Abstract
Venoms are comprised of diverse mixtures of proteins, peptides, and small molecules. Identifying individual venom components and their target(s) with mechanism of action is now attainable to understand comprehensively the effectiveness of venom cocktails and how they collectively function in the defense and predation of an organism. Here, structure-based computational methods were used with bioinformatics tools to screen and identify potential biological targets of tertiapin (TPN), a venom peptide from Apis mellifera (European honey bee). The small hive beetle (Aethina tumida (A. tumida)) is a natural predator of the honey bee colony and was found to possess multiple inwardly rectifying K+ (Kir) channel subunit genes from a genomic BLAST search analysis. Structure-based virtual screening of homology modelled A. tumida Kir (atKir) channels found TPN to interact with a docking profile and interface “footprint” equivalent to known TPN-sensitive mammalian Kir channels. The results support the hypothesis that atKir channels, and perhaps other insect Kir channels, are natural biological targets of TPN that help defend the bee colony from infestations by blocking K+ transport via atKir channels. From these in silico findings, this hypothesis can now be subsequently tested in vitro by validating atKir channel block as well as in vivo TPN toxicity towards A. tumida. This study highlights the utility and potential benefits of screening in virtual space for venom peptide interactions and their biological targets, which otherwise would not be feasible.
Highlights
Venoms from Hymenoptera and other venomous species are comprised of diverse mixtures of proteins, peptides, and small molecules [1,2]
The atomic-level structural details that have emerged for both venom-derived peptides and several ion channels have enabled structure-based computational screening techniques to be deployed for identifying potential target effectors for venom components in silico [6]
The human Kir1.1 channel isoform is insensitive to TPN block due primarily to two key amino acid differences in the outer vestibule of the Kir1.1 channel where TPN is known to bind [15,16]
Summary
Venoms from Hymenoptera and other venomous species are comprised of diverse mixtures of proteins, peptides, and small molecules [1,2]. The atomic-level structural details that have emerged for both venom-derived peptides and several ion channels have enabled structure-based computational screening techniques to be deployed for identifying potential target effectors for venom components in silico [6]. These methods are helping to guide rational peptide design efforts to re-engineer venom peptides for potential drug development purposes [7,8,9]
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