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Psychedelic Drug Database

Psychotropic and psychedelics drugs database with molecular descriptors

By Juan Jose [source]

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About this dataset

This dataset is a comprehensive database of psychotropic and psychedelic drugs, focusing on their molecular descriptors. The data was sourced from the PubChem Database, which is a widely-used resource for chemical information. The main objective of this project is to create an easily accessible and centralized database specifically for psychedelic compounds.

To achieve this, the dataset includes information on identified psychedelic compounds obtained from the PubChem Database. Additionally, molecular descriptors for these compounds were generated using the KNIME Analytics Platform and RDKit module. These molecular descriptors provide important characteristics and properties of each compound, making it easier to perform quantitative structure-activity relationship (QSAR) and quantitative structure-property relationship (QSPR) analyses.

By providing access to such data, researchers and scientists can have a valuable resource for studying psychoactive substances in a more efficient manner. This database offers consolidated and accurate information about various psychotropic drugs, aiding in research related to their effects, mechanisms of action, toxicity profiles, and potential therapeutic uses.

External resources used in this project include the PubChem Project website as well as the KNIME Analytics Platform and RDKit software tools. With these resources combined, this dataset serves as a dependable repository for both basic research purposes as well as applications in drug design or development efforts targeting psychoactive substances.

The columns within this dataset provide detailed information about each compound's molecular descriptors derived from its chemical structure. This diverse set of characteristics enables researchers to compare different compounds based on their structural features or predict certain properties using computational models.

Overall, this comprehensive psychotropic and psychedelics drugs database plays a crucial role in advancing understanding of these substances' pharmacological activities while facilitating more efficient drug discovery processes through predictive modeling approaches like QSAR/QSPR analysis

How to use the dataset

Understanding the Columns

• Compound Name: The name or identifier of each compound in the database.
• Molecular Formula: The chemical formula representing the number and types of atoms in a compound.
• Molecular Weight: The mass of a molecule, calculated as the sum of atomic weights.
• Canonical SMILES: A simplified molecular representation using standardised notation for atoms and bonds.
• Isomeric SMILES: A more specific molecular representation that includes information about stereochemistry (the spatial arrangement of atoms).
  6-10. Additional columns may be included with specific molecular descriptors depending on how they were generated.

Accessing Additional Information

To delve deeper into any given compound in this database, make use of external resources such as The PubChem Project. This comprehensive resource provides additional data on each compound including chemical properties, biological activities, safety information, and much more.

Performing QSAR or QSPR Analysis

One potential application for this dataset is Quantitative Structure-Activity Relationship (QSAR) or Quantitative Structure-Property Relationship (QSPR) analysis. These approaches involve studying the relationship between a set of chemical properties (molecular descriptors) and an observed activity/property value for a set of compounds.

To perform QSAR/QSPR analysis using this dataset:

• Import these data into your preferred analytics platform such as KNIME Analytics Platform.
• Use the molecular descriptors provided in the dataset as independent variables.
• Obtain an activity/property dataset as your dependent variable (e.g., biological activity, toxicity, physical property).
• Apply appropriate machine learning or statistical modeling techniques to build a model that predicts the activity/property based on the molecular descriptors.
• Evaluate and validate your model using suitable methods (e.g., cross-validation, external test set).

Precautions and Ethical Considerations

While this database provides valuable information for research purposes, it is essential to handle psychedelic substances with caution and adhere to legal and ethical considerations.

• Legal Compliance: Ensure that

Research Ideas

• Research and analysis: Researchers or scientists can use this dataset to study the molecular descriptors of psychotropic and psychedelics drugs. They can explore different properties of these compounds and analyze their structural characteristics that may contribute to their effects on the brain.
• Drug discovery: Pharmaceutical companies or drug discovery researchers can utilize this dataset to identify potential new compounds for the development of psychotropic or psychedelic drugs. By analyzing the molecular descriptors, they can look for similarities with known drugs and evaluate the potential efficacy or safety profiles of novel compounds.
• Education: This dataset can be used in educational settings, such as universities or workshops, to teach students about molecular descriptors and their importance in drug design. Students can learn how these descriptors are calculated and how they relate to drug activity, providing a practical application of chemistry concepts in a real-world context

Acknowledgements

If you use this dataset in your research, please credit the original authors.
Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

Acknowledgements

If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit Juan Jose.