DiAMoNDBack: Diffusion-denoising Autoregressive Model for Non-Deterministic Backmapping of C{\alpha} Protein Traces

Coarse-grained molecular models of proteins permit access to length and time scales unattainable by all-atom models and the simulation of processes that occur on long-time scales such as aggregation and folding. The reduced resolution realizes computational accelerations but an atomistic representation can be vital for a complete understanding of mechanistic details. Backmapping is the process of restoring all-atom resolution to coarse-grained molecular models. In this work, we report DiAMoNDBack (Diffusion-denoising Autoregressive Model for Non-Deterministic Backmapping) as an autoregressive denoising diffusion probability model to restore all-atom details to coarse-grained protein representations retaining only C{\alpha} coordinates. The autoregressive generation process proceeds from the protein N-terminus to C-terminus in a residue-by-residue fashion conditioned on the C{\alpha} trace and previously backmapped backbone and side chain atoms within the local neighborhood. The local and autoregressive nature of our model makes it transferable between proteins. The stochastic nature of the denoising diffusion process means that the model generates a realistic ensemble of backbone and side chain all-atom configurations consistent with the coarse-grained C{\alpha} trace. We train DiAMoNDBack over 65k+ structures from Protein Data Bank (PDB) and validate it in applications to a hold-out PDB test set, intrinsically-disordered protein structures from the Protein Ensemble Database (PED), molecular dynamics simulations of fast-folding mini-proteins from DE Shaw Research, and coarse-grained simulation data. We achieve state-of-the-art reconstruction performance in terms of correct bond formation, avoidance of side chain clashes, and diversity of the generated side chain configurational states. We make DiAMoNDBack model publicly available as a free and open source Python package

Understanding How Kurtosis Is Transferred from Input Acceleration to Stress Response and Its Influence on Fatigue Llife

High cycle fatigue of metals typically occurs through long term exposure to time varying loads which, although modest in amplitude, give rise to microscopic cracks that can ultimately propagate to failure. The fatigue life of a component is primarily dependent on the stress amplitude response at critical failure locations. For most vibration tests, it is common to assume a Gaussian distribution of both the input acceleration and stress response. In real life, however, it is common to experience non-Gaussian acceleration input, and this can cause the response to be non-Gaussian. Examples of non-Gaussian loads include road irregularities such as potholes in the automotive world or turbulent boundary layer pressure fluctuations for the aerospace sector or more generally wind, wave or high amplitude acoustic loads. The paper first reviews some of the methods used to generate non-Gaussian excitation signals with a given power spectral density and kurtosis. The kurtosis of the response is examined once the signal is passed through a linear time invariant system. Finally an algorithm is presented that determines the output kurtosis based upon the input kurtosis, the input power spectral density and the frequency response function of the system. The algorithm is validated using numerical simulations. Direct applications of these results include improved fatigue life estimations and a method to accelerate shaker tests by generating high kurtosis, non-Gaussian drive signals

Permutationally Invariant Networks for Enhanced Sampling (PINES): Discovery of Multi-Molecular and Solvent-Inclusive Collective Variables

The typically rugged nature of molecular free energy landscapes can frustrate efficient sampling of the thermodynamically relevant phase space due to the presence of high free energy barriers. Enhanced sampling techniques can improve phase space exploration by accelerating sampling along particular collective variables (CVs). A number of techniques exist for data-driven discovery of CVs parameterizing the important large scale motions of the system. A challenge to CV discovery is learning CVs invariant to symmetries of the molecular system, frequently rigid translation, rigid rotation, and permutational relabeling of identical particles. Of these, permutational invariance have proved a persistent challenge in frustrating the the data-driven discovery of multi-molecular CVs in systems of self-assembling particles and solvent-inclusive CVs for solvated systems. In this work, we integrate Permutation Invariant Vector (PIV) featurizations with autoencoding neural networks to learn nonlinear CVs invariant to translation, rotation, and permutation, and perform interleaved rounds of CV discovery and enhanced sampling to iteratively expand sampling of configurational phase space and obtain converged CVs and free energy landscapes. We demonstrate the Permutationally Invariant Network for Enhanced Sampling (PINES) approach in applications to the self-assembly of a 13-atom Argon cluster, association/dissociation of a NaCl ion pair in water, and hydrophobic collapse of a C45H92 n-pentatetracontane polymer chain. We make the approach freely available as a new module within the PLUMED2 enhanced sampling libraries

Avirulent Strains of Toxoplasma Gondii Infect Macrophages by Active Invasion from the Phagosome

Unlike most intracellular pathogens that gain access into host cells through endocytic pathways, Toxoplasma gondii initiates infection at the cell surface by active penetration through a moving junction and subsequent formation of a parasitophorous vacuole. Here, we describe a noncanonical pathway for T. gondii infection of macrophages, in which parasites are initially internalized through phagocytosis, and then actively invade from within a phagosomal compartment to form a parasitophorous vacuole. This phagosome to vacuole invasion (PTVI) pathway may represent an intermediary link between the endocytic and the penetrative routes for host cell entry by intracellular pathogens. The PTVI pathway is preferentially used by avirulent strains of T. gondii and confers an infectious advantage over virulent strains for macrophage tropism

A hybrid double-dot in silicon

We report electrical measurements of a single arsenic dopant atom in the tunnel-barrier of a silicon SET. As well as performing electrical characterization of the individual dopant, we study series electrical transport through the dopant and SET. We measure the triple points of this hybrid double dot, using simulations to support our results, and show that we can tune the electrostatic coupling between the two sub-systems.Comment: 11 pages, 6 figure

HST and Palomar Imaging of GRB 990123: Implications for the Nature of Gamma-Ray Bursts and their Hosts

We report on HST and Palomar optical images of the field of GRB 990123, obtained on 8 and 9 February 1999. We find that the optical transient (OT) associated with GRB 990123 is located on an irregular galaxy, with magnitude V=24.20 +/- 0.15. The strong metal absorption lines seen in the spectrum of the OT, along with the low probability of a chance superposition, lead us to conclude that this galaxy is the host of the GRB. The OT is projected within the ~1'' visible stellar field of the host, nearer the edge than the center. We cannot, on this basis, rule out the galactic nucleus as the site of the GRB, since the unusual morphology of the host may be the result of an ongoing galactic merger, but our demonstration that this host galaxy has extremely blue optical to infrared colors more strongly supports an association between GRBs and star formation. We find that the OT magnitude on 1999 Feb 9.05, V = 25.45 +/- 0.15, is about 1.5 mag fainter than expected from extrapolation of the decay rate found in earlier observations. A detailed analysis of the OT light curve suggests that its fading has gone through three distinct phases: an early rapid decline (f_{nu} \propto t^{-1.6} for t < 0.1 days), a slower intermediate decline power-law decay (f_{nu} \propto t^{-1.1} for 0.1 < t < 2 days), and then a more rapid decay (at least as steep as (f_{\nu} \propto t^{-1.8} for t > 2 days). The break to steeper slope at late times may provide evidence that the optical emission from this GRB was highly beamed.Comment: Accepted for publication in Astrophysical Journal (Letters). Fourteen pages. Three encapsulated figure

Computational Prediction of Broadly Neutralizing HIV-1 Antibody Epitopes from Neutralization Activity Data

Broadly neutralizing monoclonal antibodies effective against the majority of circulating isolates of HIV-1 have been isolated from a small number of infected individuals. Definition of the conformational epitopes on the HIV spike to which these antibodies bind is of great value in defining targets for vaccine and drug design. Drawing on techniques from compressed sensing and information theory, we developed a computational methodology to predict key residues constituting the conformational epitopes on the viral spike from cross-clade neutralization activity data. Our approach does not require the availability of structural information for either the antibody or antigen. Predictions of the conformational epitopes of ten broadly neutralizing HIV-1 antibodies are shown to be in good agreement with new and existing experimental data. Our findings suggest that our approach offers a means to accelerate epitope identification for diverse pathogenic antigens