145 research outputs found
Target-Free Compound Activity Prediction via Few-Shot Learning
Predicting the activities of compounds against protein-based or phenotypic
assays using only a few known compounds and their activities is a common task
in target-free drug discovery. Existing few-shot learning approaches are
limited to predicting binary labels (active/inactive). However, in real-world
drug discovery, degrees of compound activity are highly relevant. We study
Few-Shot Compound Activity Prediction (FS-CAP) and design a novel neural
architecture to meta-learn continuous compound activities across large
bioactivity datasets. Our model aggregates encodings generated from the known
compounds and their activities to capture assay information. We also introduce
a separate encoder for the unknown compound. We show that FS-CAP surpasses
traditional similarity-based techniques as well as other state of the art
few-shot learning methods on a variety of target-free drug discovery settings
and datasets.Comment: 9 pages, 2 figure
MFBind: a Multi-Fidelity Approach for Evaluating Drug Compounds in Practical Generative Modeling
Current generative models for drug discovery primarily use molecular docking
to evaluate the quality of generated compounds. However, such models are often
not useful in practice because even compounds with high docking scores do not
consistently show experimental activity. More accurate methods for activity
prediction exist, such as molecular dynamics based binding free energy
calculations, but they are too computationally expensive to use in a generative
model. We propose a multi-fidelity approach, Multi-Fidelity Bind (MFBind), to
achieve the optimal trade-off between accuracy and computational cost. MFBind
integrates docking and binding free energy simulators to train a multi-fidelity
deep surrogate model with active learning. Our deep surrogate model utilizes a
pretraining technique and linear prediction heads to efficiently fit small
amounts of high-fidelity data. We perform extensive experiments and show that
MFBind (1) outperforms other state-of-the-art single and multi-fidelity
baselines in surrogate modeling, and (2) boosts the performance of generative
models with markedly higher quality compounds.Comment: 9 pages, 4 figure
Recommended from our members
ELMO1 has an essential role in the internalization of Salmonella Typhimurium into enteric macrophages that impacts disease outcome.
Backgrounds and aims4-6 million people die of enteric infections each year. After invading intestinal epithelial cells, enteric bacteria encounter phagocytes. However, little is known about how phagocytes internalize the bacteria to generate host responses. Previously, we have shown that BAI1 (Brain Angiogenesis Inhibitor 1) binds and internalizes Gram-negative bacteria through an ELMO1 (Engulfment and cell Motility protein 1)/Rac1-dependent mechanism. Here we delineate the role of ELMO1 in host inflammatory responses following enteric infection.MethodsELMO1-depleted murine macrophage cell lines, intestinal macrophages and ELMO1 deficient mice (total or myeloid-cell specific) was infected with Salmonella enterica serovar Typhimurium. The bacterial load, inflammatory cytokines and histopathology was evaluated in the ileum, cecum and spleen. The ELMO1 dependent host cytokines were detected by a cytokine array. ELMO1 mediated Rac1 activity was measured by pulldown assay.ResultsThe cytokine array showed reduced release of pro-inflammatory cytokines, including TNF-α and MCP-1, by ELMO1-depleted macrophages. Inhibition of ELMO1 expression in macrophages decreased Rac1 activation (~6 fold) and reduced internalization of Salmonella. ELMO1-dependent internalization was indispensable for TNF-α and MCP-1. Simultaneous inhibition of ELMO1 and Rac function virtually abrogated TNF-α responses to infection. Further, activation of NF-κB, ERK1/2 and p38 MAP kinases were impaired in ELMO1-depleted cells. Strikingly, bacterial internalization by intestinal macrophages was completely dependent on ELMO1. Salmonella infection of ELMO1-deficient mice resulted in a 90% reduction in bacterial burden and attenuated inflammatory responses in the ileum, spleen and cecum.ConclusionThese findings suggest a novel role for ELMO1 in facilitating intracellular bacterial sensing and the induction of inflammatory responses following infection with Salmonella
Plasmon-phonon coupling in large-area graphene dot and antidot arrays
Nanostructured graphene on SiO2 substrates pave the way for enhanced
light-matter interactions and explorations of strong plasmon-phonon
hybridization in the mid-infrared regime. Unprecedented large-area graphene
nanodot and antidot optical arrays are fabricated by nanosphere lithography,
with structural control down to the sub-100 nanometer regime. The interaction
between graphene plasmon modes and the substrate phonons is experimentally
demonstrated and structural control is used to map out the hybridization of
plasmons and phonons, showing coupling energies of the order 20 meV. Our
findings are further supported by theoretical calculations and numerical
simulations.Comment: 7 pages including 6 figures. Supporting information is available upon
request to author
Epithelial p38α Controls Immune Cell Recruitment in the Colonic Mucosa
Intestinal epithelial cells (IECs) compose the first barrier against microorganisms in the gastrointestinal tract. Although the NF-κB pathway in IECs was recently shown to be essential for epithelial integrity and intestinal immune homeostasis, the roles of other inflammatory signaling pathways in immune responses in IECs are still largely unknown. Here we show that p38α in IECs is critical for chemokine expression, subsequent immune cell recruitment into the intestinal mucosa, and clearance of the infected pathogen. Mice with p38α deletion in IECs suffer from a sustained bacterial burden after inoculation with Citrobacter rodentium. These animals are normal in epithelial integrity and immune cell function, but fail to recruit CD4+ T cells into colonic mucosal lesions. The expression of chemokines in IECs is impaired, which appears to be responsible for the impaired T cell recruitment. Thus, p38α in IECs contributes to the host immune responses against enteric bacteria by the recruitment of immune cells
Cross-realm assessment of climate change impacts on species' abundance trends
Climate change, land-use change, pollution and exploitation are among the main drivers of species' population trends; however, their relative importance is much debated. We used a unique collection of over 1,000 local population time series in 22 communities across terrestrial, freshwater and marine realms within central Europe to compare the impacts of long-term temperature change and other environmental drivers from 1980 onwards. To disentangle different drivers, we related species' population trends to species- and driver-specific attributes, such as temperature and habitat preference or pollution tolerance. We found a consistent impact of temperature change on the local abundances of terrestrial species. Populations of warm-dwelling species increased more than those of cold-dwelling species. In contrast, impacts of temperature change on aquatic species' abundances were variable. Effects of temperature preference were more consistent in terrestrial communities than effects of habitat preference, suggesting that the impacts of temperature change have become widespread for recent changes in abundance within many terrestrial communities of central Europe.Additionally, we appreciate the open access marine data provided by the International Council for the Exploration of the Sea. We thank the following scientists for taxonomic or technical advice: C. Brendel, T. Caprano, R. Claus, K. Desender, A. Flakus, P. R. Flakus, S. Fritz, E.-M. Gerstner, J.-P. Maelfait, E.-L. Neuschulz, S. Pauls, C. Printzen, I. Schmitt and H. Turin, and I. Bartomeus for comments on a previous version of the manuscript. R.A. was supported by the EUproject LIMNOTIP funded under the seventh European Commission Framework Programme (FP7) ERA-Net Scheme (Biodiversa, 01LC1207A) and the long-term ecological research program at the Leibniz-Institute of Freshwater Ecology and Inland Fisheries (IGB). R.W.B. was supported by the Scottish Government Rural and Environment Science and Analytical Services Division (RESAS) through Theme 3 of their Strategic Research Programme. S.D. acknowledges support of the German Research Foundation DFG (grant DO 1880/1-1). S.S. acknowledges the support from the FP7 project EU BON (grant no. 308454). S.K., I.Kü. and O.S. acknowledge funding thorough the Helmholtz Association’s Programme Oriented Funding, Topic ‘Land use, biodiversity, and ecosystem services: Sustaining human livelihoods’. O.S. also acknowledges the support from FP7 via the Integrated Project STEP (grant no. 244090). D.E.B. was funded by a Landes–Offensive zur Entwicklung Wissenschaftlich–ökonomischer Exzellenz (LOEWE) excellence initiative of the Hessian Ministry for Science and the Arts and the German Research Foundation (DFG: Grant no. BO 1221/23-1).Peer Reviewe
Aberrant phase separation and nucleolar dysfunction in rare genetic diseases
Thousands of genetic variants in protein-coding genes have been linked to disease. However, the functional impact of most variants is unknown as they occur within intrinsically disordered protein regions that have poorly defined functions1-3. Intrinsically disordered regions can mediate phase separation and the formation of biomolecular condensates, such as the nucleolus4,5. This suggests that mutations in disordered proteins may alter condensate properties and function6-8. Here we show that a subset of disease-associated variants in disordered regions alter phase separation, cause mispartitioning into the nucleolus and disrupt nucleolar function. We discover de novo frameshift variants in HMGB1 that cause brachyphalangy, polydactyly and tibial aplasia syndrome, a rare complex malformation syndrome. The frameshifts replace the intrinsically disordered acidic tail of HMGB1 with an arginine-rich basic tail. The mutant tail alters HMGB1 phase separation, enhances its partitioning into the nucleolus and causes nucleolar dysfunction. We built a catalogue of more than 200,000 variants in disordered carboxy-terminal tails and identified more than 600 frameshifts that create arginine-rich basic tails in transcription factors and other proteins. For 12 out of the 13 disease-associated variants tested, the mutation enhanced partitioning into the nucleolus, and several variants altered rRNA biogenesis. These data identify the cause of a rare complex syndrome and suggest that a large number of genetic variants may dysregulate nucleoli and other biomolecular condensates in humans.© 2023. The Author(s)
Personalized medicine with IgGAM compared with standard of care for treatment of peritonitis after infectious source control (the PEPPER trial): study protocol for a randomized controlled trial
Background: Peritonitis is responsible for thousands of deaths annually in Germany alone. Even source control (SC) and antibiotic treatment often fail to prevent severe sepsis or septic shock, and this situation has hardly improved in the past two decades. Most experimental immunomodulatory therapeutics for sepsis have been aimed at blocking or dampening a specific pro-inflammatory immunological mediator. However, the patient collective is large and heterogeneous. There are therefore grounds for investigating the possibility of developing personalized therapies by classifying patients into groups according to biomarkers. This study aims to combine an assessment of the efficacy of treatment with a preparation of human immunoglobulins G, A, and M (IgGAM) with individual status of various biomarkers (immunoglobulin level, procalcitonin, interleukin 6, antigen D-related human leucocyte antigen (HLA-DR), transcription factor NF-κB1, adrenomedullin, and pathogen spectrum).
Methods/design: A total of 200 patients with sepsis or septic shock will receive standard-of-care treatment (SoC). Of these, 133 patients (selected by 1:2 randomization) will in addition receive infusions of IgGAM for 5 days. All patients will be followed for approximately 90 days and assessed by the multiple-organ failure (MOF) score, by the EQ QLQ 5D quality-of-life scale, and by measurement of vital signs, biomarkers (as above), and survival.
Discussion: This study is intended to provide further information on the efficacy and safety of treatment with IgGAM and to offer the possibility of correlating these with the biomarkers to be studied. Specifically, it will test (at a descriptive level) the hypothesis that patients receiving IgGAM who have higher inflammation status (IL-6) and poorer immune status (low HLA-DR, low immunoglobulin levels) have a better outcome than patients who do not receive IgGAM. It is expected to provide information that will help to close the knowledge gap concerning the association between the effect of IgGAM and the presence of various biomarkers, thus possibly opening the way to a personalized medicine.
Trial registration: EudraCT, 2016–001788-34; ClinicalTrials.gov, NCT03334006. Registered on 17 Nov 2017.
Trial sponsor: RWTH Aachen University, represented by the Center for Translational & Clinical Research Aachen (contact Dr. S. Isfort)
Community landscapes: an integrative approach to determine overlapping network module hierarchy, identify key nodes and predict network dynamics
Background: Network communities help the functional organization and
evolution of complex networks. However, the development of a method, which is
both fast and accurate, provides modular overlaps and partitions of a
heterogeneous network, has proven to be rather difficult. Methodology/Principal
Findings: Here we introduce the novel concept of ModuLand, an integrative
method family determining overlapping network modules as hills of an influence
function-based, centrality-type community landscape, and including several
widely used modularization methods as special cases. As various adaptations of
the method family, we developed several algorithms, which provide an efficient
analysis of weighted and directed networks, and (1) determine pervasively
overlapping modules with high resolution; (2) uncover a detailed hierarchical
network structure allowing an efficient, zoom-in analysis of large networks;
(3) allow the determination of key network nodes and (4) help to predict
network dynamics. Conclusions/Significance: The concept opens a wide range of
possibilities to develop new approaches and applications including network
routing, classification, comparison and prediction.Comment: 25 pages with 6 figures and a Glossary + Supporting Information
containing pseudo-codes of all algorithms used, 14 Figures, 5 Tables (with 18
module definitions, 129 different modularization methods, 13 module
comparision methods) and 396 references. All algorithms can be downloaded
from this web-site: http://www.linkgroup.hu/modules.ph
- …