Background: Since caspases are key executioners of apoptosis in cases of severe diseases including neurodegenerative disorders such as Alzheimer's disease and Huntington's disease, and viral infection diseases such as AIDS and hepatitis, potent and specific inhibitors of caspases have clinical potential. A series of peptide inhibitors has been designed based on cleavage sites of substrate proteins. However, these peptides are not necessarily the most potent to each caspase. Moreover, so far, it has proved to be difficult to design potent and specific peptide inhibitors of each caspase from sequence data of known cleavage sites in substrate proteins. We have attempted to develop a computational screening system for rapid selection of potent and specific peptide inhibitors from a comprehensive peptide library.
Results: We developed a new method for rapid evaluation and screening of peptide inhibitors based on Amino acid Positional Fitness (APF) score. By using this score, all known peptide inhibitors of each caspases-3,-7,-8, and -9 were rapidly selected in their enriched libraries. In this libraries, there were good correlations between predicted binding affinities of the known peptide inhibitors and their experimental Ki values. Furthermore, a novel potent peptide inhibitor, Ac-DNLD-CHO, for caspase-3 was able to be designed by this method. To our knowledge, DNLD is a first reported caspase-3 inhibitory peptide identified by using the computational screening strategy.
Conclusion: Our new method for rapid screening of peptide inhibitors using APF score is an efficient strategy to select potent and specific peptide inhibitors from a comprehensive peptide library. Thus, the APF method has the potential to become a valuable approach for the discovery of the most effective peptide inhibitors. Moreover, it is anticipated that these peptide inhibitors can serve as leads for further drug design and optimization of small molecular inhibitors.