Structural and functional profile of phytases across the domains of life.

Phytase enzymes are a crucial component of the natural phosphorus cycle, as they help make phosphate bioavailable by releasing it from phytate, the primary reservoir of organic phosphorus in grain and soil. Phytases also comprise a significant segment of the agricultural enzyme market, used primarily as an animal feed additive. At least four structurally and mechanistically distinct classes of phytases have evolved in bacteria and eukaryotes, and the natural diversity of each class is explored here using advances in protein structure prediction and functional annotation. This graphical review aims to provide a succinct description of the major classes of phytase enzymes across phyla, including their structures, conserved motifs, and mechanisms of action.

Automated fitting of transition state force fields for biomolecular simulations.

The generation of surrogate potential energy functions (PEF) that are orders of magnitude faster to compute but as accurate as the underlying training data from high-level electronic structure methods is one of the most promising applications of fitting procedures in chemistry. In previous work, we have shown that transition state force fields (TSFFs), fitted to the functional form of MM3* force fields using the quantum guided molecular mechanics (Q2MM) method, provide an accurate description of transition states that can be used for stereoselectivity predictions of small molecule reactions. Here, we demonstrate the applicability of the method for fit TSFFs to the well-established Amber force field, which could be used for molecular dynamics studies of enzyme reaction. As a case study, the fitting of a TSFF to the second hydride transfer in Pseudomonas mevalonii 3-hydroxy-3-methylglutaryl coenzyme A reductase (PmHMGR) is used. The differences and similarities to fitting of small molecule TSFFs are discussed.

A Phosphine-Mediated Dearomative Skeletal Rearrangement of Dianiline Squaraine Dyes.

A phosphorus(III)-mediated dearomatization of ortho-substituted dianiline squaraine dyes results in an unusual skeletal rearrangement to provide exotic, highly conjugated benzofuranone and oxindole scaffolds bearing a C3 side chain comprised of a linear conflagration of an enol, a phosphorus ylide, and 2,4-disubstituted aniline. Employing experimental and computational analysis, a mechanistic evaluation revealed a striking dependence on the acidity of the aniline ortho substituent. Notably, the rearrangement adducts underwent rapid and complete reversion to the parent squaraine in the presence of a Brønsted acid.

Recent developments in the PySCF program package.

PySCF is a Python-based general-purpose electronic structure platform that supports first-principles simulations of molecules and solids as well as accelerates the development of new methodology and complex computational workflows. This paper explains the design and philosophy behind PySCF that enables it to meet these twin objectives. With several case studies, we show how users can easily implement their own methods using PySCF as a development environment. We then summarize the capabilities of PySCF for molecular and solid-state simulations. Finally, we describe the growing ecosystem of projects that use PySCF across the domains of quantum chemistry, materials science, machine learning, and quantum information science.

Compressing physics with an autoencoder: Creating an atomic species representation to improve machine learning models in the chemical sciences.

We define a vector quantity which corresponds to atomic species identity by compressing a set of physical properties with an autoencoder. This vector, referred to here as the elemental modes, provides many advantages in downstream machine learning tasks. Using the elemental modes directly as the feature vector, we trained a neural network to predict formation energies of elpasolites with improved accuracy over previous works on the same task. Combining the elemental modes with geometric features used in high-dimensional neural network potentials (HD-NNPs) solves many problems of scaling and efficiency in the development of such neural network potentials. Whereas similar models in the past have been limited to typically four atomic species (H, C, N, and O), our implementation does not scale in cost by adding more atomic species and allows us to train an HD-NNP model which treats molecules containing H, C, N, O, F, P, S, Cl, Se, Br, and I. Finally, we establish that our implementation allows us to define feature vectors for alchemical intermediate states in the HD-NNP model, which opens up new possibilities for performing alchemical free energy calculations on systems where bond breaking/forming is important.

Evaluation of the effect of the accordion suturing technique on wound lengths in breast cancer surgery: a randomised clinical trial.

BACKGROUND: Cosmetic outcomes and scar lengths remain important considerations in breast cancer surgery. Suturing techniques should decrease scar tissue formation and provide good cosmetic results. The use of an accordion suturing technique may result in decreased surgical wound lengths and better cosmetic outcomes. We compared the outcomes of the accordion suturing technique with the standard suturing technique in breast cancer surgeries. MATERIALS AND METHODS: Female patients undergoing wide local excision of breast cancers were randomised to undergo closure of their surgical wound by either the accordion or the non-accordion (standard) suturing techniques between the months of May and October 2015. Pre-closure and post-closure wound lengths were measured intra-operatively. The primary outcome was a reduction of the surgical wound length at 6 weeks. The secondary outcome was a composite of the absence of hypertrophic scar tissue formation and optimal cosmesis. RESULTS: Thirty eligible women for wide local excision of breast tumours were randomly assigned to the accordion and non-accordion groups (15 accordion and 15 non-accordion). Seven women were excluded from the study because they underwent re-excision of margins for their breast tumours before the end of 6 weeks, and one woman was lost to follow-up. We therefore compared the outcomes of 12 women who underwent closure of their surgical wound by way of the accordion suturing technique to the outcomes of 10 women who underwent closure with the non-accordion (standard) suturing technique. The percentage reduction of wound length at 6 weeks was significantly greater in the accordion group than in the non-accordion group (M = 24.4, SD = 10.2 vs. M = 8.6, SD = 11.5, p = 0.0026). There was no significant difference in the cosmetic outcome between both groups using the James Quinn's wound evaluation score. CONCLUSION: The accordion suturing technique was associated with a significant reduction in surgical wound lengths in breast conserving surgery at 6 weeks without compromising the cosmetic result.

Accelerating Realtime TDDFT with Block-Orthogonalized Manby-Miller Embedding Theory.

Realtime time-dependent density-functional theory (RT-TDDFT) is one of the most practical techniques available to simulate electronic dynamics of molecules and materials. Promising applications of RT-TDDFT to study nonlinear spectra and energy transport demand simulations of large solvated systems over long time scales, which are computationally quite costly. In this paper, we apply an embedding technique developed for ground-state SCF methods by Manby and Miller to accelerate realtime TDDFT. We assess the accuracy and speed of these approximations by studying the absorption spectra of solvated and covalently split chromophores. Our embedding approach is also compared with less accurate, less costly QM/MM charge embeddings. We find that by mixing levels of detail the embedded mean-field theory scheme is a simple, accurate, and effective way to accelerate RT-TDDFT simulations.

Optimal feature selection applied to multispectral fluorescence imaging.

Recent rapid developments in multi-modal optical imaging have created a significant clinical demand for its in vivo--in situ application. This offers the potential for real-time tissue characterization, functional assessment, and intra-operative guidance. One of the key requirements for in vivo consideration is to minimise the acquisition window to avoid tissue motion and deformation, whilst making the best use of the available photons to account for correlation or redundancy between different dimensions. The purpose of this paper is to propose a feature selection framework to identify the best combination of features for discriminating between different tissue classes such that redundant or irrelevant information can be avoided during data acquisition. The method is based on a Bayesian framework for feature selection by using the receiver operating characteristic curves to determine the most pertinent data to capture. This represents a general technique that can be applied to different multi-modal imaging modalities and initial results derived from phantom and ex vivo tissue experiments demonstrate the potential clinical value of the technique.

Molecular and functional characterization of inositol trisphosphate receptors during early zebrafish development.

Fluctuations in cytosolic Ca(2+) are crucial for a variety of cellular processes including many aspects of development. Mobilization of intracellular Ca(2+) stores via the production of inositol trisphosphate (IP(3)) and the consequent activation of IP(3)-sensitive Ca(2+) channels is a ubiquitous means by which diverse stimuli mediate their cellular effects. Although IP(3) receptors have been well studied at fertilization, information regarding their possible involvement during subsequent development is scant. In the present study we examined the role of IP(3) receptors in early development of the zebrafish. We report the first molecular analysis of zebrafish IP(3) receptors which indicates that, like mammals, the zebrafish genome contains three distinct IP(3) receptor genes. mRNA for all isoforms was detectable at differing levels by the 64 cell stage, and IP(3)-induced Ca(2+) transients could be readily generated (by flash photolysis) in a controlled fashion throughout the cleavage period in vivo. Furthermore, we show that early blastula formation was disrupted by pharmacological blockade of IP(3) receptors or phospholipase C, by molecular inhibition of the former by injection of IRBIT (IP(3) receptor-binding protein released with IP(3)) and by depletion of thapsigargin-sensitive Ca(2+) stores after completion of the second cell cycle. Inhibition of Ca(2+) entry or ryanodine receptors, however, had little effect. Our work defines the importance of IP(3) receptors during early development of a genetically and optically tractable model vertebrate organism.