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High-Throughput Prediction and Design of Novel Conopeptides for Biomedical Research and Development
Cone snail venoms have been considered a valuable treasure for international scientists and businessmen, mainly due to their pharmacological applications in development of marine drugs for treatment of various human diseases. To date, around 800 Conus species are recorded, and each of them produces...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AAAS
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10521759/ https://www.ncbi.nlm.nih.gov/pubmed/37850131 http://dx.doi.org/10.34133/2022/9895270 |
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author | Gao, Bingmiao Huang, Yu Peng, Chao Lin, Bo Liao, Yanling Bian, Chao Yang, Jiaan Shi, Qiong |
author_facet | Gao, Bingmiao Huang, Yu Peng, Chao Lin, Bo Liao, Yanling Bian, Chao Yang, Jiaan Shi, Qiong |
author_sort | Gao, Bingmiao |
collection | PubMed |
description | Cone snail venoms have been considered a valuable treasure for international scientists and businessmen, mainly due to their pharmacological applications in development of marine drugs for treatment of various human diseases. To date, around 800 Conus species are recorded, and each of them produces over 1,000 venom peptides (termed as conopeptides or conotoxins). This reflects the high diversity and complexity of cone snails, although most of their venoms are still uncharacterized. Advanced multiomics (such as genomics, transcriptomics, and proteomics) approaches have been recently developed to mine diverse Conus venom samples, with the main aim to predict and identify potentially interesting conopeptides in an efficient way. Some bioinformatics techniques have been applied to predict and design novel conopeptide sequences, related targets, and their binding modes. This review provides an overview of current knowledge on the high diversity of conopeptides and multiomics advances in high-throughput prediction of novel conopeptide sequences, as well as molecular modeling and design of potential drugs based on the predicted or validated interactions between these toxins and their molecular targets. |
format | Online Article Text |
id | pubmed-10521759 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | AAAS |
record_format | MEDLINE/PubMed |
spelling | pubmed-105217592023-10-17 High-Throughput Prediction and Design of Novel Conopeptides for Biomedical Research and Development Gao, Bingmiao Huang, Yu Peng, Chao Lin, Bo Liao, Yanling Bian, Chao Yang, Jiaan Shi, Qiong Biodes Res Review Article Cone snail venoms have been considered a valuable treasure for international scientists and businessmen, mainly due to their pharmacological applications in development of marine drugs for treatment of various human diseases. To date, around 800 Conus species are recorded, and each of them produces over 1,000 venom peptides (termed as conopeptides or conotoxins). This reflects the high diversity and complexity of cone snails, although most of their venoms are still uncharacterized. Advanced multiomics (such as genomics, transcriptomics, and proteomics) approaches have been recently developed to mine diverse Conus venom samples, with the main aim to predict and identify potentially interesting conopeptides in an efficient way. Some bioinformatics techniques have been applied to predict and design novel conopeptide sequences, related targets, and their binding modes. This review provides an overview of current knowledge on the high diversity of conopeptides and multiomics advances in high-throughput prediction of novel conopeptide sequences, as well as molecular modeling and design of potential drugs based on the predicted or validated interactions between these toxins and their molecular targets. AAAS 2022-11-07 /pmc/articles/PMC10521759/ /pubmed/37850131 http://dx.doi.org/10.34133/2022/9895270 Text en https://creativecommons.org/licenses/by/4.0/Exclusive Licensee Nanjing Agricultural University. Distributed under a Creative Commons Attribution License (CC BY 4.0). |
spellingShingle | Review Article Gao, Bingmiao Huang, Yu Peng, Chao Lin, Bo Liao, Yanling Bian, Chao Yang, Jiaan Shi, Qiong High-Throughput Prediction and Design of Novel Conopeptides for Biomedical Research and Development |
title | High-Throughput Prediction and Design of Novel Conopeptides for Biomedical Research and Development |
title_full | High-Throughput Prediction and Design of Novel Conopeptides for Biomedical Research and Development |
title_fullStr | High-Throughput Prediction and Design of Novel Conopeptides for Biomedical Research and Development |
title_full_unstemmed | High-Throughput Prediction and Design of Novel Conopeptides for Biomedical Research and Development |
title_short | High-Throughput Prediction and Design of Novel Conopeptides for Biomedical Research and Development |
title_sort | high-throughput prediction and design of novel conopeptides for biomedical research and development |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10521759/ https://www.ncbi.nlm.nih.gov/pubmed/37850131 http://dx.doi.org/10.34133/2022/9895270 |
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