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Computational Discovery of Marine Molecules of the Cyclopeptide Family with Therapeutic Potential
Stellatolides are natural compounds that have shown promising biological activities, including antitumor, antimicrobial, and anti-inflammatory properties, making them potential candidates for drug development. Chemical Reactivity Theory (CRT) is a branch of chemistry that explains and predicts the b...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10610383/ https://www.ncbi.nlm.nih.gov/pubmed/37895848 http://dx.doi.org/10.3390/ph16101377 |
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author | Flores-Holguín, Norma Salas-Leiva, Joan S. Glossman-Mitnik, Daniel |
author_facet | Flores-Holguín, Norma Salas-Leiva, Joan S. Glossman-Mitnik, Daniel |
author_sort | Flores-Holguín, Norma |
collection | PubMed |
description | Stellatolides are natural compounds that have shown promising biological activities, including antitumor, antimicrobial, and anti-inflammatory properties, making them potential candidates for drug development. Chemical Reactivity Theory (CRT) is a branch of chemistry that explains and predicts the behavior of chemical reactions based on the electronic structure of molecules. Conceptual Density Functional Theory (CDFT) and Computational Peptidology (CP) are computational approaches used to study the behavior of atoms, molecules, and peptides. In this study, we present the results of our investigation of the chemical reactivity and ADMET properties of Stellatolides A-H using a novel computational approach called Conceptual DFT-based Computational Peptidology (CDFT-CP). Our study uses CDFT and CP to predict the reactivity and stability of molecules and to understand the behavior of peptides at the molecular level. We also predict the ADMET properties of the Stellatolides A–H to provide insight into their effectiveness, potential side effects, and optimal dosage and route of administration, as well as their biological targets. This study sheds light on the potential of Stellatolides A–H as promising candidates for drug development and highlights the potential of CDFT-CP for the study of other natural compounds and peptides. |
format | Online Article Text |
id | pubmed-10610383 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-106103832023-10-28 Computational Discovery of Marine Molecules of the Cyclopeptide Family with Therapeutic Potential Flores-Holguín, Norma Salas-Leiva, Joan S. Glossman-Mitnik, Daniel Pharmaceuticals (Basel) Article Stellatolides are natural compounds that have shown promising biological activities, including antitumor, antimicrobial, and anti-inflammatory properties, making them potential candidates for drug development. Chemical Reactivity Theory (CRT) is a branch of chemistry that explains and predicts the behavior of chemical reactions based on the electronic structure of molecules. Conceptual Density Functional Theory (CDFT) and Computational Peptidology (CP) are computational approaches used to study the behavior of atoms, molecules, and peptides. In this study, we present the results of our investigation of the chemical reactivity and ADMET properties of Stellatolides A-H using a novel computational approach called Conceptual DFT-based Computational Peptidology (CDFT-CP). Our study uses CDFT and CP to predict the reactivity and stability of molecules and to understand the behavior of peptides at the molecular level. We also predict the ADMET properties of the Stellatolides A–H to provide insight into their effectiveness, potential side effects, and optimal dosage and route of administration, as well as their biological targets. This study sheds light on the potential of Stellatolides A–H as promising candidates for drug development and highlights the potential of CDFT-CP for the study of other natural compounds and peptides. MDPI 2023-09-28 /pmc/articles/PMC10610383/ /pubmed/37895848 http://dx.doi.org/10.3390/ph16101377 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Flores-Holguín, Norma Salas-Leiva, Joan S. Glossman-Mitnik, Daniel Computational Discovery of Marine Molecules of the Cyclopeptide Family with Therapeutic Potential |
title | Computational Discovery of Marine Molecules of the Cyclopeptide Family with Therapeutic Potential |
title_full | Computational Discovery of Marine Molecules of the Cyclopeptide Family with Therapeutic Potential |
title_fullStr | Computational Discovery of Marine Molecules of the Cyclopeptide Family with Therapeutic Potential |
title_full_unstemmed | Computational Discovery of Marine Molecules of the Cyclopeptide Family with Therapeutic Potential |
title_short | Computational Discovery of Marine Molecules of the Cyclopeptide Family with Therapeutic Potential |
title_sort | computational discovery of marine molecules of the cyclopeptide family with therapeutic potential |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10610383/ https://www.ncbi.nlm.nih.gov/pubmed/37895848 http://dx.doi.org/10.3390/ph16101377 |
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