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Soft spot analysis helps evaluate the site of the metabolic lability that impacts the bio-availability of the drug. However, given its laborious and time consuming experimentation, we propose a reliable and cheap in silico strategy. In this context, we hypothesized a mechanistic rationale for metabolism of erlotinib by the CYP3A4 enzyme. The comparison of the 3D conformations of the target CYP class of enzymes using MD simulations with GROMACS helped evaluate its impact on the metabolism. The molecular docking studies using Autodock-Vina ascertained the explicit role of the Fe ion present in the Heme moiety in this process. This mechanism was confirmed with respect to 13 other popular approved FDA kinase inhibitors using ab initio DFT calculations using Gaussian 09 (G09), molecular docking studies with Autodock-Vina, and MD simulations with GROMACS. We then developed a quantitative (Q-Met) metabolic profile of these soft spots in the molecules and demonstrated the lack of a linear relationship between the extent of metabolism and drug efficacy. We thus propose an economic in silico strategy for the early prediction of the lability in kinase inhibitors to help model their bio-availability and activity simultaneously, prior to clinical testing. [ABSTRACT FROM AUTHOR]