Beyond Bt: Exploiting arachnid venom peptide toxins to control crop pests

2016 ◽  
Author(s):  
Elaine C. Fitches
Keyword(s):  
Crop Pests ◽  
Venom Peptide ◽  
Peptide Toxins

Induction of seizures by the potent K+ channel-blocking scorpion venom peptide toxins tityustoxin-Kα and pandinustoxin-Kα

1999 ◽  
Vol 34 (2-3) ◽  
pp. 177-186 ◽  
Author(s):  
K.N. Juhng ◽  
T.G. Kokate ◽  
S. Yamaguchi ◽  
B.Y. Kim ◽  
R.S. Rogowski ◽  
...  
Keyword(s):  
Scorpion Venom ◽  
K Channel ◽  
Venom Peptide ◽  
Channel Blocking ◽  
Peptide Toxins

Ca2+-activated K+ channels of human and rabbit erythrocytes display distinctive patterns of inhibition by venom peptide toxins

1995 ◽  
Vol 147 (1) ◽  
pp. 71-82 ◽  
Author(s):  
C. Brugnara ◽  
C. C. Armsby ◽  
L. De Franceschi ◽  
M. Crest ◽  
M.-F. Martin Euclaire ◽  
...  
Keyword(s):  
K Channels ◽  
Venom Peptide ◽  
Peptide Toxins

Peptide toxins from the longest animal on earth

Planta Medica ◽  
2016 ◽  
Vol 81 (S 01) ◽  
pp. S1-S381
Author(s):  
E Jacobsson ◽  
HS Andersson ◽  
M Strand ◽  
E Lebbe ◽  
C Eriksson ◽  
...  
Keyword(s):  
Peptide Toxins

Behavior-based control of insect crop pests

2018 ◽  
Author(s):  
Sandra A. Allan
Keyword(s):  
Insect Pests ◽  
Control Strategies ◽  
Insect Behavior ◽  
Life Cycles ◽  
Economic Damage ◽  
Mass Trapping ◽  
Ecological Traits ◽  
Crop Pests ◽  
Effective Strategies ◽  
Crop Development

Manipulation of insect behavior can provide the foundation for effective strategies for control of insect crop pests. A detailed understanding of life cycles and the behavioral repertoires of insect pests is essential for development of this approach. A variety of strategies have been developed based on behavioral manipulation and include mass trapping, attract-and-kill, auto-dissemination, mating and host plant location disruption, and push-pull. Insight into application of these strategies for insect pests within Diptera, Lepidoptera, Coleoptera, and Hemiptera/Thysanoptera are provided, but first with an overview of economic damage and traditional control approaches, and overview of relevant behavioral/ecological traits. Then examples are provided of how these different control strategies are applied for each taxonomic group. The future of these approaches in the context of altered crop development for repellency or as anti-feedants, the effects of climate change and the risks of behaviorally-based methods are discussed.

Synergies and tradeoffs in natural regulation of crop pests and diseases under plant species diversification

2021 ◽  
pp. 105658
Author(s):  
Alain Ratnadass ◽  
Jacques Avelino ◽  
Paula Fernandes ◽  
Philippe Letourmy ◽  
Régis Babin ◽  
...  
Keyword(s):  
Plant Species ◽  
Crop Pests ◽  
Species Diversification ◽  
Pests And Diseases ◽  
Natural Regulation

scholarly journals Snails In Silico: A Review of Computational Studies on the Conopeptides

Marine Drugs ◽  
2019 ◽  
Vol 17 (3) ◽  
pp. 145 ◽  
Author(s):  
Rachael Mansbach ◽  
Timothy Travers ◽  
Benjamin McMahon ◽  
Jeanne Fair ◽  
S. Gnanakaran
Keyword(s):  
Posttranslational Modifications ◽  
High Throughput Screening ◽  
Molecular Mechanisms ◽  
Defense Mechanism ◽  
Docking Studies ◽  
Chemical Diversity ◽  
Machine Learning Techniques ◽  
Peptide Toxins ◽  
Dynamics Simulations ◽  
And Function

Marine cone snails are carnivorous gastropods that use peptide toxins called conopeptides both as a defense mechanism and as a means to immobilize and kill their prey. These peptide toxins exhibit a large chemical diversity that enables exquisite specificity and potency for target receptor proteins. This diversity arises in terms of variations both in amino acid sequence and length, and in posttranslational modifications, particularly the formation of multiple disulfide linkages. Most of the functionally characterized conopeptides target ion channels of animal nervous systems, which has led to research on their therapeutic applications. Many facets of the underlying molecular mechanisms responsible for the specificity and virulence of conopeptides, however, remain poorly understood. In this review, we will explore the chemical diversity of conopeptides from a computational perspective. First, we discuss current approaches used for classifying conopeptides. Next, we review different computational strategies that have been applied to understanding and predicting their structure and function, from machine learning techniques for predictive classification to docking studies and molecular dynamics simulations for molecular-level understanding. We then review recent novel computational approaches for rapid high-throughput screening and chemical design of conopeptides for particular applications. We close with an assessment of the state of the field, emphasizing important questions for future lines of inquiry.

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