Cardiovascular diseases (CVDs) have become one of the leading causes of death worldwide, which is associated with several risk factors. One major cause is the elevation in the level of proatherogenic factors such as low-density lipoprotein (LDL) and very low-density lipoprotein (VLDL) that leads to building up of cholesterol plaque in the artery wall, causing atherosclerosis and other CVDs. Scientists have demonstrated that elevated levels of high-density lipoproteins (HDLs) can inversely impact the disease progression. In this aspect, Cholesteryl ester transfer protein (CETP) is an emerging protein target. Inhibition of CETP activity increases the HDL-C that has the potential to reduce CVDs. From the last decade, several small molecules including Torcetrapib, Dalcetrapib, Evacetrapib and Anacetrapib have been investigated thoroughly in clinical trials. Despite the beneficial influence on cholesterol metabolism, off-target effects and lack of reduction in CV events and mortality led to failure of majority of the inhibitors in early phase III trials. Though available crystal structure of substrate- and inhibitor-bound CETP are present, very little is known concerning the mechanism of lipid transfer and how this protein interacts with the lipoproteins. This study aims to provide a detailed investigation on molecular mechanism of lipid transfer and binding pattern of small molecule to the active site, which will help us to give a better understanding of inhibitor binding. Besides, machine learning based QSAR studies will be implemented to build predictive models for identifying important structural fingerprints as contributors towards activity. Subsequently, virtual screening of FDA-approved drugs can help to identify some potential inhibitor molecules, that have better potency in terms of efficacy and negligeable chances in trials failure.