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Webinar Collection

ISCB COVID-19 Webinar Collection

The ISCB COVID-19 webinar collection points to webinars on ongoing research on COVID-19 and Sars-Cov2.  The webianrs are split into two lists

  1. A list of recent ISCBacademy COVID-19 webinars
  2. A list of presentations given at ISMB 2020

ISCBacademy Covid-19 Webinars

A SARS-CoV-2 protein interaction map reveals targets for drug repurposing
By Nevan Krogan

May 19, 2020

Efforts to develop antiviral drugs versus COVID-19 or vaccines for its prevention have been hampered by limited knowledge of the molecular details of SARS-CoV-2 infection. This webinar will describe our efforts to address this challenge by expressing 26 of the 29 SARS-CoV-2 proteins in human cells and identifying the human proteins physically associated with each using affinity-purification mass spectrometry. Among 332 high-confidence SARS-CoV-2-human protein-protein interactions, we identified 66 druggable human proteins or host factors targeted by 69 compounds (29 FDA-approved drugs, 12 drugs in clinical trials, and 28 preclinical compounds). Within a subset of these, multiple viral assays identified two sets of pharmacological agents that displayed antiviral activity.

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At Home with Covid-19
By Brian Shoichet

June 26, 2020

The urgency of the coronavirus pandemic has motivated investigators world wide to seek approved drugs or investigation new drugs as a way to rapidly advance therapeutics into clinical trials to treat the disease.  I will describe a large collaboration, hosted by the UCSF Quantitative Biology Institute, to do that in a mechanistically focused way.  Using AP-MS, a host-pathogen network of viral and human proteins was created, and drugs were sought targeting the human partner.  From among 322 high confidence human proteins associated with 26 viral proteins emerged 63 that were druggable.  Against those, 69 drugs were tested for efficacy, and from these 10 drugs in two broad classes emerged: those targeting protein biogenesis, and those acting against the Sigma1 and Sigma2 receptors.  The activities of these drugs, and the chemoinformatics infrastructure that supported their selection, will be discussed.  The mechanism-based repurposing strategy will be compared to a complementary effort that targets viral proteins and seeks novel chemical matter, using structure-based ultra-large library docking.

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Global surveillance of COVID-19 by mining news media using a multi-source dynamic embedded topic model
Yue Li and David Buckeridge

June 30, 2020

As the COVID-19 pandemic continues to unfold, understanding the global impact of non-pharmacological interventions (NPI) is important for formulating effective intervention strategies, particularly as many countries prepare for future waves. We used a machine learning approach to distill latent topics related to NPI from large-scale international news media. We hypothesize that these topics are informative about the timing and nature of implemented NPI, dependent on the source of the information (e.g., local news versus official government announcements) and the target countries. Given a set of latent topics associated with NPI (e.g., self-quarantine, social distancing, online education, etc), we assume that countries and media sources have different prior distributions over these topics, which are sampled to generate the news articles. To model the source-specific topic priors, we developed a semi-supervised, multi-source, dynamic, embedded topic model. Our model is able to simultaneously infer latent topics and learn a linear classifier to predict NPI labels using the topic mixtures as input for each news article. To learn these models, we developed an efficient end-to-end amortized variational inference algorithm. We applied our models to news data collected and labelled by the World Health Organization (WHO) and the Global Public Health Intelligence Network (GPHIN). Through comprehensive experiments, we observed superior topic quality and intervention prediction accuracy, compared to the baseline embedded topic models, which ignore information on media source and intervention labels. The inferred latent topics reveal distinct policies and media framing in different countries and media sources, and also characterize reaction COVID-19 and NPI in a semantically meaningful manner.

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Evolutionary origins of the SARS-CoV-2 sarbecovirus lineage responsible for the COVID-19 pandemic

September 29, 2020 at 11:00AM EDT!

There are outstanding evolutionary questions on the recent emergence of human coronavirus SARS-CoV-2 including the role of reservoir species, the role of recombination and its time of divergence from animal viruses. We find that the sarbecoviruses—the viral subgenus containing SARS-CoV and SARS-CoV-2—undergo frequent recombination and exhibit spatially structured genetic diversity on a regional scale in China. SARS-CoV-2 itself is not a recombinant of any sarbecoviruses detected to date, and its receptor-binding motif, important for specificity to human ACE2 receptors, appears to be an ancestral trait shared with bat viruses and not one acquired recently via recombination. To employ phylogenetic dating methods, recombinant regions of a 68-genome sarbecovirus alignment were removed with three independent methods. Bayesian evolutionary rate and divergence date estimates were shown to be consistent for these three approaches and for two different prior specifications of evolutionary rates based on HCoV-OC43 and MERS-CoV. Divergence dates between SARS-CoV-2 and the bat sarbecovirus reservoir were estimated as 1948 (95% highest posterior density (HPD): 1879–1999), 1969 (95% HPD: 1930–2000) and 1982 (95% HPD: 1948–2009), indicating that the lineage giving rise to SARS-CoV-2 has been circulating unnoticed in bats for decades.

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ISMB 2020 COVID-19 Related Presentations

Links within this section: COVID-19 Session | Other ISMB tracks

COVID-19 Session

Title Presenter
Tools, Workflows and Infrastructure for Open and Reproducible Analysis of SARS-CoV-2 Data  Björn Grüning
Transcriptomics-based drug repositioning pipeline identifies therapeutic candidates for COVID-19 Brian Le
Viruses, Visualization, and Validation: Interactive mining of COVID-19 literature Varun Mittal
CoV-AbDab: the Coronavirus Antibody Database Matthew Raybould
Differentially conserved amino acid positions reflect differences in SARS-CoV-2 and SARS-CoV behaviour Jake McGreig
Characterization of SARS-CoV-2 viral diversity within and across hosts Palash Sashittal
Real-time tracking of SARS-CoV-2 spread and evolution Richard Neher

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Other ISMB Tracks

Title - Track
POCOVID-Net: Automatic Detection of COVID-19 From a New Lung Ultrasound Imaging Dataset (POCUS) - TransMed Jannis Born
SS02-VIII: Gamers and experimentalists collaborate on COVID-19 - Special Sessions Firas Khatib
SS02-IX: Crowdsourced design of stabilized COVID-19 mRNA vaccines with Eterna OpenVaccine - Special Sessions Rhiju Das
SS01-XIII: Single-cell transcriptomic analysis of SARS-CoV-2 reactive CD4+ T cells - Special Sessions Benjamin Meckiff

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