Documentation

Introduction

The repository, CannabinoidDB provides an overview of 5,652 CB1 molecules and 4,875 CB2 molecules. Further the molecules are classified into agonists, antagonists, inverse agonists and partial agonists. The interface is straightforward, easy-to-use and intuitive, allowing users to browse and search the database with ease.
CannabinoidDB has a simple and user-friendly interface for querying and browsing molecules. Visualizations of all the molecules in the receptor’s binding site are provided to understand relevant interactions. CannabinoidDB allows the user to interactively browse through the pages to access corresponding molecules and subsequently obtain details of the molecules along with their interaction details.

The following documentation provides users, the information on browsing and navigating through the CannabinoidDB website easily and get the information they need, quickly.

List of Contents:

  1. About the Database
  2. Search and Browse
  3. Functions and Tools
  4. References and Citations

About CannabinoidDB

Cannabinoid receptors 1 (CB1) and Cannabinoid receptors 2 (CB2) are the two types of receptors that are part of the endocannabinoid system. CB1 receptors are primarily found in the central nervous system, while CB2 receptors are present in the peripheral nervous system, immune system etc. The activation of cannabinoid receptors can have diverse effects like pain modulation, neuroprotection, immune regulation, appetite, metabolism as well as mood regulation. This potential of cannabinoid receptors to produce various physiological and psychoactive effects raised great interest in cannabinoid research around the world. Cannabinoids are compounds that interact with the endocannabinoid system and produce various effects on the body. Over the years, many cannabinoid databases have been developed. However, currently there is no online resource grouping all the known cannabinoid molecules at one place. Therefore, we developed CannabinoidDB that is a comprehensive database containing information about various endocannabinoids, phytocannabinoids as well as other synthetic cannabinoids that bind to these receptors. Further, we have provided information about various physiological and pharmacokinetic properties of these cannabinoids. The CannabinoidDB is an open access web server that is designed to be user-friendly with easy-to-understand information about each molecule. Users can search for specific cannabinoid-receptor targeting molecules and view their chemical structures, physicochemical and ADMET properties along with their interactions with the CB1 and CB2 proteins. The data analysis module presented in the database includes descriptor calculation and scaffold analysis using powerful tools that can be used to analyze molecules in different ways. Furthermore, CannabinoidDB is an essential resource for researchers, healthcare professionals and anyone interested in exploring the importance of the endocannabinoid system. By providing a centralized location for information on different molecules, CannabinoidDB can help to advance our understanding of these compounds and their potential applications in medicine. This will greatly simplify cannabinoid research by allowing virtual screening of all the compounds and their other in-silico applications.

You can find more information on CannabinoidDB by clicking on Read More button of the About Section of the Homepage of the website.

Basic Search

In the Small Molecules section of the Homepage, click on the type of small molecules you want to browse for, be it - Agonists of CB1, Antagonists of CB1, Agonists of CB2, Antagonists of CB2, Partial Agonists of CB1, Partial Agonists of CB2, Inverse Agonists of CB1 and Inverse Agonists of CB2.

After going into the respective database of your chosen molecules, use the SEARCH bar above to search for any specific ZINC IDs/ SMILES/Molecular Weight.


To have more information about the molecule from the ZINC database, click on the clickable ZINC ID link.


Interactions

The receptor and ligand molecules have been docked using the Glide* module of Maestro interface in Schrodinger software (see citations below). To look into the interactions of that particular molecule with the chosen receptor, click on View option under Interactions column for that particular molecule OR You can directly access the Interactions Tool in the Functions section of the Homepage.

To view the interactions of the molecule with the chosen receptor in the Mol* plugin window, click on the ligand molecule directly.

Details

To look into the general properties, physiochemical and pharmacokinetic properties, ADMETLab*, ADMETSAR* and SwissADME*(see citations below) properties of the respective molecule, click on View option under Details column for that particular molecule OR You can directly access the Search Tool in the Functions section of the Homepage.



Functions and Tools

The receptor and ligand molecules have been docked using the Glide* module of Maestro interface in Schrodinger software (see citations below). To view the interactions of a particular molecule with the chosen receptor, click on Learn More button of Interactions Tool in Functions section of the Homepage.


Interactions

Choose your required ligand molecule's ZINC ID/SMILES from the database and the respective receptor. The interactions are displayed in a standard PDBe Molstar (Mol*) Plugin window equipped with the basic standard options.


If you encounter any problem during the visualization of the interactions of the ligand molecule with the receptor, click on the ? button on the left side of plugin window to help you guide through the interface.

Receptors

To know more about the receptors and the various related research articles, you can access this tool by clicking on the Learn More button of the Receptor Tool in the Functions section of the Homepage.

Search Details Tool

To know more about the general, physiochemical, pharmacokinetic, ADMETLab*, ADMETSAR* and SwissADME*(see citations below) properties of the molecules, choose the respective molecules and the receptor by clicking on the Learn More button of the Search Tool in the Functions section of the Homepage.


Advanced Search Tool

Use this tool to narrow down and refine your search results. To find a specific ligand molecule, enter its property/properties (in range) as asked by the tool (Molecular Formula, Molecular Weight, Number of Heavy Atoms and AlogP values). The tool gives you results even if you enter values for a single property (eg. Molecular Weight).


The results can be seen in the following format, categorized into CB1 and CB2 receptor hits.


References And Citations

  • Glide:
    1. Yang, Y; Yao, K; Repasky, M.P.; Leswing, K; Abel, R; Shoichet, B.K.; Jerome, S.V., Efficient Exploration of Chemical Space with Docking and Deep Learning. J. Chem. Theory Comput. 2021, 17, 11, 7106–7119
    2. Friesner, R. A.; Murphy, R. B.; Repasky, M. P.; Frye, L. L.; Greenwood, J. R.; Halgren,T. A.; Sanschagrin, P. C.; Mainz, D. T., “Extra Precision Glide: Docking and Scoring Incorporating a Model of Hydrophobic Enclosure for Protein-Ligand Complexes,” J. Med. Chem., 2006, 49, 6177–6196
    3. Halgren, T. A.; Murphy, R. B.; Friesner, R. A.; Beard, H. S.; Frye, L. L.; Pollard, W. T.; Banks, J. L., “Glide: A New Approach for Rapid, Accurate Docking and Scoring. 2. Enrichment Factors in Database Screening,” J. Med. Chem., 2004, 47, 1750–1759
    4. Friesner, R. A.; Banks, J. L.; Murphy, R. B.; Halgren, T. A.; Klicic, J. J.; Mainz, D. T.; Repasky, M. P.; Knoll, E. H.; Shaw, D. E.; Shelley, M.; Perry, J. K.; Francis, P.; Shenkin, P. S., “Glide: A New Approach for Rapid, Accurate Docking and Scoring. 1. Method and Assessment of Docking Accuracy,” J. Med. Chem., 2004, 47, 1739–1749
  • ADMETLab:
    1. Dong, J., Wang, NN., Yao, ZJ. et al. ADMETlab: a platform for systematic ADMET evaluation based on a comprehensively collected ADMET database. J Cheminform 10, 29 (2018).
  • ADMETSAR:
    1. Hongbin Yang, Chaofeng Lou, Lixia Sun, Jie Li, Yingchun Cai, Zhuang Wang, Weihua Li, Guixia Liu, Yun Tang. admetSAR 2.0: web-service for prediction and optimization of chemical ADMET properties. Bioinformatics, 2018, bty707.
    2. Feixiong Cheng, Weihua Li, Yadi Zhou, Jie Shen, Zengrui Wu, Guixia Liu, Philip W. Lee, Yun Tang. admetSAR: a comprehensive source and free tool for evaluating chemical ADMET properties. J. Chem. Inf. Model., 2012, 52(11): 3099-3105.
  • SwissADME:
    1. A. Daina, O. Michielin, V. Zoete. SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci. Rep. 2017; 7:42717.
  • ZINC:
    1. Irwin, Tang, Young, Dandarchuluun, Wong, Khurelbaatar, Moroz, Mayfield, Sayle, J. Chem. Inf. Model 2020
    2. Sterling and Irwin, J. Chem. Inf. Model, 2015 http://pubs.acs.org/doi/abs/10.1021/acs.jcim.5b00559. Irwin, Sterling, Mysinger, Bolstad and Coleman, J. Chem. Inf. Model, 2012