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Homology Modeling, Docking Studies and Molecular Dynamic Simulations Using Graphical Processing Unit Architecture to Probe the Type‐11 Phosphodiesterase Catalytic Site: A Computational Approach for the Rational Design of Selective Inhibitors
Author(s) -
Cichero Elena,
D'Ursi Pasqualina,
Moscatelli Marco,
Bruno Olga,
Orro Alessandro,
Rotolo Chiara,
Milanesi Luciano,
Fossa Paola
Publication year - 2013
Publication title -
chemical biology and drug design
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.59
H-Index - 77
eISSN - 1747-0285
pISSN - 1747-0277
DOI - 10.1111/cbdd.12193
Subject(s) - docking (animal) , homology modeling , phosphodiesterase , cyclic guanosine monophosphate , in silico , adme , active site , chemistry , gene isoform , computational biology , cgmp specific phosphodiesterase type 5 , enzyme , biology , biochemistry , sildenafil , medicine , in vitro , nursing , organic chemistry , anatomy , nitric oxide , gene
Phosphodiesterase 11 ( PDE 11) is the latest isoform of the PDE s family to be identified, acting on both cyclic adenosine monophosphate and cyclic guanosine monophosphate. The initial reports of PDE 11 found evidence for PDE 11 expression in skeletal muscle, prostate, testis, and salivary glands; however, the tissue distribution of PDE 11 still remains a topic of active study and some controversy. Given the sequence similarity between PDE 11 and PDE 5, several PDE 5 inhibitors have been shown to cross‐react with PDE 11. Accordingly, many non‐selective inhibitors, such as IBMX , zaprinast, sildenafil, and dipyridamole, have been documented to inhibit PDE 11. Only recently, a series of dihydrothieno[3,2‐ d ]pyrimidin‐4(3 H )‐one derivatives proved to be selective toward the PDE 11 isoform. In the absence of experimental data about PDE 11 X‐ray structures, we found interesting to gain a better understanding of the enzyme–inhibitor interactions using in silico simulations. In this work, we describe a computational approach based on homology modeling, docking, and molecular dynamics simulation to derive a predictive 3 D model of PDE 11. Using a G raphical P rocessing U nit architecture, it is possible to perform long simulations, find stable interactions involved in the complex, and finally to suggest guideline for the identification and synthesis of potent and selective inhibitors.