The human equilibrative nucleoside transporters (hENTs) are important proteins that allow nucleosides and nucleobases permeation into the cell. hENT 1 is a promising target against heart and Huntington’s diseases as its inhibition mediates cardiac- and neural protection effects, respectively. However, the current hENT1 inhibitors have significant off-target effects and poor pharmacological profile, hence there is need for new novel inhibitors. Therefore, we developed a computational protocol that identified and selected inhibitors of hENT1 in an efficient and specific manner. First, several pharmacophores were created using a set of known inhibitors. Consequently, the best inhibitor pharmacophore exhibited as high selectivity and specificity rates as 92% and 88%, respectively. Furthermore, another pharmacophore was validated for the oppositely acting type of the hENT1 molecules (i.e. permeants) to act as an extra refinement step in our search for hENT1 inhibitors. Interestingly, employing the inhibitor pharmacophore as a filter-in along with the permeant pharmacophore as a filter-out resulted in up to two-fold enhancement of docking-based virtual screening results of hENT1 inhibitors. This in silico approach can prove very useful in the development of new cardio- and neuroprotective hENT1 inhibitors.