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Protein Design Explorer

Introduction

This vignette adapts the Mosaic Protein Design Explorer example for rMosaic. It explores synthesized protein minibinders generated via RFDiffusion and combines:

For pAE, lower values are better. For pLDDT, higher values are better.

Note: This example uses a remote Parquet file and may take a few seconds to load.

Example: Protein Design Explorer

library(rMosaic)

protein_data_url <- "https://idl.uw.edu/mosaic/data/protein-design.parquet"

protein_spec <- list(
  meta = list(
    title = "Protein Design Explorer",
    description = paste(
      "Explore synthesized proteins generated via RFDiffusion.",
      "Minibinders are small proteins that bind to a specific protein target.",
      "The dashboard links parameter menus, marginal histograms, a pLDDT vs. pAE raster plot, and a table of selected designs.",
      sep = "\n\n"
    ),
    credit = paste(
      "Adapted from a UW CSE 512 project by Christina Savvides,",
      "Alexander Shida, Riti Biswas, and Nora McNamara-Bordewick.",
      "Data from the UW Institute for Protein Design."
    )
  ),
  data = list(
    proteins = list(file = protein_data_url)
  ),
  params = list(
    query = list(select = "crossfilter"),
    point = list(select = "intersect", empty = TRUE),
    plddt_domain = c(67, 94.5),
    pae_domain = c(5, 29),
    scheme = "observable10"
  ),
  vconcat = list(
    # Parameter menus filter all downstream views.
    list(
      hconcat = list(
        list(
          input = "menu",
          from = "proteins",
          column = "partial_t",
          label = "Partial t",
          as = "$query"
        ),
        list(
          input = "menu",
          from = "proteins",
          column = "noise",
          label = "Noise",
          as = "$query"
        ),
        list(
          input = "menu",
          from = "proteins",
          column = "gradient_decay_function",
          label = "Gradient Decay",
          as = "$query"
        ),
        list(
          input = "menu",
          from = "proteins",
          column = "gradient_scale",
          label = "Gradient Scale",
          as = "$query"
        )
      )
    ),
    list(vspace = "1.5em"),
    # Top marginal histogram for pLDDT.
    list(
      hconcat = list(
        list(
          plot = list(
            list(
              mark = "rectY",
              data = list(from = "proteins", filterBy = "$query"),
              x = list(bin = "plddt_total", steps = 60),
              y = list(count = NULL),
              z = "version",
              fill = "version",
              order = "z",
              reverse = TRUE,
              insetLeft = 0.5,
              insetRight = 0.5
            )
          ),
          width = 600,
          height = 55,
          xAxis = NULL,
          yAxis = NULL,
          xDomain = "$plddt_domain",
          colorDomain = "Fixed",
          colorScheme = "$scheme",
          marginLeft = 40,
          marginRight = 0,
          marginTop = 0,
          marginBottom = 0
        ),
        list(hspace = 5),
        list(
          legend = "color",
          `for` = "scatter",
          columns = 1,
          as = "$query"
        )
      )
    ),
    # Main raster scatterplot plus right marginal histogram for pAE.
    list(
      hconcat = list(
        list(
          name = "scatter",
          plot = list(
            list(mark = "frame", stroke = "#ccc"),
            list(
              mark = "raster",
              data = list(from = "proteins", filterBy = "$query"),
              x = "plddt_total",
              y = "pae_interaction",
              fill = "version",
              pad = 0
            ),
            list(
              select = "intervalXY",
              as = "$query",
              brush = list(stroke = "currentColor", fill = "transparent")
            ),
            list(
              mark = "dot",
              data = list(from = "proteins", filterBy = "$point"),
              x = "plddt_total",
              y = "pae_interaction",
              fill = "version",
              stroke = "currentColor",
              strokeWidth = 0.5
            )
          ),
          opacityDomain = c(0, 2),
          opacityClamp = TRUE,
          colorDomain = "Fixed",
          colorScheme = "$scheme",
          xDomain = "$plddt_domain",
          yDomain = "$pae_domain",
          xLabelAnchor = "center",
          yLabelAnchor = "center",
          marginTop = 0,
          marginLeft = 40,
          marginRight = 0,
          width = 600,
          height = 450
        ),
        list(
          plot = list(
            list(
              mark = "rectX",
              data = list(from = "proteins", filterBy = "$query"),
              x = list(count = NULL),
              y = list(bin = "pae_interaction", steps = 60),
              z = "version",
              fill = "version",
              order = "z",
              reverse = TRUE,
              insetTop = 0.5,
              insetBottom = 0.5
            )
          ),
          width = 55,
          height = 450,
          xAxis = NULL,
          yAxis = NULL,
          marginTop = 0,
          marginLeft = 0,
          marginRight = 0,
          yDomain = "$pae_domain",
          colorDomain = "Fixed",
          colorScheme = "$scheme"
        )
      )
    ),
    list(vspace = "1em"),
    list(
      input = "table",
      as = "$point",
      filterBy = "$query",
      from = "proteins",
      columns = c(
        "version",
        "pae_interaction",
        "plddt_total",
        "noise",
        "gradient_decay_function",
        "gradient_scale",
        "movement"
      ),
      width = 680,
      height = 215
    )
  )
)

runMosaicApp(
  spec = protein_spec,
  specType = "yaml",
  data = NULL,
  title = "Protein Design Explorer",
  backend = "wasm",
  height = "900px"
)

Key Features

Crossfilter Menus and Brushing

The query parameter uses select = "crossfilter", so menus and the scatterplot brush all contribute to a single linked filter.

Dense Metric View

The central raster mark aggregates tens of thousands of protein designs by plddt_total and pae_interaction, colored by design version.

Marginal Distributions

The top and right histograms use the same query filter as the central plot, making it easier to compare pLDDT and pAE distributions after filtering by process parameters.

Linked Table

The table is filtered by the current query and writes to a separate point selection. Hovering or selecting table rows highlights corresponding records in the scatterplot.

Try It Yourself

  1. Select values from the parameter menus to compare design settings.
  2. Brush the lower-right region of the scatterplot to focus on low pAE and high pLDDT designs.
  3. Inspect the linked table to see parameter values for promising designs.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.