Long-range correlation energy calculated from coupled atomic response functions

An accurate determination of the electron correlation energy is essential for describing the structure, stability, and function in a wide variety of systems, ranging from gas-phase molecular assemblies to condensed matter and organic/inorganic interfaces. Even small errors in the correlation energy can have a large impact on the description of chemical and physical properties in the systems of interest. In this context, the development of efficient approaches for the accurate calculation of the long-range correlation energy (and hence dispersion) is the main challenge. In the last years a number of methods have been developed to augment density functional approximations via dispersion energy corrections, but most of these approaches ignore the intrinsic many-body nature of correlation effects, leading to inconsistent and sometimes even qualitatively incorrect predictions. Here we build upon the recent many-body dispersion (MBD) framework, which is intimately linked to the random-phase approximation for the correlation energy. We separate the correlation energy into short-range contributions that are modeled by semi-local functionals and long-range contributions that are calculated by mapping the complex all-electron problem onto a set of atomic response functions coupled in the dipole approximation. We propose an effective range-separation of the coupling between the atomic response functions that extends the already broad applicability of the MBD method to non-metallic materials with highly anisotropic responses, such as layered nanostructures. Application to a variety of high-quality benchmark datasets illustrates the accuracy and applicability of the improved MBD approach, which offers the prospect of first-principles modeling of large structurally complex systems with an accurate description of the long-range correlation energy.Comment: 15 pages, 3 figure

Accurate molecular polarizabilities with coupled-cluster theory and machine learning

The molecular polarizability describes the tendency of a molecule to deform or polarize in response to an applied electric field. As such, this quantity governs key intra- and inter-molecular interactions such as induction and dispersion, plays a key role in determining the spectroscopic signatures of molecules, and is an essential ingredient in polarizable force fields and other empirical models for collective interactions. Compared to other ground-state properties, an accurate and reliable prediction of the molecular polarizability is considerably more difficult as this response quantity is quite sensitive to the description of the underlying molecular electronic structure. In this work, we present state-of-the-art quantum mechanical calculations of the static dipole polarizability tensors of 7,211 small organic molecules computed using linear-response coupled-cluster singles and doubles theory (LR-CCSD). Using a symmetry-adapted machine-learning based approach, we demonstrate that it is possible to predict the molecular polarizability with LR-CCSD accuracy at a negligible computational cost. The employed model is quite robust and transferable, yielding molecular polarizabilities for a diverse set of 52 larger molecules (which includes challenging conjugated systems, carbohydrates, small drugs, amino acids, nucleobases, and hydrocarbon isomers) at an accuracy that exceeds that of hybrid density functional theory (DFT). The atom-centered decomposition implicit in our machine-learning approach offers some insight into the shortcomings of DFT in the prediction of this fundamental quantity of interest

Crossover from Poisson to Wigner-Dyson Level Statistics in Spin Chains with Integrability Breaking

We study numerically the evolution of energy-level statistics as an integrability-breaking term is added to the XXZ Hamiltonian. For finite-length chains, physical properties exhibit a cross-over from behavior resulting from the Poisson level statistics characteristic of integrable models to behavior corresponding to the Wigner-Dyson statistics characteristic of the random-matrix theory used to describe chaotic systems. Different measures of the level statistics are observed to follow different crossover patterns. The range of numerically accessible system sizes is too small to establish with certainty the scaling with system size, but the evidence suggests that in a thermodynamically large system an infinitesimal integrability breaking would lead to Wigner-Dyson behavior.Comment: 8 pages, 8 figures, Revtex

Methylrhenium Trioxide Revisited: Mechanisms for Nonredox Oxygen Insertion in an M−CH_3 Bond

Methylrhenium trioxide (MTO) has the rare ability to stoichiometrically generate methanol at room temperature with an external oxidant (H_2O_2) under basic conditions. In order to use this transformation as a model for nonredox oxidative C−O coupling, the mechanisms have been elucidated using density functional theory (DFT). Our studies show several possible reaction pathways to form methanol, with the lowest net barrier (ΔH‡) being 23.3 kcal mol^(-1). The rate-determining step is a direct “Baeyer−Villiger” type concerted oxygen insertion into MTO, forming methoxyrhenium trioxide. The key to the low-energy transition state is the donation of electron density, first, from HOO(−) to the –CH_3 group (making –CH_3 more nucleophilic and HOO− more electrophilic) and, second, from the Re−C bond to both the forming Re−O and breaking O−O bonds, simultaneously (thus forming the Re−O bond as the Re−C bond is broken). In turn, the ability of MTO to undergo these transfers can be traced to the electrophilic nature of the metal center and to the absence of accessible d-orbitals. If accessible d-orbitals are present, they would most likely donate the required electron density instead of the M−CH_3 moiety, and this bond would thus not be broken. It is possible that other metal centers with similar qualities, such as Pt^(IV) or Ir^V, could be competent for the same type of chemistry

Report on the sixth blind test of organic crystal-structure prediction methods

The sixth blind test of organic crystal-structure prediction (CSP) methods has been held, with five target systems: a small nearly rigid molecule, a polymorphic former drug candidate, a chloride salt hydrate, a co-crystal, and a bulky flexible molecule. This blind test has seen substantial growth in the number of submissions, with the broad range of prediction methods giving a unique insight into the state of the art in the field. Significant progress has been seen in treating flexible molecules, usage of hierarchical approaches to ranking structures, the application of density-functional approximations, and the establishment of new workflows and "best practices" for performing CSP calculations. All of the targets, apart from a single potentially disordered Z` = 2 polymorph of the drug candidate, were predicted by at least one submission. Despite many remaining challenges, it is clear that CSP methods are becoming more applicable to a wider range of real systems, including salts, hydrates and larger flexible molecules. The results also highlight the potential for CSP calculations to complement and augment experimental studies of organic solid forms

The At Home/Chez Soi trial protocol: a pragmatic, multi-site, randomised controlled trial of a Housing First intervention for homeless individuals with mental illness in five Canadian cities

This article was published in BMJ Open following peer review and can also be viewed on the journal’s website at http://bmjopen.bmj.comIntroduction: Housing First is a complex housing and support intervention for homeless individuals with mental health problems. It has a sufficient knowledge base and interest to warrant a test of wide-scale implementation in various settings. This protocol describes the quantitative design of a Canadian five city, $110 million demonstration project and provides the rationale for key scientific decisions. Methods: A pragmatic, mixed methods, multi-site field trial of the effectiveness of Housing First in Vancouver, Winnipeg, Toronto, Montreal and Moncton, is randomising approximately 2500 participants, stratified by high and moderate need levels, into intervention and treatment as usual groups. Quantitative outcome measures are being collected over a 2-year period and a qualitative process evaluation is being completed. Primary outcomes are housing stability, social functioning and, for the economic analyses, quality of life. Hierarchical linear modelling is the primary data analytic strategy. Ethics and dissemination: Research ethics board approval has been obtained from 11 institutions and a safety and adverse events committee is in place. The results of the multi-site analyses of outcomes at 12 months and 2 years will be reported in a series of core scientific journal papers. Extensive knowledge exchange activities with non-academic audiences will occur throughout the duration of the project.This work was supported by a contract from Health Canada administrated by the Mental Health Commission of Canada

Cdc37 has distinct roles in protein kinase quality control that protect nascent chains from degradation and promote posttranslational maturation

Cdc37 is a molecular chaperone that functions with Hsp90 to promote protein kinase folding. Analysis of 65 Saccharomyces cerevisiae protein kinases (∼50% of the kinome) in a cdc37 mutant strain showed that 51 had decreased abundance compared with levels in the wild-type strain. Several lipid kinases also accumulated in reduced amounts in the cdc37 mutant strain. Results from our pulse-labeling studies showed that Cdc37 protects nascent kinase chains from rapid degradation shortly after synthesis. This degradation phenotype was suppressed when cdc37 mutant cells were grown at reduced temperatures, although this did not lead to a full restoration of kinase activity. We propose that Cdc37 functions at distinct steps in kinase biogenesis that involves protecting nascent chains from rapid degradation followed by its folding function in association with Hsp90. Our studies demonstrate that Cdc37 has a general role in kinome biogenesis