Quantitative Structur Property Relationship

Molecular similarity is a fundamental concept of cheminformatics to predict the Quantitative properties of molecule from the library of molecular structure. This is done through the computional methods in python using rdkit and the molecule likely have the similar biological and physioproperties.

The similar molecular structre is the fundamental concenpt & molecule will tend to show the same physical properties or biological activity.

Example 01 : Hexane and heptane should have similar bioling point and water solublity.

// import MolComponent from "../../components/apps/MolecularStructure/MolComponent.tsx"

Mention second example

Example 02: Cocaine and procaine are both local anesthetics

(Quantitative structure property relationship) QSPR & (Quntitave structure active relationship) QSAR are used as the stastical model to predict the physioproperties. The descriptor are used to get all the chemical information of the compounds (refer the rdkit article).

And Machinelearning (ML) is used to gerenerate the most accurate report of the commpounds. lets say we have dataset of the known compounds then we wiil divide that dataset into Test set & Traning set and after that we will pass that dataset into the ML Algorithm (refer sklearn, it provides ready made algorithm) and it will generate an answer from the model.

If we want to develop a ML model to predict, we need to be able to describe in biological and physical properties.

Information is remaining

from rdkit 

This descriptors provide some clue related to the molecules