Identification by virtual screening and in vitro testing of human DOPA decarboxylase inhibitors.

通过虚拟筛选和体外试验鉴定人类多巴脱羧酶抑制剂

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作者:Daidone Frederick, Montioli Riccardo, Paiardini Alessandro, Cellini Barbara, Macchiarulo Antonio, Giardina Giorgio, Bossa Francesco, Borri Voltattorni Carla
Dopa decarboxylase (DDC), a pyridoxal 5'-phosphate (PLP) enzyme responsible for the biosynthesis of dopamine and serotonin, is involved in Parkinson's disease (PD). PD is a neurodegenerative disease mainly due to a progressive loss of dopamine-producing cells in the midbrain. Co-administration of L-Dopa with peripheral DDC inhibitors (carbidopa or benserazide) is the most effective symptomatic treatment for PD. Although carbidopa and trihydroxybenzylhydrazine (the in vivo hydrolysis product of benserazide) are both powerful irreversible DDC inhibitors, they are not selective because they irreversibly bind to free PLP and PLP-enzymes, thus inducing diverse side effects. Therefore, the main goals of this study were (a) to use virtual screening to identify potential human DDC inhibitors and (b) to evaluate the reliability of our virtual-screening (VS) protocol by experimentally testing the "in vitro" activity of selected molecules. Starting from the crystal structure of the DDC-carbidopa complex, a new VS protocol, integrating pharmacophore searches and molecular docking, was developed. Analysis of 15 selected compounds, obtained by filtering the public ZINC database, yielded two molecules that bind to the active site of human DDC and behave as competitive inhibitors with K(i) values ≥10 µM. By performing in silico similarity search on the latter compounds followed by a substructure search using the core of the most active compound we identified several competitive inhibitors of human DDC with K(i) values in the low micromolar range, unable to bind free PLP, and predicted to not cross the blood-brain barrier. The most potent inhibitor with a K(i) value of 500 nM represents a new lead compound, targeting human DDC, that may be the basis for lead optimization in the development of new DDC inhibitors. To our knowledge, a similar approach has not been reported yet in the field of DDC inhibitors discovery.

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