Moldrug algorithm for an automated ligand binding site exploration by 3D aware molecular enumerations (SI)

Supporting informaiton for the paper Moldrug algorithm for an automated ligand binding site exploration by 3D aware molecular enumerations Here are uploaded all files, instructions and data to reproduce the results (including images and analysis) of the paper. Installation of the environment conda create -n moldrug-paper python="3.9" ipykernel ipython ipywidgets -y conda activate moldrug-paper pip install moldrug pip install -r https://raw.githubusercontent.com/ale94mleon/moldrug/refs/heads/main/streamlit/requirements.txt Extra requirements pip install pdb2pqr pip install git+https://github.com/PatWalters/rd_filters.git To follow the Notebooks in ./ref-crystals you need to install ADFRsuite. So you can use the script prepare_receptor. Repo structure 6lu7: It has both moldrug campaigns: configuration files and results. figures-and-analysis: All the IPython-Notebooks to reproduce the images and analysis full-data: A CSV (separated by ";") with all the data for the final population of generations 20; 45; 85; 100 (final populaiton of each stage). mappers: JSON files with that map names internally used and moldrug IDX.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-26
DOI
https://doi.org/10.5281/zenodo.15090830
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Moldrug algorithm for an automated ligand binding site exploration by 3D aware molecular enumerations (SI)

Zenodo (CERN European Organization for Nuclear Research)
Computational Drug Discovery Methods
article

Moldrug algorithm for an automated ligand binding site exploration by 3D aware molecular enumerations (SI)

article en

Abstract

Supporting informaiton for the paper Moldrug algorithm for an automated ligand binding site exploration by 3D aware molecular enumerations Here are uploaded all files, instructions and data to reproduce the results (including images and analysis) of the paper. Installation of the environment conda create -n moldrug-paper python="3.9" ipykernel ipython ipywidgets -y conda activate moldrug-paper pip install moldrug pip install -r https://raw.githubusercontent.com/ale94mleon/moldrug/refs/heads/main/streamlit/requirements.txt Extra requirements pip install pdb2pqr pip install git+https://github.com/PatWalters/rd_filters.git To follow the Notebooks in ./ref-crystals you need to install ADFRsuite. So you can use the script prepare_receptor. Repo structure 6lu7: It has both moldrug campaigns: configuration files and results. figures-and-analysis: All the IPython-Notebooks to reproduce the images and analysis full-data: A CSV (separated by ";") with all the data for the final population of generations 20; 45; 85; 100 (final populaiton of each stage). mappers: JSON files with that map names internally used and moldrug IDX.

Zenodo (CERN European Organization for Nuclear Research)
Boehringer Ingelheim (Germany) (DE), Open Geospatial Consortium (GB), Saarland University (DE)
Openalex Percentile: Top 52%
Computational Drug Discovery Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Moldrug algorithm for an automated ligand binding site exploration by 3D aware molecular enumerations (SI) · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS