RBPEqBind simulates competitive binding of multiple RNA-binding proteins (RBPs) to RNA sequences using equilibrium binding kinetics.

Installation

From Bioconductor (Recommended)

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("RBPEqBind")

From GitHub (Development Version)

if (!requireNamespace("devtools", quietly = TRUE))
    install.packages("devtools")

devtools::install_github("S00NYI/RBPEqBind")

Quick Start

library(RBPEqBind)

# Load and process sample RBP models included in the package
model_file <- system.file("extdata", "model_RBP.csv", package = "RBPEqBind")
raw_models <- loadModel(model_file)
rbp_models <- setModel(raw_models, max_affinity = 100)

# Run simulation
results <- simulateBinding(
  sequence = "ACGUACGUACGUUUUUACGUACGU",
  rbp_models = rbp_models,
  protein_concs = c(HH = 100, HL = 100),
  rna_conc = 10
)

# Visualize
results$transcript <- "QuickStart"
plotBinding(results, rbp = c("HH", "HL"))

Features

• Competitive binding simulation for multiple RBPs
• Concentration grid sweeps for parameter exploration
• FASTA file support (simulateBindingFasta(), simulateGridFasta()) for multi-sequence analysis
• Visualization with binding profiles and heatmaps
• Genomic coordinate parsing from FASTA headers for BED export and peak-calling

Documentation

See the package vignette for detailed examples covering:

1. Single sequence simulation
2. Concentration grid sweeps
3. FASTA file processing
4. Visualization options

For detailed usage, see Figure_Scripts folder in: https://github.com/S00NYI/BITS_Specificity

Citation

If you use RBPEqBind in your research, please cite:

Yi S, Singh SS, Ye X, Krishna R, Kothwela V, Jankowsky E, Luna JM. (2025). Inherent Specificity and Mutational Sensitivity as Quantitative Metrics for RBP Binding. bioRxiv. https://www.biorxiv.org/content/10.1101/2025.03.28.646018v4

Work in Progress

Planned developments for RBPEqBind include:

• CLIP-Seq Concordance: Directly comparing simulated occupancy with experimental CLIP-seq peaks or crosslink signal tracks.
• RNA Structure Integration: Adding accessibility masking using SHAPE/DMS experimental reactivity profiles or pre-computed structures.

AI Usage Disclosure

This package's Bioconductor review remediation, API refactoring, and test suite expansion were developed in collaboration with Google Antigravity. For the original R and python implementation of the simulation model, see the BITS_Specificity repository.