A target-based enzyme design is an ultimate goal for the bioengineers as it gives a greener and sustainable approach for synthesis of desired products . This goal is now possible by mutating some key strategic residues of the active site using directed evolution method, which is efficient, but at the same time, is random. Therefore, a comprehensive understanding of the molecular mechanism that confers better activity could improve such design protocols as well as could also guide the development of smarter mutagenesis and screening strategies. But, unlike a protein-drug interactions where the binding information of the drug using lock-key concept could be enough , understanding the molecular mechanism of the enzyme catalysis is somewhat tricky. An enzymatic reaction, according to Warshel, can involve two components : the first component is the entropic contribution to the binding free energy for bringing the reactive fragment into the catalytic site which is equivalent to dissociation constant, and the second fragment is the free energy needed to reach the TS from the reactant geometry and is equivalent to activation energy. Fortunately, modern methods like MD simulations [13, can deal the information related to the first component (binding stability) while hybrid QM/MM calculations can reveal the second component i.e., activation energy . A combination of these two methods, therefore, provides a crucial lead to design more effective and powerful enzyme for modern use. More recently, with ever increased rate, the external electric field (EEF) is being used to harness the catalytic activity of many chemical reactions . In fact, Nature routinely harnesses pre-oriented local-electric fields (LEF) for the electrostatic catalysis observed in enzymes. Therefore, the quantification of electric field in the enzyme system using computational tools could be an add-on to the rational based enzyme designing. In the present study, we show how the quantification of electric field (EF) along the axis of reaction could be used as a descriptor for the enzyme activity.