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Fragment‐Based Drug Design with CNS Therapeutic Targets
Author(s) -
Surratt Christopher K.,
Pellegrene Kendy A.,
Wasko Michael J.,
Jean Bernandie K.,
Madura Jeffry D.
Publication year - 2016
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.30.1_supplement.lb487
Subject(s) - virtual screening , drug discovery , computational biology , homology modeling , dopamine transporter , in silico , ligand efficiency , eticlopride , dopamine receptor d3 , transporter , chemistry , ligand (biochemistry) , computer science , dopamine receptor d2 , biology , receptor , biochemistry , gene , enzyme , sch 23390
Hundreds of millions of U.S. dollars are invested in the research and development of a single drug, a process fraught with failure. Lead compound development is an area ripe for new design strategies. Therapeutic lead candidates have been traditionally found using high‐throughput in vitro pharmacologic screening, a costly method for assaying thousands of compounds. This approach has more recently been augmented by structure‐based virtual screening, which employs computer models of the target protein to narrow the search for possible leads. A variant of virtual screening is fragment‐based drug design (FBDD), an emerging in silico lead discovery method that introduces low molecular weight fragments, rather than intact compounds, into the binding pocket of the receptor model. These fragments serve as starting points for “growing” the lead compound candidate. The objective of this study is to develop monoamine transporter and receptor computational models and employ their relevant ligand binding pockets as enclaves within which novel‐scaffold ligands can be constructed. Homology models of the human serotonin transporter (hSERT) and dopamine transporter (hDAT) proteins were constructed using as template a Drosophila dopamine transporter crystal structure; creation of a D3 dopamine receptor (D3R) model employed a human D3R crystal structure as template. The MedChem Transformations (MCT) module of Molecular Operating Environment 2015.10 software was used for FBDD. Applied to the generated D3R model, the MCT method successfully built using a fragment library the D2/D3 antagonist eticlopride and other potential D3R ligands. MCT places special emphasis on creating synthesizable, nontoxic molecules, suggesting that these hit compounds are viable ligand candidates (to be tested in subsequent in vitro pharmacologic assays). Fragment‐based methods should provide a viable, relatively low‐cost alternative for therapeutic lead discovery and optimization that can be applied to CNS targets to augment current design strategies. Support or Funding Information Supported by NIH grant DA027806.