The quantitative structure-activity relationship (QSAR) models describe the relationship between molecular structure and a certain biological activity of the molecule. The basic assumption is that the molecular structure of a compound contains information that determines its physical, chemical, and biological properties, and these physical and chemical properties further determine the biological activity of the compound. Furthermore, the molecular structure property data of the compound and its biological activity should also be related to some extent.
Figure 1. QSAR modeling.
2D-QSAR method is a drug design method that uses the overall structural properties of the molecule as a parameter to perform regression analysis on the physiological activity of the molecule to establish a model of the relationship between the chemical structure and the physiological activity. Commonly used two-dimensional QSAR models include hansch method, free-wilson method, molecular connection method, etc. The most famous and widely used method is the hansch method.
The research on two-dimensional QSAR focuses on two directions: the improvement of structural data and the optimization of statistical methods.
The structure data used in the traditional two-dimensional quantitative structure-activity relationship can often only reflect the properties of the whole molecule. By improving the structural parameters, the two-dimensional structure parameter becomes a development direction of the two-dimensional quantitative structure-activity relationship.
Introducing new statistical methods, such as genetic algorithms, artificial neural networks, partial least square regression, etc. and improving the predictive ability of QSAR models are the main development direction of 2D-QSAR.
|Project name||2D-QSAR Service|
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|Deliverables||We provide you with raw data and analysis service.|
CD ComputaBio' 2D-QSAR service can significantly reduce the cost and labor of subsequent experiments. 2D-QSAR service is a personalized and customized innovative scientific research service. Each project needs to be evaluated before the corresponding analysis plan and price can be determined. If you want to know more service prices or technical details, please feel free to contact us.
A: 2D-QSAR is a drug design approach that utilizes the overall structural properties of the molecule as parameters. It is applied to perform regression analysis on the physiological activity of the molecule, and establish a model of the correlation between chemical structure and physiological activity. 2D-QSAR models are used routinely during the process of optimization of a chemical series towards a candidate for clinical trials. The research on two-dimensional QSAR focuses on two directions: the improvement of structural data and the optimization of statistical methods. Commonly applied 2D-QSAR methods include the hansch method, free-wilson method, molecular connection method, etc.
A: Descriptors are numerical representations of the chemical characteristics of a molecule, the main considerations for its selection are as follows:
1) Using as few descriptors as possible to increase the interpretation of model results.
2) Reducing noisy and redundant molecular descriptors to reduce the risk of over-fitting.
3) Providing faster and cost effective models whenever possible. By reducing the dimensionality of the input space, but not losing any important information. Molecular descriptors, on the other hand, have been one of the most important features in QSAR/QSPR modeling, and the information encoded by the descriptors usually depends on the type of molecular representation and the defined computational algorithm. This includes: topological, geometric descriptors, etc.
A: Our analysis steps include the following five steps:
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A: Parameters used to describe the physicochemical characteristics of a substance, such as the lipophilicity, solubility and permeability of a compound. These properties of drugs can improve their efficacy and increase the clinical and market value of products; therefore, studying these properties of drugs not only supports safety, but also contributes significantly to the drug discovery process of candidate compounds.