Computational chemistry represents molecular structures as a numerical models and simulates their behavior with the equations of quantum and classical physics. Available programs enable scientists to easily generate and present molecular data including geometries, energies and associated properties (electronic, spectroscopic and bulk). The usual paradigm for displaying and manipulating these data is a table in which compounds are defined by individual rows and molecular properties (or descriptors) are defined by the associated columns. A QSAR attempts to find consistent relationships between the variations in the values of molecular properties and the biological activity for a series of compounds so that these "rules" can be used to evaluate new chemical entities.
A QSAR generally takes the form of a linear equation
Biological Activity = Constant + (C1 P1) + (C2 P2) + (C3 P3) + ...
where the parameters P1 through Pn are computed for each molecule in the series and the coefficients C1 through Cn are calculated by fitting variations in the parameters and the biological activity. Since these relationships are generally discovered through the application of advanced statistical techniques which might be very difficult to implement manually, so a tool that would do all this calculation and would be available freely would higly contribute to the field. I would not give a list of available tools available but would rather introduce you to a tool which has been developed by me. The main motivation behind developing the tool is to enable inexperienced users to get into the field and take up the work without any big pain to go through long tutorials.EasyQSAR has a very friendly GUI that guides through every step and gives valuable tips to analyze the data. But one thing that should be remembered is that the tool only makes the analysis when you provide the data about the descriptors and activity. It does not generates the descriptors itself.
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Kuntal Kumar Bhusan
University of HyderabadIndia