PCA/K-Means Clustering and Analysis of Molecular Dynamics Simulation of TLR4/MD-2 Complex with β-Sesquiphellandrene

Abstract

This repository contains the source code and computational model supporting the findings of our study: "Aframomum melegueta Attenuates LPS-Induced Neuroinflammation and Memory Impairment through Synergistic TLR4/MD-2 Conformational Locking by β-Sesquiphellandrene and its Natural Phytochemical Matrix" Contents: Molecular Dynamics Simulation Jupyter Notebook: Notebook containing full code for simulation, processed trajectories for RMSD, RMSF, Binding Energy, Principal Component Analysis (PCA), and K-Means Clustering (unsupervised machine learning). Reproducibility: Self-contained environments to reproduce the Figures in the Results section. Usage: Please refer to README.md for instructions and the option to view code via Google Colab. Citation: If you use this code, please cite both the code DOI and the associated publication: Code: Oladele, T. S., Iteire, K. A., Ogunmiluyi, O. E., Adebisi, K. A., Siyanbade, A. J., Sulaiman, K. A., Leko, B. J., & Ijomone, O. M. (2026). PCA/K-Means Clustering and Analysis of Molecular Dynamics Simulation of TLR4/MD-2 Complex with β-Sesquiphellandrene (v1.1.0). Zenodo. https://doi.org/10.5281/zenodo.22286036