SPIDR: small-molecule peptide-influenced drug repurposing

Matthew D King,Owen M Mcdougal,Thomas Long,Timothy L Andersen,Daniel L Pfalmer

doi:10.1186/s12859-018-2153-y

Abstract

BackgroundConventional de novo drug design is costly and time consuming, making it accessible to only the best resourced research organizations. An emergent approach to new drug development is drug repurposing, in which compounds that have already gone through some level of clinical testing are examined for efficacy against diseases divergent than their original application. Repurposing of existing drugs circumvents the time and considerable cost of early stages of drug development, and can be accelerated by using software to screen existing chemical databases to identify suitable drug candidates.ResultsSmall-molecule Peptide-Influenced Drug Repurposing (SPIDR) was developed to identify small molecule drugs that target a specific receptor by exploring the conformational binding space of peptide ligands. SPIDR was tested using the potent and selective 16-amino acid peptide α-conotoxin MII ligand and the α3β2-nicotinic acetylcholine receptor (nAChR) isoform. SPIDR incorporates a genetic algorithm-based, heuristic search procedure, which was used to explore the ligand binding domain of the α3β2-nAChR isoform using a library consisting of 640,000 α-conotoxin MII peptide analogs. The peptides that exhibited the highest affinity for α3β2-nAChR were used as models for a small-molecule structure similarity search of the PubChem Compound database. SPIDR incorporates the SimSearcher utility, which generates shape distribution signatures of molecules and employs multi-level K-means clustering to insure fast database queries. SPIDR identified non-peptide drugs with estimated binding affinities nearly double that of the native α-conotoxin MII peptide.ConclusionsSPIDR has been generalized and integrated into DockoMatic v 2.1. This software contains an intuitive graphical interface for peptide mutant screening workflow and facilitates mapping, clustering, and searching of local molecular databases, making DockoMatic a valuable tool for researchers in drug design and repurposing.

Highlights

Conventional de novo drug design is costly and time consuming, making it accessible to only the best resourced research organizations
genetic algorithm managed peptide mutant screening (GAMPMS) implementation required a total of 9344 molecular docking jobs to explore 640,000 variants of Alpha conotoxins (α-CTxs) MII
The estimated binding free energy of α-CTx MII was − 12.38 kcal/mol compared to the ΔGbind of the top ten mutants ranging from − 20.66 to − 21.07 kcal/mol, indicating that the analog screening process identified peptide ligands with more favorable receptor binding energies than the native peptide

Summary

Introduction

Conventional de novo drug design is costly and time consuming, making it accessible to only the best resourced research organizations. An emergent approach to new drug development is drug repurposing, in which compounds that have already gone through some level of clinical testing are examined for efficacy against diseases divergent than their original application. Conventional de novo drug development involves identifying a lead drug candidate, optimizing its structural and pharmacological properties, and validating it through expensive and time intensive pre-clinical and clinical trials. Drug repurposing jumpstarts the drug development process by using compounds that have already gone through some level of clinical testing, rather than attempting to create new unproven drugs. The drug-repurposing paradigm accounted for nearly 30% of United States Food and Drug Administration (FDA) approved drugs between 1999 and 2008 [6].

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