Data

Predictive toxinology: calculated molecular descriptors to describe toxicity using Saxitoxins

Australian Institute of Marine Science
Australian Institute of Marine Science (AIMS)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=https://apps.aims.gov.au/metadata/view/52e8f4a0-4000-4650-9372-fd97de9e7725&rft.title=Predictive toxinology: calculated molecular descriptors to describe toxicity using Saxitoxins&rft.identifier=https://apps.aims.gov.au/metadata/view/52e8f4a0-4000-4650-9372-fd97de9e7725&rft.publisher=Australian Institute of Marine Science (AIMS)&rft.description=Saxitoxins (STXs) were used to ascertain whether a combination of calculated molecular descriptors could explain observed biological activity. A dataset of 3050 molecular descriptors was generated for each of 30 Saxitoxins. Removal of descriptors that were the same for all toxins, or because a descriptor could not be calculated for one or more of the toxins, decreased the dataset to 1751 descriptors. To assess the utility of molecular descriptors to describe potency of natural toxins and then to use them to predict likely bioactivity of as yet untested toxins. The dataset of toxicity and molecular descriptors(30 toxins x 1751 descriptors) is available upon request.Molecular descriptors and their mathematical combination have been used for predictive toxicology and risk assessments of environmental pollutants and pharmaceutical leads. This was the first study to use this approach for natural toxins.Maintenance and Update Frequency: asNeededStatement: Statement: Descriptors were generated from SMILES translation of structures using the Virtual Computational Chemistry Laboratory (http://www.vcclab.org/)&rft.creator=Australian Institute of Marine Science (AIMS) &rft.date=2026&rft_rights=Creative Commons Attribution-NonCommercial 3.0 Australia License http://creativecommons.org/licenses/by-nc/3.0/au/&rft_rights=Use Limitation: All AIMS data, products and services are provided as is and AIMS does not warrant their fitness for a particular purpose or non-infringement. While AIMS has made every reasonable effort to ensure high quality of the data, products and services, to the extent permitted by law the data, products and services are provided without any warranties of any kind, either expressed or implied, including without limitation any implied warranties of title, merchantability, and fitness for a particular purpose or non-infringement. AIMS make no representation or warranty that the data, products and services are accurate, complete, reliable or current. To the extent permitted by law, AIMS exclude all liability to any person arising directly or indirectly from the use of the data, products and services.&rft_rights=Attribution: Format for citation of metadata sourced from Australian Institute of Marine Science (AIMS) in a list of reference is as follows: Australian Institute of Marine Science (AIMS). (2009). Predictive toxinology: calculated molecular descriptors to describe toxicity using Saxitoxins. https://apps.aims.gov.au/metadata/view/52e8f4a0-4000-4650-9372-fd97de9e7725, accessed[date-of-access].&rft_rights=Resource Usage:Use of the AIMS data is for not-for-profit applications only. All other users shall seek permission for use by contacting AIMS. Acknowledgements as prescribed must be clearly set out in the user's formal communications or publications.&rft_subject=oceans&rft.type=dataset&rft.language=English Access the data
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Creative Commons Attribution-NonCommercial 3.0 Australia License
http://creativecommons.org/licenses/by-nc/3.0/au/

Use Limitation: All AIMS data, products and services are provided "as is" and AIMS does not warrant their fitness for a particular purpose or non-infringement. While AIMS has made every reasonable effort to ensure high quality of the data, products and services, to the extent permitted by law the data, products and services are provided without any warranties of any kind, either expressed or implied, including without limitation any implied warranties of title, merchantability, and fitness for a particular purpose or non-infringement. AIMS make no representation or warranty that the data, products and services are accurate, complete, reliable or current. To the extent permitted by law, AIMS exclude all liability to any person arising directly or indirectly from the use of the data, products and services.

Attribution: Format for citation of metadata sourced from Australian Institute of Marine Science (AIMS) in a list of reference is as follows: "Australian Institute of Marine Science (AIMS). (2009). Predictive toxinology: calculated molecular descriptors to describe toxicity using Saxitoxins. https://apps.aims.gov.au/metadata/view/52e8f4a0-4000-4650-9372-fd97de9e7725, accessed[date-of-access]".

Resource Usage:Use of the AIMS data is for not-for-profit applications only. All other users shall seek permission for use by contacting AIMS. Acknowledgements as prescribed must be clearly set out in the user's formal communications or publications.

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Saxitoxins (STXs) were used to ascertain whether a combination of calculated molecular descriptors could explain observed biological activity. A dataset of 3050 molecular descriptors was generated for each of 30 Saxitoxins. Removal of descriptors that were the same for all toxins, or because a descriptor could not be calculated for one or more of the toxins, decreased the dataset to 1751 descriptors.
To assess the utility of molecular descriptors to describe potency of natural toxins and then to use them to predict likely bioactivity of as yet untested toxins.
The dataset of toxicity and molecular descriptors(30 toxins x 1751 descriptors) is available upon request.Molecular descriptors and their mathematical combination have been used for predictive toxicology and risk assessments of environmental pollutants and pharmaceutical leads. This was the first study to use this approach for natural toxins.

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Maintenance and Update Frequency: asNeeded
Statement: Statement: Descriptors were generated from SMILES translation of structures using the Virtual Computational Chemistry Laboratory (http://www.vcclab.org/)

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Credit
Llewellyn, Lyndon E, Dr (Principal Investigator)

Modified: 18 09 2026

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Predictive toxinology: an initial foray using calculated molecular descriptors to describe toxicity using saxitoxins as a model: Llewellyn LE (2007) Predictive toxinology: an initial foray using calculated molecular descriptors to describe toxicity using saxitoxins as a model. Toxicon 50:901-913.

local : articleId=7497

Identifiers
  • global : 52e8f4a0-4000-4650-9372-fd97de9e7725
ACN 633 798 857