QSAR models: Chemical Informatics


QSAR models:  Chemical Informatics


Chemical Informatics is Insight medical publisher  journal and also one of the most emerging fields in the present scenario. It is a multidisciplinary field which covers the research containing molecular design tools for finding the best fitting compounds which address to particular targets.

Chemical Informatics is a vast field that aims to disseminate information regarding the design, structures, creation, dissemination, visualization and the use of chemical information. Chemical Informatics Journal aims to supply scientists of resources in order to provide the scientific knowledge through the publication of peer-reviewed, high quality, scientific papers and other material on all topics related to Chemical information, Software and databases.

QSAR models

Structure-activity relationship (SAR) and quantitative structure-activity relationship (QSAR) models - collectively referred to as (Q)SARs - are mathematical models that can be used to predict the physicochemical, biological and environmental fate properties of compounds from the knowledge of their chemical structure. These models are available for free or as commercial softwares.

The use of (Q)SARs has deliver reliable information that is comparable to and sufficient to fulfil the information requirements. The (Q)SAR has to be scientifically validated and your substance has to fall within the applicability domain of the model. As with any other form of data, you need to provide sufficient documentation to allow for an independent evaluation of the results.


  • Use (Q)SARs for physicochemical properties and for some environmental toxicity and fate properties. Currently (Q)SARs are not suitable for complex toxicological properties, as they are not fit for purpose for classification and labelling or risk assessment.
  • Document your (Q)SARs thoroughly in your registration dossier using the standardised formats in IUCLID.
  • It is recommended to use classification models (predicting yes/no answers) for properties where the test result can be expressed as such.
  • Consider using additional parameters and link potential interactions between them. (Q)SARs may be coupled with other data and used in a weight of evidence approach.
  • Create one study record for each chemical structure subject to a (Q)SAR prediction.


Article submissions should be done using the online Editor Tracking System or through E-mail IDs provided at the respective journal’s site.

Submit manuscript to http://www.imedpub.com/submissions/chemical-informatics.html or as an E-mail attachment to our editorial office at chemicalinformatics@chemistryjournals.org



Journal Manager

Whatsup: +44-20-3608-4181
Chemical Informatics-Open Access