Marine Toxins: Characterization, Detection, Classification and Potential Therapeutics

A special issue of Marine Drugs (ISSN 1660-3397). This special issue belongs to the section "Marine Toxins".

Deadline for manuscript submissions: 15 April 2025 | Viewed by 84

Special Issue Editors


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Guest Editor
Bioscience Division, MS M888, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
Interests: conotoxin structure; NMR structure of peptide toxins; prediction of marine toxin structures; machine learning and artificial intelligence (ML/AI); therapeutics; toxicological assays; detection of toxins; low magnetic field systems for portable NMR detection

E-Mail Website
Guest Editor
Bioscience Division, MS M888, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
Interests: toxin structural and functional characterization; toxin prediction; toxin detection; therapeutics; protein/peptide engineering

Special Issue Information

Dear Colleagues,

Marine natural products and especially the myriad diverse forms of conotoxins and related marine toxins have a tremendous future in the development of new therapeutic strategies and biomedical treatments for many diseases including cancer, microbial infections, epilepsy, autoimmune diseases, neurological conditions and cardiovascular conditions. Consequently, marine organisms will play a critical role in our future discovery of novel toxin-based drugs with the potential to treat multiple diseases that threaten human health.

While there is a recognized need to identify and characterize these toxins, the process of identifying and characterizing both the target of their attack and their toxicity is a difficult, costly, and time-consuming challenge. Overcoming this challenge requires a set of diverse, complex, and labor-intensive biological, toxicological, and analytical techniques for effective characterization. Additionally, with the thousands of new peptide sequences being generated by transcriptomics and proteomics, traditional toxicological methods are just too slow; hence, experimental tools coupled with computational methods are necessary to understand toxin structure/function, allowing new detection reagents and therapeutics to be developed.

This Special Issue particularly welcomes and invites articles that focus on this challenge for marine toxin characterization, detection, classification, ML/AI prediction of biological targets, toxicity, and, importantly, potential therapeutics.

Dr. Robert F. Williams
Dr. Hau B. Nguyen
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Marine Drugs is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • marine toxins
  • conotoxins
  • detection
  • characterization
  • classification
  • structure prediction
  • therapeutics
  • machine learning
  • modeling
  • structure design

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Published Papers

This special issue is now open for submission.
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