IST Austria: PubRep (Institute of Science and Technology)
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Cartesian equivariant representations for learning and understanding molecular orbitals
No full textQualitative and quantitative orbital properties such as bonding/antibonding character, localization, and orbital energies are critical to how chemists understand reactivity, catalysis, and excited-state behavior. Despite this, representations of orbitals in deep learning models have been very underdeveloped relative to representations of molecular geometries and Hamiltonians. Here, we apply state-of-the-art equivariant deep learning architectures to the task of assigning global labels to orbitals, namely energies characterizations, given the molecular coefficients from Hartree–Fock or density functional theory. The architecture we have developed, the Cartesian Equivariant Orbital Network (CEONET), shows how molecular orbital coefficients are readily featurized as equivariant node features common to all graph-based machine-learned potentials. We find that CEONET performs well at predicting difficult quantitative labels such as the orbital energy and orbital entropy. Furthermore, we find that the CEONET representation provides an intuitive latent space for differentiating orbital character for the qualitative assignment of e.g. bonding or antibonding character. In addition to providing a useful representation for further integrating deep learning with electronic structure theory, we expect CEONET to be useful for automatizing and interpreting the results of advanced electronic structure methods such as complete active space self-consistent field theory. In particular, the ability of CEONET to infer multireference character via the orbital entropy paves the way toward the machine-learned selection of active spaces
Cell migration: How animal cells run and tumble
No full textAnimal cells migrating up chemotactic gradients often show speed oscillations. A new study describes a molecular circuit that switches zebrafish germ cells between phases of straight runs, tumbling and directional reorientation
Decorrelation transition in the Wigner minor process
No full textWe consider the Wigner minor process, i.e. the eigenvalues of an N\times N Wigner matrix H^{(N)} together with the eigenvalues of all its n\times n minors, H^{(n)}, n\le N. The top eigenvalues of H^{(N)} and those of its immediate minor H^{(N-1)} are very strongly correlated, but this correlation becomes weaker for smaller minors H^{(N-k)} as k increases. For the GUE minor process the critical transition regime around k\sim N^{2/3} was analyzed by Forrester and Nagao (J. Stat. Mech.: Theory and Experiment, 2011) providing an explicit formula for the nontrivial joint correlation function. We prove that this formula is universal, i.e. it holds for the Wigner minor process. Moreover, we give a complete analysis of the sub- and supercritical regimes both for eigenvalues and for the corresponding eigenvector overlaps, thus we prove the decorrelation transition in full generality
Testing compact massive black hole binary candidates through multi-epoch spectroscopy
No full textEmission from two massive black holes (MBHs) bound in a close binary is expected to be modulated by different processes, such as the Doppler boost due to the orbital motion, accretion rate variability generated by the interaction with a circumbinary disc, and binary gravitational self-lensing. When the binary is compact enough, the two black holes are thought to be surrounded by a common broad-line region that reprocesses the impinging periodically varying ionising flux, creating broad emission lines with variable line shapes. Therefore, the study of broad emission line variability through multi-epoch spectroscopic campaigns is of paramount importance for the unambiguous identification of a binary. In this work, we study the response of a disc-like broad-line region to the Doppler-boosted ionising flux emitted by sub-milliparsec MBH binaries on a circular orbit and compare it with the response of a broad-line region illuminated by a single MBH with a periodically but isotropically varying intrinsic luminosity. We show that in the binary case, the time lags of the blue and red wings of the broad emission lines, arising from diametrically opposite sides of the circumbinary disc, are out of phase by half of the binary’s orbital period, as they each respond to the periodic ‘lighthouse’ modulation from the binary’s continuum emission. This asymmetric time lag represents a new binary signature that cannot be mimicked by a single MBH
All-rf-based coarse-tuning algorithm for quantum devices using machine learning
No full textRadio-frequency measurements could satisfy DiVincenzo’s readout criterion in future large-scale solid-state quantum processors, as they allow for high bandwidths and frequency multiplexing. However, the scalability potential of this readout technique can only be leveraged if quantum device tuning is performed using exclusively radio-frequency measurements, that is, without resorting to current measurements. We demonstrate an algorithm that performs automatic coarse tuning of double quantum dots with only radio-frequency measurements by exploiting their bandwidth and impedance matching. The tuning was completed within a few minutes with minimal prior knowledge about the device. Our results show that it is possible to eliminate the need for transport measurements for quantum-dot tuning, paving the way for more scalable device architectures
Structure of cytoplasmic RNA polymerase II
No full textRNA polymerase II (Pol II) must be assembled in the cytoplasm before it enters the nucleus, where it transcribes protein-coding genes. Although transcription by Pol II is intensively studied, how this central multi-subunit enzyme is made and the role of dedicated factors remains unclear. Here, we report the integrative structural analysis of a native human Pol II from the cytoplasm captured near the end of biogenesis. The complex contained Gdown1 and three biogenesis factors – RPAP2 and the critical small GTPases GPN1 and GPN3. Cryo-EM analysis of the complex revealed how Gdown1 and RPAP2 associate with Pol II and prevent the premature association of transcription factors. Further biochemical and cryo-EM analysis revealed how RPAP2 recruits GPN1–GPN3 to the complex, and how the assembly of the RPAP2–GPN1–GPN3 complex is controlled by GTP hydrolysis. The combined results uncover a network of interactions that chaperone cytoplasmic Pol II to prevent aberrant interactions, reveal a GTP-controlled switch during the final stages of Pol II biogenesis, and suggest a general mechanism for the action of GPN-loop GTPase family of enzymes
Mutation–selection–drift balance models of complex diseases
No full textGenetic variation that influences complex disease susceptibility is introduced into the population by mutation and removed by natural selection and genetic drift. This mutation–selection–drift balance (MSDB) shapes the prevalence of a disease and its genetic architecture. To date, however, MSDB has been modeled only for monogenic (Mendelian) diseases. Here, we develop an MSDB model for complex disease susceptibility: we assume that genotype relates to disease risk according to the canonical liability threshold model and that the selection on variants affecting risk stems from the fitness cost of the disease. We focus on diseases that are highly polygenic, entail a substantial fitness cost, and are neither extremely common in the population nor exceedingly rare. The comparison of model predictions with genome-wide association studies and other observations in humans indicates that common genetic variation affecting complex disease susceptibility is little affected by directional selection and instead shaped by pleiotropic stabilizing selection on other traits. In turn, directional selection may exert a more substantial effect on rare, large-effect variants. Our results also suggest that current estimates of disease heritability are likely biased. The model thus provides a better understanding of the evolutionary processes that shape the architecture and prevalence of complex diseases
Toward community-driven visual proteomics with large-scale cryo-electron tomography of Chlamydomonas reinhardtii
No full textIn situ cryo-electron tomography (cryo-ET) has emerged as the method of choice to investigate the structures of biomolecules in their native context. However, challenges remain for the efficient production and sharing of large-scale cryo-ET datasets. Here, we combined cryogenic plasma-based focused ion beam (cryo-PFIB) milling with recent advances in cryo-ET acquisition and processing to generate a dataset of 1,829 annotated tomograms of the green alga Chlamydomonas reinhardtii, which we provide as a community resource to drive method development and inspire biological discovery. To assay data quality, we performed subtomogram averaging of both soluble and membrane-bound complexes ranging in size from >3 MDa to ∼200 kDa, including 80S ribosomes, Rubisco, nucleosomes, microtubules, clathrin, photosystem II, and mitochondrial ATP synthase. The majority of these density maps reached sub-nanometer resolution, demonstrating the potential of this C. reinhardtii dataset as well as the promise of modern cryo-ET workflows and open data sharing to empower visual proteomics
Normal typicality and dynamical typicality for a random block-band matrix model
No full textWe prove normal typicality and dynamical typicality for a (centered) random block-band matrix model with block-dependent variances. A key feature of our model is that we achieve intermediate equilibration times, an aspect that has not been proven rigorously in any model before. Our proof builds on recently established concentration estimates for products of resolvents of Wigner type random matrices (Erdős and Riabov in Commun Math Phys 405(12): 282, 2024) and an intricate analysis of the deterministic approximation
Protocol for integrative analysis of transcription factor-nucleosome interactions using SeEN-seq and cryo-EM structure determination
No full textPioneer transcription factors (TFs) possess the ability to read out DNA motifs embedded within nucleosomes, driving changes in gene expression during cellular differentiation and reprogramming. Here, we present selected engagement on nucleosome sequencing (SeEN-seq), a protocol designed to systematically identify potential TF-binding sites on the nucleosome. We describe steps for nucleosome library assembly, SeEN-seq assay, and cryoelectron microscopy (cryo-EM) sample preparation. This protocol facilitates the preparation of homogeneous pioneer TF-nucleosome complexes for cryo-EM structure determination using single-particle analysis.
For complete details on the use and execution of this protocol, please refer to Michael et al.