Phosphodiesterase 4 (PDE4) has been established as a drug target for inflammatory diseases of respiratory tract like asthma and chronic obstructive pulmonary disease. The selective inhibitors of PDE4B, a subtype of PDE4, are devoid of adverse effects like nausea and vomiting commonly associated with non-selective PDE4B inhibitors. This makes the development of PDE4B subtype selective inhibitors a desirable research goal. Thus, in the present study, molecular docking, molecular dynamic simulations and binding free energy were performed to explore potential selective PDE4B inhibitors based on ginger phenolic compounds. The results of docking studies indicate that some of the ginger phenolic compounds demonstrate higher selective PDE4B inhibition than existing selective PDE4B inhibitors. Additionally, 6-gingerol showed the highest PDE4B inhibitory activity as well as selectivity. The comparison of binding mode of PDE4B/6-gingerol and PDE4D/6-gingerol complexes revealed that 6-gingerol formed additional hydrogen bond and hydrophobic interactions with active site and control region 3 (CR3) residues in PDE4B, which were primarily responsible for its PDE4B selectivity. The results of binding free energy demonstrated that electrostatic energy is the primary factor in elucidating the mechanism of PDE4B inhibition by 6-gingerol. Dynamic cross-correlation studies also supported the results of docking and molecular dynamics simulation. Finally, a small library of molecules were designed based on the identified structural features, majority of designed molecules showed higher PDE4B selectivity than 6-gingerol. These results provide important structural features for designing new selective PDE4B inhibitors as anti-inflammatory drugs and promising candidates for synthesis and pre-clinical pharmacological investigations.

Computational drug design tools have become indispensable in the quest for new drugs. There is hardly any drug discovery program where computational methods are not employed, be it structure-based or ligand-based methods. Numerous drug targets have been explored for discovery of new drugs using computational methods. In recent times, discovery of newer and selective phosphodiesterase as medications for inlammatory disorders, CNS disorders, and many other diseases has been the focus of many research groups worldwide. Most of these groups have employed computational methods of drug design and discovery at diferent stages of their research. This chapter reviews the reported application of computational methods used in the discovery and development of phosphodiesterase inhibitors.