Molecular scale imaging of F-actin assemblies immobilized on a photopolymer surface

A photo-immobilization based process is presented for direct imaging of hierarchical assemblies of biopolymers using atomic force microscopy (AFM). The technique was used to investigate the phase behavior of F-actin aggregates as a function of concentration of the divalent cation Mg2+. The data provided direct experimental evidence of a coil-on-coil (braided) structure of F-actin bundles formed at high Mg2+ concentrations. At intermediate Mg2+ concentrations, the data showed the first images of the two-dimensional nematic rafts discovered by recent x-ray studies and theoretical treatments.     

Stimuli-responsive surfaces using polyampholyte polymer brushes prepared via atom transfer radical polymerization

The synthesis of AB diblock copolymer polyampholyte polymer brushes of the type Si/SiO2//poly(acrylic acid-b-vinyl pyridine) prepared using atom transfer radical polymerization is reported. Both 2- and 4-vinyl pyridine have been used. The diblock polyampholyte polymer brushes demonstrate stimuli-responsive behavior with respect to pH, showing both polyelectrolyte and polyampholyte effects. Furthermore, we have quaternized the 4-vinyl pyridine segments to form a mixed weak/strong, or annealed/quenched, polyelectrolyte system. The quaternized polymer brush exhibits different pH-responsive behavior, with decreasing film thickness being observed with increasing pH.     

Exact Stratified Linear Rank Tests for Ordered Categorical and Binary Data

Abstract

We present an efficient algorithm for generating exact permutational distributions for linear rank statistics defined on stratified 2 × c contingency tables. The algorithm can compute exact p values and confidence intervals for a rich class of nonparametric problems. These include exact p values for stratified two-population Wilcoxon, Logrank, and Van der Waerden tests, exact p values for stratified tests of trend across several binomial populations, exact p values for stratified permutation tests with arbitrary scores, and exact confidence intervals for odds ratios embedded in stratified 2 × c tables. The algorithm uses network-based recursions to generate stratum-specific distributions and then combines them into an overall permutation distribution by convolution. Where only the tail area of a permutation distribution is desired, additional efficiency gains are achieved by backward induction and branch-and-bound processing of the network. The algorithm is especially efficient for highly imbalanced categorical data, a situation where the asymptotic theory is unreliable. The backward induction component of the algorithm can also be used to evaluate the conditional maximum likelihood, and its higher order derivatives, for the logistic regression model with grouped data. We illustrate the techniques with an analysis of two data sets: The leukemia data on survivors of the Hiroshima atomic bomb and data from an animal toxicology experiment provided by the U.S. Food and Drug Administration.     

MP-NeRF: A massively parallel method for accelerating protein structure reconstruction from internal coordinates

The conversion of proteins between internal and cartesian coordinates is a limiting step in many pipelines, such as molecular dynamics simulations and machine learning models. This conversion is typically carried out by sequential or parallel applications of the Natural extension of Reference Frame (NeRF) algorithm. This work proposes a massively parallel NeRF implementation which, depending on the polymer length, achieves speedups between 400 and 1200× over the previous state-of-the-art. It accomplishes this by dividing the conversion into three main phases: parallel composition of the monomer backbone, assembly of backbone subunits, and parallel elongation of sidechains; and by batching these computations into a minimal number of efficient matrix operations. Special emphasis is placed on reusability and ease of use. We open source the code (available at https://github.com/EleutherAI/mp_nerf ) and provide a corresponding python package.     

Improving protein secondary structure prediction: the evolutionary optimized classification algorithms

Structural Chemistry - Determining protein structures plays an important role in the field of drug design. Currently, the machine learning methods including artificial neural network (ANN) and...     

Structural evolution of environmentally responsive cationic liposome-DNA complexes with a reducible lipid linker

Environmentally responsive materials (i.e., materials that respond to changes in their environment with a change in their properties or structure) are attracting increasing amounts of interest. We recently designed and synthesized a series of cleavable multivalent lipids (CMVLn, with n = 2-5 being the number of positive headgroup charges at full protonation) with a disulfide bond in the linker between their cationic headgroup and hydrophobic tails. The self-assembled complexes of the CMVLs and DNA are a prototypical environmentally responsive material, undergoing extensive structural rearrangement when exposed to reducing agents. We investigated the structural evolution of CMVL-DNA complexes at varied complex composition, temperature, and incubation time using small-angle X-ray scattering (SAXS) and wide-angle X-ray scattering (WAXS). A related lipid with a stable linker, TMVL4, was used as a control. In a nonreducing environment, CMVL-DNA complexes form the lamellar (L(α)(C)) phase, with DNA rods sandwiched between lipid bilayers. However, new self-assembled phases form when the disulfide linker is cleaved by dithiothreitol or the biologically relevant reducing agent glutathione. The released DNA and cleaved CMVL headgroups form a loosely organized phase, giving rise to a characteristic broad SAXS correlation profile. CMVLs with high headgroup charge also form condensed DNA bundles. Intriguingly, the cleaved hydrophobic tails of the CMVLs reassemble into tilted chain-ordered L(β') phases upon incubation at physiological temperature (37 °C), as indicated by characteristic WAXS peaks. X-ray scattering further reveals that two of the three phases (L(βF), L(βL), and L(βI)) constituting the L(β') phase coexist in these samples. The described system may have applications in lipid-based nanotechnologies.     

Near-Infrared Study of the Hydrogen Bonding in Acetone-Methanol and Acetone-Ethanol Mixtures: Roles of Mechanical and Electrical Anharmonicities of Hydroxyl Oscillator

Near-infrared spectra of methanol-acetone and ethanol-acetone mixtures in the entire mole fraction range in increments of 0.1 were recorded in the region of 7500–6000 cm^?1. The first overtone bands of the hydroxyl (OH) groups were assigned to the polymeric and oligomeric OH associations. In both solutions, the frequency of the polymeric OH band decreased with the increase in the mole fraction of alcohol, which indicated the increase in the hydrogen bonding strength. The integrated area of the polymeric OH band followed the opposite trend to the frequency with the mole fraction. The nonlinearity of the plot of the integrated band area of the polymeric OH band of methanol versus the mole fraction of acetone revealed the nonideal character of the methanol-acetone mixtures, whereas the opposite was observed for the ethanol-acetone mixtures. These observations have been explained in terms of mechanical and electrical anharmonicities of the OH oscillator.     

On equivalencies between design-based and regression-based variance estimators for randomized experiments

This paper demonstrates that the randomization-based “Neyman” and constant-effects estimators for the variance of estimated average treatment effects are equivalent to a variant of the White “heteroskedasticity-robust” estimator and the homoskedastic ordinary least squares (OLS) estimator, respectively.     

Striking patterns in natural magic squares’ associated electrostatic potentials: Matrices of the 4th and 5th order

A magic square is a square matrix whereby the sum of any row, column, or any one of the two principal diagonals is equal. A surrogate of this abstract mathematical construct, introduced in 2012 by Fahimi and Jaleh, is the “electrostatic potential (ESP)” that results from treating the matrix elements of the magic square as electric charges. The overarching idea is to characterize patterns associated with these matrices that can possibly be used, in the future, in reverse to generate these squares. This study focuses on squares of order 4 and 5 with 880 and 275,305,224 distinct (irreducible/unique) realizations, respectively. It is shown that characteristic patterns emerge from plots of the ESPs of the matrices representing the studied squares. The electrostatic potentials for natural magic squares exhibit a striking pattern of maxima and minima in all distinct 880 of the 4th order and all distinct 275,305,224 of the 5th order matrices. The minimum values of ESP of Dudeney groups are discussed. Equipotential points and certain constants are found among the ESP sums along horizontal and vertical lines on the square lattice. These findings may help to open a new perspective regarding magic squares unsolved problems. While mathematics often leads discovery in physics, the latter (physics) is used here to detect otherwise invisible patterns in a mathematical object such as magic squares.     

Comparison of metabolic soft spot predictions of CYP3A4, CYP2C9 and CYP2D6 substrates using MetaSite and StarDrop

Metabolite identification study plays an important role in determining the sites of metabolic liability of new chemical entities (NCEs) in drug discovery for lead optimization. Here we compare the two predictive software, MetaSite and StarDrop, available for this purpose. They work very differently but are used to predict the site of oxidation by major human cytochrome P450 (CYP) isoforms. Neither software can predict non-CYP catalyzed metabolism nor the rates of metabolism. For the purpose of comparing the two software packages, we tested known probe substrate for these enzymes, which included 12 substrates of CYP3A4 and 18 substrates of CYP2C9 and CYP2D6 were analyzed by each software and the results were compared. It is possible that these known substrates were part of the training set but we are not aware of it. To assess the performance of each software we assigned a point system for each correct prediction. The total points assigned for each CYP isoform experimentally were compared as a percentage of the total points assigned theoretically for the first choice prediction for all substrates for each isoform. Our results show that MetaSite and StarDrop are similar in predicting the correct site of metabolism by CYP3A4 (78% vs 83%, respectively). StarDrop appears to do slightly better in predicting the correct site of metabolism by CYP2C9 and CYP2D6 metabolism (89% and 93%, respectively) compared to MetaSite (63% and 70%, respectively). The sites of metabolism (SOM) from 34 in-house NCEs incubated in human liver microsomes or human hepatocytes were also evaluated using two prediction software packages and the results showed comparable SOM predictions. What makes this comparison challenging is that the contribution of each isoform to the intrinsic clearance (Clint) is not known. Overall the software were comparable except for MetaSite performing better for CYP2D6 and that MetaSite has a liver model that is absent in StarDrop that predicted with 82% accuracy.