FARM -BIOMOL chemical library dataset to train a machine learning-based QSAR model for beta-lactamase inhibitors screening

Biological data (enzyme inhibition), Molecular simulation file, Jupyter notebook.

2023

Link: https://github.com/ThanetPi/ML-QSAR-Docking-Proof-of-Concept

DOI: https://doi.org/10.5281/zenodo.13378955

Licence: CC BY-NC-ND (Attribution, NonCommercial, No Derivatives)

Pictures

Dataset picture

Details

Description

This respiratory is used for depositing supplementary and relevant data, including Python code, from the scientific article entitled, "Utilizing machine learning-based QSAR model to overcome standalone consensus docking limitation in beta-lactamase inhibitors screening: a proof-of-concept study."

Publication Date: Aug. 28, 2024

Creators/Owners

Gregor Fuhrmann Lehrstuhl für Pharmazeutische Biologie Jennifer Munkert Lehrstuhl für Pharmazeutische Biologie Thanet Pitakbut Lehrstuhl für Pharmazeutische Biologie

Involved external institutions

Shenzhen Institutes of Advanced Technology (SIAT) CN China (CN)

Debug: Alles

Owner: T. Pitakbut, J. Munkert, G. Fuhrmann
Datum: None
Year: 2023
Beschreibung: This respiratory is used for depositing supplementary and relevant data, including Python code, from the scientific article entitled, "Utilizing machine learning-based QSAR model to overcome standalone consensus docking limitation in beta-lactamase inhibitors screening: a proof-of-concept study."
Subject:
Verf: Public
Publ-Datum: Aug. 28, 2024
Lizenz: 248358946
Lizenz DE: CC BY-NC-ND (Namensnennung, nicht-kommerziell, gleiche Bedingungen, Keine Bearbeitung))
Lizenz Other:
Datentyp: Biological data (enzyme inhibition), Molecular simulation file, Jupyter notebook.
Anderer Datentyp: Biological data (enzyme inhibition), Molecular simulation file, Jupyter notebook.
Beschreibung Zugang:
Groesse: 0
Einheit:
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