Molecular Dynamics Simulation Study of SF3A1–snRNA Interaction

🧬 Overview

This repository contains molecular dynamics (MD) simulation data and analysis for studying the interaction between SF3A1 ULD domain and U1 SL4 snRNA, focusing on effects of mutation on conformational preferences during early spliceosome assembly.

The dataset includes:

• Wild-type (WT) and mutant simulations
• Replicate trajectories
• Structural and dynamic analyses (RMSD, RMSF, Radius of Gyration, correlation maps)

---

📁 Directory Structure

.
├── data
│   ├── basic_analysis        # RMSD, RMSF, Radius of Gyration
│   ├── rmscorr               # RMS correlation analysis
│   └── traj                  # MD trajectories (WT and mutants)
├── scripts                   # Analysis scripts (Jupyter notebooks)
└── README.md

---

📊 Data Description

🔹 Basic Analyses

Located in: data/basic_analysis/

Includes:

• RMSD (Backbone) → structural stability
• RMSF (Per residue) → residue flexibility
• Radius of Gyration (Rg) → compactness

For the following systems:

• Wild-type (WT)

• Mutants:

  • E787A
  • R788A
  • R791A
  • R788A/R791A

Each analysis contains two independent replicates.

---

🔹 RMS Correlation Analysis

Located in: data/rmscorr/

• Residue-wise correlation matrices
• .agr files (Grace format)
• Pre-rendered .tiff visualizations

---

🔹 Trajectories

Located in: data/traj/

Contains MD trajectories for:

• WT (bound)

• WT_unbound (unbound)

• Mutants:

  • E787A
  • R788A
  • R791A
  • R788A_R791A

---

🛠️ Software & Tools

• GROMACS 2023 – Molecular dynamics simulations
• VMD 1.9.3 – Visualization
• MDTraj 1.9.8 – Trajectory analysis
• AmberTools 2023 – Binding Affinity Calculations
• Barnaba – RNA structural analysis

---

▶️ Usage

🔹 Run Analysis

All analysis workflows are available in:

scripts/basic_analyses_md.ipynb

You can:

• Reproduce RMSD, RMSF, Rg plots
• Compare WT vs mutants
• Analyze structural correlations

---

📈 Outputs

Generated plots include:

• RMSD_all_plots.png
• RMSF_all_plots.png
• RG_all_plots.png
• Correlation heatmaps (.tiff)

---

🔬 Key Features of the Study

• Comparative analysis of WT vs mutants
• Identification of conformational changes
• Insights into RNA recognition mechanisms
• Replicate-based validation for robustness

---

📌 Reproducibility

• All datasets and scripts are included
• Analyses can be reproduced using the provided notebook
• Compatible with Python (Jupyter) workflows

---

📖 Reference

Shri Kant, Atanu Maity, Mashu Ratnakar Bhagat, Savan Masipeddi, and Ranjit Prasad Bahadur (2026). Decoding Mutually Induced Conformational Changes in Non-Canonical Recognition of U1 SL4 snRNA by ULD of SF3A1 during Early Spliceosome Assembly.

---

📦 Citation (Zenodo)

If you use this dataset, please cite:

Kant, S. et al. (2026). Molecular Dynamics Simulation Study of SF3A1–snRNA Interaction. Zenodo.

📬 Contact

For queries or collaborations, please contact: Shri Kant