Structure-Activity-Relationship study (SAR)

Circle Oncodesign Services

Unlocking the power of SAR studies in chemistry and drug development with a CRO partner

 

What is a SAR study?

Structure-activity relationship (SAR) investigates the relationship between the chemical structure of a molecule and its biological activity. It is a fundamental principle in drug discovery, as it allows scientists to understand how changes in a molecule structure can affect its ability to interact with a target and elicit a desired biological response.

SAR studies typically involve the synthesis and testing of a series of compounds that are structurally related to a known active compound. The biological activity of each compound is measured, and the results are analyzed to identify structural features that are associated with increased or decreased activity. This information can then be used to design new compounds with improved biological properties.

SAR studies are an essential part of the drug discovery process. They help scientists to identify promising lead compounds (hit to lead), optimize their structure (lead optimization) for improved activity and selectivity, and identify potential safety concerns. SAR data can also be used to develop computational models that can predict the biological activity of new compounds, which can help to accelerate the drug discovery process.

SAR study methodology

Medicinal chemists employ a variety of techniques to study the structure-activity relationship (SAR) of compounds. These techniques can be classified into two categories: experimental and computational methods.

Experimental SAR studies involve the synthesis and testing of a series of compounds that are structurally related to a known active compound. The biological activity of each compound is measured, and the results are analyzed to identify structural features that are associated with increased or decreased activity. This information can then be used to design new compounds with improved biological properties.

Specific experimental SAR techniques include:

  • Biological assays: These assays measure the biological activity of a compound on a target, such as an enzyme, receptor, or cell.
  • Pharmacokinetic studies: These studies measure the absorption, distribution, metabolism, and excretion of a compound in the body.
  • Toxicological studies: These studies assess the safety of a compound by measuring its effects on various organs and systems in the body.

 

Computational SAR methods utilize Machine Learning models to predict the biological activity of new compounds based on their chemical structure. These models are developed using data from experimental SAR studies. The models can then be used to identify promising lead compounds and to optimize their structure for improved activity and selectivity.

Specific computational SAR techniques include:

  • Molecular modeling: These techniques use computer software to build and simulate three-dimensional models of molecules. This information can be used to understand how molecules interact with their biological targets.
  • Quantitative structure-activity relationship (QSAR) modeling: These models use Artificial Intelligence models to relate the chemical structure of a compound to its biological activity.

Oncodesign Services provides SAR services and a state-of-the-art medicinal chemistry platform

Oncodesign Services offers tailored SAR and QSAR model building services to accelerate your drug discovery process. Our team of experts includes computational and medicinal chemists with decades of experience in drug development.

We offer in silico drug design and optimization services spanning the entire process of drug development, including:

 

Here at Oncodesign Services, we use a combination of computational chemistry softwares to evaluate  SARs and QSARs. Our Molecular Operating Environment (MOE) software has been in place for many years and combines Structure-Based Drug Design (SBDD) and Ligand-Based Drug Design (LBDD) approaches efficiently. Our software is further assisted by Konstanz Information Miner (KNIME), which allows automatization and speeds up computational LBDD and SBDD workflows.

If you are interested in learning more on our capabilities, please be in touch!

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