Computational structure–activity study directs synthesis of novel antitumor enkephalin analogs

Abstract

The capability of a Support Vector Machines QSAR model to predict the antiproliferative ability of small peptides was evaluated by screening a virtual library of enkephalin-like analogs modified by incorporation of the (R,S)-(1-adamantyl)glycine (Aaa) residue. From an initial set of 390 compounds, the peptides, Tyr-Aaa-Gly-Phe-Met (2), Tyr-Aaa-Gly-Phe-Phe (3), Phe-Aaa-Gly-Phe-Phe (4) and Phe-Aaa-Gly-Phe-Met (5) were selected, synthesized and their antitumor activity was tested and compared to that of Met-enkephalin (1). The antiproliferative activity correlated with the computational prediction and with the foldamer-forming ability of the studied peptides. The most active compounds were the hydrophobic peptides, Phe-Aaa-Gly-Phe-Phe (4) and Phe-Aaa-Gly-Phe-Met (5), having a greater propensity to adopt folded structures than the other peptides.