SARS-CoV-2 structures

Last updated on Sun Feb 11 22:56:11 2024.

How to re-use this work

If you use these figures in your own work, please cite this website: https://doi.org/10.5281/zenodo.3470119

# Load required packages
library(magrittr)
library(dplyr)
library(jsonlite)
library(forcats)
library(ggplot2)
library(plotly)
library(here)
library(lubridate)

# We need two queries: one for uppercase titles, the other for lowercase ones
pdb_query <- 'https://www.ebi.ac.uk/pdbe/search/pdb/select?q=title:*SARS-CoV-2*%20AND%20status:REL&fl=pdb_id,deposition_date,citation_year,title,experimental_method,resolution,organism_scientific_name,molecule_name,molecule_type&rows=1000000&wt=json'

# This is a helper pipeline to extract data
dig_up_data <- . %>%
    .$response %>%
    .$docs %>%
    as_tibble()

# Query the PDB and clean up data
pdb_data <- pdb_query %>% 
    fromJSON() %>% 
    dig_up_data() %>% 
    bind_rows() %>% 
    mutate(
      experimental_method   = as_factor(as.character(experimental_method)),
      deposition_date       = as_date(ymd_hms(deposition_date)),
      citation_year         = as.integer(citation_year),
      molecule_name         = as.character(molecule_name),
      molecule_type         = as_factor(as.character(molecule_type))
      ) %>% 
    distinct(pdb_id, .keep_all = TRUE)

About this section

With the ongoing COVID-19 pandemic, new structures of proteins from SARS-CoV-2 are deposited to the PDB at a fast pace. The visualizations presented here won’t help curb the pandemic (and are not medical advice, obviously), but I hope they will make curious and helpless minds (like myself) get a feel for the research effort currently being deployed against it.

The following resources are a lot more relevant and actionable:

• Coronavirus Structural Task Force
• PDBe COVID-19 Data Portal
• Crowdfight COVID-19

SARS-CoV-2 structures by deposition date

All figures are interactive (you can zoom in, and hovering over elements will show more information).

sars_cov2_structures_year <- pdb_data %>% 
    ggplot() +
    geom_bar(mapping = aes(x = deposition_date)) +
    ggtitle("Structures of SARS-CoV-2 by deposition date") +
    xlab("Deposition date") +
    ylab("Number of PDB entries") +
    theme_bw()
ggplotly(sars_cov2_structures_year)

Noticeable very large numbers of depositions on a same day (for example, 68 structures deposited on March 15th and 14 structures deposited on April 7th) come from large-scale fragment screening experiments performed at Diamond Light Source:

• main protease
• macro domain
• helicase

Download figure in SVG format

SARS-CoV-2 structures by experimental method

sars_cov2_structures_method <- pdb_data %>% 
    ggplot() +
    geom_bar(mapping = aes(x = experimental_method, fill = experimental_method)) +
    guides(fill = guide_legend(title = "Experimental method")) +
    ggtitle("Structures of SARS-CoV-2 by experimental method") +
    xlab("") +
    ylab("Number of PDB entries") +
    theme_bw()
ggplotly(sars_cov2_structures_method)

Download figure in SVG format

Dataset

The graphs presented above are derived from the following dataset:

# Format table for display
pdb_table <- pdb_data %>% 
    arrange(desc(citation_year)) %>% 
    select(`PDB code` = pdb_id,
           `Citation year` = citation_year,
           `Experimental method` = experimental_method,
           Title = title)
pdb_table

Download raw dataset in JSON format