4.7 Article

Comprehensive 3D-QSAR Model Predicts Binding Affinity of Structurally Diverse Sigma 1 Receptor Ligands

Journal

JOURNAL OF CHEMICAL INFORMATION AND MODELING
Volume 59, Issue 1, Pages 486-497

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acs.jcim.8b00521

Keywords

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Funding

  1. New Jersey Health Foundation
  2. Rutgers TechAdvance/TechXpress fund
  3. Biomedical Informatics Shared Resource of the Rutgers Cancer Institute of New Jersey [P30CA072720]
  4. NIH [ISI0OD012346-01A1]

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The Sigma 1 Receptor (SIR) has attracted intense interest as a pharmaceutical target for various therapeutic indications, including the treatment of neuropathic pain and the potentiation of opioid analgesia. Efforts by drug developers to rationally design SIR antagonists have been spurred recently by the 2016 publication of the high-resolution X-ray crystal structure of the ligand-bound human SIR. Until now, however, the absence in the published literature of a single, large-scale, and comprehensive quantitative structure activity relationship (QSAR) model that encompasses a structurally diverse collection of S1R ligands has impaired rapid progress. To our best knowledge, the present study represents the first report of a statistically robust and highly predictive 3D-QSAR model (R-2 = 0.92, Q(2) = 0.62, R-pred(2) = 0.81) based on the X-ray crystal structure of human SIR and constructed from a pooled compilation of 180 SIR antagonists that encompass five structurally diverse chemical families investigated using identical experimental protocols. Best practices, as recommended by the Organization for Economic Cooperation and Development (OECD: http://www.oecd.org/), were adopted for pooling data from disparate sources and for QSAR model development and both internal and external model validation. The practical utility of the final 3D-QSAR model was tested by virtual screening of the DrugBank database of FDA approved drugs supplemented by eight reported SIR antagonists. Among the top-ranked 40 DrugBank hits, four approved drugs which were previously unknown as SIR antagonists were tested using in vitro radiolabeled human SIR binding assays. Of these, two drugs (diphenhydramine and phenyltoloxamine) exhibited potent S1R binding affinity with K-i = 58 nM and 160 nM, respectively. As diphenhydramine is approved as an antiallergic, and phenyltoloxamine as an analgesic and sedative, each of these compounds represents a viable starting point for a drug discovery campaign aimed at the development of novel S1R antagonists for a wide range of therapeutic indications.

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