<b>File 4 — Supplementary Manuscript</b><b> </b><b>for DrLungker</b>
<p dir="ltr"><b>Article Title:</b> <i>DrLungker: A Deep Ensemble Learning Framework for Predicting Anti-Lung Cancer Compound Activity and Validating Multitarget Potency through WaterMap, DFT, MD Simulations, and MM-GBSA Analysis</i><br><b>Published in:</b> <i>Advanced Theory and Simulations</i><br><b>Manuscript DOI:</b> <a href="https://doi.org/10.1002/adts.202501550" rel="noopener" target="_new">https://doi.org/10.1002/adts.202501550</a><br><b>More Information:</b> <a href="https://github.com/ShabanAhmad/DrLungker" rel="noopener" target="_new">GitHub Repository</a></p><p><br></p><h3><b>Description</b></h3><p dir="ltr">This supplementary manuscript accompanies the main DrLungker article and provides comprehensive additional information to support the study’s findings. It includes detailed experimental procedures, extended results, and methodological insights not presented in the primary publication. Specifically, the document contains:</p><ul><li><b>Extended Methods:</b> Detailed descriptions of experimental protocols and computational approaches used in the study.</li><li><b>Model Evaluations:</b> Comprehensive assessments of the DrLungker model’s performance.</li><li><b>Molecular Interaction Fingerprints:</b> Analysis of key molecular interactions identified in the study.</li><li><b>Density Functional Theory (DFT) Analyses:</b> Computational characterization of the top molecules.</li><li><b>Molecular Dynamics Simulations:</b> Detailed simulation results, including Root Mean Square Fluctuation (RMSF) analyses and Simulation Interaction Diagrams.</li></ul><p dir="ltr">This supplementary material is intended to provide additional transparency, reproducibility, and depth for researchers interested in the computational and experimental aspects of the DrLungker study.</p>
