linked by a four-way helical junction (4WJ). In its most basic form, each domain can be formed independently and reconstituted without a 4WJ to yield an active enzyme. The production of such minimal junctionless hairpin ribozymes is achievable by chemical synthesis, which has allowed structures to be determined for numerous nucleotide variants. However, abasic and other destabilizing core modifications hinder crystallization. This investigation describes the use of a dangling 5′-U to form an intermolecular U·U mismatch, as well as the use of synthetic linkers to tether the loop A and B domains, including (i) a three-carbon propyl linker (C3L) and (ii) a nine-atom triethylene glycol linker (S9L). Both linker constructs demonstrated similar enzymatic activity, but S9L constructs yielded crystals that diffracted to 2.65 Å resolution or better. In contrast, C3L variants diffracted to 3.35 Å and exhibited a 15 Å expansion of the c axis. Crystal packing of the C3L construct showed a paucity of 61 contacts, which comprise numerous backbone to 2′-OH hydrogen bonds in junctionless and S9L complexes. Significantly, the crystal packing in minimal structures mimics stabilizing features observed in the 4WJ hairpin ribozyme structure. The results demonstrate how knowledge-based design can be used to improve diffraction and overcome otherwise destabilizing defects.

An automated ligand-fitting procedure has been developed and tested on 9327 ligands and (F o − F c)exp(iϕc) difference density from macromolecular structures in the Protein Data Bank., A procedure for fitting of ligands to electron-density maps by first fitting a core fragment of the ligand to density and then extending the remainder of the ligand into density is presented. The approach was tested by fitting 9327 ligands over a wide range of resolutions (most are in the range 0.8–­4.8 Å) from the Protein Data Bank (PDB) into (F o − F c)exp(iϕc) difference density calculated using entries from the PDB without these ligands. The procedure was able to place 58% of these 9327 ligands within 2 Å (r.m.s.d.) of the coordinates of the atoms in the original PDB entry for that ligand. The success of the fitting procedure was relatively insensitive to the size of the ligand in the range 10–100 non-H atoms and was only moderately sensitive to resolution, with the percentage of ligands placed near the coordinates of the original PDB entry for fits in the range 58–73% over all resolution ranges tested.