Bioinformatics Structure Analysis

Structure-Activity Relationship (SAR)

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The structure–activity relationship (SAR) is the relationship between the chemical structure of a molecule and its biological activity. This idea was first presented by Crum-Brown and Fraser in 1865. The analysis of SAR enables the identification of the chemical group responsible for evoking a target biological effect in the organism. This allows modification of the effect or the potency of a bioactive compound (typically a drug) by changing its chemical structure. Medicinal chemists use the techniques of chemical synthesis to insert new chemical groups into the biomedical compound and test the modifications for their biological effects.

The structure-activity relationship (SAR) helps in understanding many aspects of drug discovery, from screening drug candidates to optimizing their properties. The effective biological activity is contributed by the certain geometric and electrostatic interactions.

The field of drug design now includes concise methods to determine SAR. This is because the geometric and electrostatic interactions involve three-dimensional space of a target site and its ligand.  Many of these interactions cannot be numerically characterized.

Understanding the interaction between a ligand and a target active site often requires abundant information and this is where SAR comes in. SAR can be used to explain various ways a ligand interacts with a receptor and can be used to optimize the ligands to develop specific and potent bioactive drugs.

Working with SAR includes identifying if a structural activity relationship exists among a collection of molecules, and whether the details of one or more SAR can be uncovered. Most optimization projects try to improve drug potency, reduce the toxicity, increase the bioavailability, etc.

There are mainly two methods that are used to capture and quantify SAR;

  • Statistical or data mining method
  • Pharmacophore models

The choice of quantitative SAR methods can determine the detail to which a SAR can be explored.

Statistical QSARs that are based on two-dimensional descriptors often miss elements of stereochemistry that are based on the chirality of the molecule. Thus, QSARs that are based on three-dimensional approaches provide more information and we can recognize ligand-receptor interactions in greater detail.

SAR depends on the recognition of which structural characteristics correlate with chemical and biological reactivity. Thus the ability to draw conclusions about an unknown compound depends upon both the structural features that can be characterized as well as the database of molecules against which they are compared. When combined with appropriate professional judgment, SAR can be a powerful tool to understanding functional implications when similarities are found. 

The large number of synthetic organic chemicals currently in production presents a huge challenge for timely collection of detailed environmental data on each compound. The concept of structure biodegradability relationships (SBR) has been applied to explain variability in persistence among organic chemicals in the environment. Early attempts generally consisted of examining the degradation of a homologous series of structurally related compounds under identical conditions with a complex “universal” inoculum, typically derived from numerous sources. This approach showed that the nature and positions of substituents affected the apparent biodegradability of many chemical classes, with resulting general themes, such as halogens generally conferring persistence under aerobic conditions. As a result, more quantitative approaches have been developed using principles of QSAR and often accounting for the role of sorption (bioavailability) in chemical fate. 

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