Supplementary Data for the Paper 'Moltiverse: Molecular Conformer Generation Using Enhanced Sampling Methods'
Year: 2024
Type: supplementary-materials
Abstract: The Moltiverse code is hosted on GitHub at: https://github.com/ucm-lbqc/moltiverseDataset Structure:1. Cofactorv1 Dataset (cofactor_v1_dataset/). This folder contains two types of subfolders for each cofactor:*_original/: Raw files extracted directly from PDB files*_rearranged_atoms/: Files processed by RDKit and chem.cr for homogeneous atom arrangement to facilitate RMSD calculations. The cofactorv1 dataset contains 8412 experimental structures extracted from the PDB.2. Input scripts (input_scripts). This folder contains essential scripts for: performance benchmarking, time measurement analysis and SMI file processing. Replace the variables accordingly.3. Time performance (time_performance). This folder contains tools and results for performance evaluation.4. Analysis Data (moltiverse_c1_data/). Contains raw data, analysis notebooks, and statistical results.Raw data files: energy, rdgyr, rmsd_matrix, rmsd_minAnalysis notebooks: ipynb notebooksstatistics_r/: Processed data and statistical analysis subfoldersAnalysis WorkflowStep 1: Data Export and Initial AnalysisA1_export_data_to_statistics_r.ipynbA2_plots_data_and_analysis.ipynbStep 2: Statistical ProcessingRun R Markdown scripts (.Rmd) in sequence from folders 01 through 08 in statistics_r/Step 3: Visualization and PlottingB1_plots_statistics_matrix.ipynbB2_plots_linear.ipynbB3_plots_spider.ipynbStep 4: Statistics by Replica AnalysisRun C1_plots_statistics_matrix_per_replica.ipynb in the 08_statistics_by_replica/ folder.Larger files with analysis results are distributed in three ZIP archives for easy handling. Each archive contains specific sets of analyses:moltiverse_c1_data_A.zipmoltiverse_c1_data_B.zipmoltiverse_c1_data_C.zipNotes: All paths are relative to the repository root. Execute notebooks and scripts in the specified order to ensure proper data flow. Ensure all dependencies are installed before running the analysis pipeline.Attribution and License InformationThis project includes and modifies code from:"High-Quality Conformer Generation with CONFORGE: Algorithm and Performance Assessment" Thomas Seidel, Christian Permann, Oliver Wieder, Stefan M. Kohlbacher, and Thierry Langer; Journal of Chemical Information and Modeling. 2023 63 (17), 5549-5570DOI: 10.1021/acs.jcim.3c00563 SUPPLEMENTARY DATA - DOI: 10.5281/zenodo.8137603Original Authors: Seidel, Thomas, Permann, Christian, Wieder, Oliver, Kohlbacher, Stefan Michael, Langer, ThierryOriginal Release Date: 2023Modifications: Some scripts (input_scripts) have been modified from their original versions by Mauricio Bedoya.Modifications include: Code reformatting, and restructured execution workflow to reduce dependency on auxiliary bash scripts.Modified files are marked with appropriate headers indicating license attribution.License InformationOriginal License: GPLv2Current License: GPLv2Date of License Update: 2024Proper CitationIf you use these scripts, please cite:"High-Quality Conformer Generation with CONFORGE: Algorithm and Performance Assessment" Thomas Seidel, Christian Permann, Oliver Wieder, Stefan M. Kohlbacher, and Thierry Langer; Journal of Chemical Information and Modeling. 2023 63 (17), 5549-5570DOI: 10.1021/acs.jcim.3c00563 Seidel, T., Permann, C., Wieder, O., Kohlbacher, S. M., & Langer, T. (2023). Supplementary Data for the Paper 'High-Quality Conformer Generation with CONFORGE: Algorithm and Performance Assessment'. https://doi.org/10.5281/zenodo.8137603 Also cite this current repository and Moltiverse work (Check citation section at GitHub): https://github.com/ucm-lbqc/moltiverse
Source: Figshare
Authors: Bedoya, Mauricio, Adasme Carreño, Francisco, Peña-Martínez, Paula Andrea, Muñoz-Gutiérrez, Camila, Peña-Tejo, Luciano, Márquez-Montesinos, José C. E., Hernández-Rodríguez, Erix W., González, Wendy, Martinez, Leandro, Alzate-Morales, Jans
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6977839895
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