The central axiom of science purports the explanation of every natural phenomenon using all possible logics coming from pure
as well as mixed scientific background. The quantitative structure-activity relationship (QSAR) analysis is a study correlating the behavioral
manifestation of compounds with their structures employing the interdisciplinary knowledge of chemistry, mathematics, biology as
well as physics. Several studies have attempted to mathematically correlate the chemistry and property (physicochemical/
biological/toxicological) of molecules using various computationally or experimentally derived quantitative parameters termed as descriptors.
The dimensionality of the descriptors depends on the type of algorithm employed and defines the nature of QSAR analysis. The
most interesting feature of predictive QSAR models is that the behavior of any new or even hypothesized molecule can be predicted by
the use of the mathematical equations. The phrase “2D-QSAR” signifies development of QSAR models using 2D-descriptors. Such predictor
variables are the most widely practised ones because of their simple and direct mathematical algorithmic nature involving no time
consuming energy computations and having reproducible operability. 2D-descriptors have a deluge of contributions in extracting chemical
attributes and they are also capable of representing the 3D molecular features to some extent; although in no case they should be considered
as the ultimate one, since they often suffer from the problems of intercorrelation, insufficient chemical information as well as lack
of interpretation. However, by following rational approaches, novel 2D-descriptors may be developed to obviate various existing problems
giving potential 2D-QSAR equations, thereby solving the innumerable chemical mysteries still unexplored.
Keywords: QSAR, QSPR, QSTR, topological descriptors, graph theory, physicochemical property.
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