Combinatorial library generation, molecular docking and molecular dynamics simulations for enhancing the isoflavone scaffold in phosphodiesterase inhibition

Abstract

Isoflavones are listed among the most widely studied natural compounds in light of their several biological properties, one of which consists in their ability to inhibit phosphodiesterases (PDEs). The enzymes from this class are deputed to the regulation of the 3′,5′-cyclic adenosine monophosphate (cAMP) and 3′,5′-cyclic guanosine monophosphate (cGMP) levels in the central and in the peripheral nervous systems (CNS and PNS), thus affecting several downstream pathways involved in different diseases. In this work, an extensive set of semi-synthetically obtainable molecules was generated by a combinatorial approach starting from the isoflavone scaffold with the aim of optimizing the interaction with the macromolecule and identifying new putative hit compounds. More specifically, a docking protocol was developed, validated and then adopted to screen the generated compounds towards PDE4, PDE5 and PDE9, three isoforms which are known to be involved in neurodegenerative disorders. Then, a structure based analysis was employed to guide the identification of the most promising hits based on the interactions with specific residues in the metal binding pocket of the PDEs, which have been proved to be crucial for triggering enzymatic inhibition. Lastly, molecular dynamics (MD) simulations were conducted to study with greater accuracy the binding of these compounds with the considered macromolecules. This study led to the set up and validation of a multi-technique computational approach for efficiently screening molecular structures towards PDE isoforms involved in neurodegeneration, and may pave the way for more targeted development of new, semi-synthetic potential PDE inhibitors derived from the isoflavone scaffold.