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

Abstract

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,more » emphasizing important questions for future lines of inquiry.« less

Authors:
 [1];  [1];  [1]; ORCiD logo [1];  [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1501817
Report Number(s):
LA-UR-19-21315
Journal ID: ISSN 1660-3397; MDARE6
Grant/Contract Number:  
89233218CNA000001
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Marine Drugs
Additional Journal Information:
Journal Volume: 17; Journal Issue: 3; Journal ID: ISSN 1660-3397
Publisher:
MDPI
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; conotoxins; reviews; bioactive peptides; machine learning; molecular dynamics

Citation Formats

Mansbach, Rachael, Travers, Timothy, McMahon, Benjamin, Fair, Jeanne, and Gnanakaran, S. Snails In Silico: A Review of Computational Studies on the Conopeptides. United States: N. p., 2019. Web. doi:10.3390/md17030145.
Mansbach, Rachael, Travers, Timothy, McMahon, Benjamin, Fair, Jeanne, & Gnanakaran, S. Snails In Silico: A Review of Computational Studies on the Conopeptides. United States. doi:10.3390/md17030145.
Mansbach, Rachael, Travers, Timothy, McMahon, Benjamin, Fair, Jeanne, and Gnanakaran, S. Fri . "Snails In Silico: A Review of Computational Studies on the Conopeptides". United States. doi:10.3390/md17030145. https://www.osti.gov/servlets/purl/1501817.
@article{osti_1501817,
title = {Snails In Silico: A Review of Computational Studies on the Conopeptides},
author = {Mansbach, Rachael and Travers, Timothy and McMahon, Benjamin and Fair, Jeanne and Gnanakaran, S.},
abstractNote = {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.},
doi = {10.3390/md17030145},
journal = {Marine Drugs},
issn = {1660-3397},
number = 3,
volume = 17,
place = {United States},
year = {2019},
month = {3}
}

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Works referenced in this record:

Conus Peptides: Biodiversity-based Discovery and Exogenomics
journal, August 2006

  • Olivera, Baldomero M.
  • Journal of Biological Chemistry, Vol. 281, Issue 42, p. 31173-31177
  • DOI: 10.1074/jbc.R600020200