4,755 research outputs found
A 212-nt long RNA structure in the Tobacco necrosis virus-D RNA genome is resistant to Xrn degradation
Plus-strand RNA viruses can accumulate viral RNA degradation products during infections. Some of these decay intermediates are generated by the cytosolic 5′-to-3′ exoribonuclease Xrn1 (mammals and yeast) or Xrn4 (plants) and are formed when the enzyme stalls on substrate RNAs upon encountering inhibitory RNA structures. Many Xrn-generated RNAs correspond to 3′-terminal segments within the 3′-UTR of viral genomes and perform important functions during infections. Here we have investigated a 3′-terminal small viral RNA (svRNA) generated by Xrn during infections with Tobacco necrosis virus-D (family Tombusviridae). Our results indicate that (i) unlike known stalling RNA structures that are compact and modular, the TNV-D structure encompasses the entire 212 nt of the svRNA and is not functionally transposable, (ii) at least two tertiary interactions within the RNA structure are required for effective Xrn blocking and (iii) most of the svRNA generated in infections is derived from viral polymerase-generated subgenomic mRNA1. In vitro and in vivo analyses allowed for inferences on roles for the svRNA. Our findings provide a new and distinct addition to the growing list of Xrn-resistant viral RNAs and stalling structures found associated with different plant and animal RNA viruses.York University Librarie
Bloom filters for molecules
Ultra-large chemical libraries are reaching 10s to 100s of billions of
molecules. A challenge for these libraries is to efficiently check if a
proposed molecule is present. Here we propose and study Bloom filters for
testing if a molecule is present in a set using either string or fingerprint
representations. Bloom filters are small enough to hold billions of molecules
in just a few GB of memory and check membership in sub milliseconds. We found
string representations can have a false positive rate below 1% and require
significantly less storage than using fingerprints. Canonical SMILES with Bloom
filters with the simple FNV hashing function provide fast and accurate
membership tests with small memory requirements. We provide a general
implementation and specific filters for detecting if a molecule is purchasable,
patented, or a natural product according to existing databases at
https://github.com/whitead/molbloo
Symmetric Molecular Dynamics
We derive a formulation of molecular dynamics that generates only symmetric
configurations. We implement it for all 2D planar and 3D space groups. An atlas
of 2D Lennard-Jones crystals under all planar groups is created with symmetric
molecular dynamics
Predicting small molecules solubilities on endpoint devices using deep ensemble neural networks
Aqueous solubility is a valuable yet challenging property to predict.
Computing solubility using first-principles methods requires accounting for the
competing effects of entropy and enthalpy, resulting in long computations for
relatively poor accuracy. Data-driven approaches, such as deep learning, offer
improved accuracy and computational efficiency but typically lack uncertainty
quantification. Additionally, ease of use remains a concern for any
computational technique, resulting in the sustained popularity of group-based
contribution methods. In this work, we addressed these problems with a deep
learning model with predictive uncertainty that runs on a static website
(without a server). This approach moves computing needs onto the website
visitor without requiring installation, removing the need to pay for and
maintain servers. Our model achieves satisfactory results in solubility
prediction. Furthermore, we demonstrate how to create molecular property
prediction models that balance uncertainty and ease of use. The code is
available at \url{https://github.com/ur-whitelab/mol.dev}, and the model is
usable at \url{https://mol.dev}
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