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In Silico Drug Design of Anti-Breast Cancer Agents
Cancer is a condition marked by abnormal cell proliferation that has the potential to invade or indicate other health issues. Human beings are affected by more than 100 different types of cancer. Some cancer promotes rapid cell proliferation, whereas others cause cells to divide and develop more slo...
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/PMC10223712/ https://www.ncbi.nlm.nih.gov/pubmed/37241915 http://dx.doi.org/10.3390/molecules28104175 |
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author | Rajagopal, Kalirajan Kalusalingam, Anandarajagopal Bharathidasan, Anubhav Raj Sivaprakash, Aadarsh Shanmugam, Krutheesh Sundaramoorthy, Monall Byran, Gowramma |
author_facet | Rajagopal, Kalirajan Kalusalingam, Anandarajagopal Bharathidasan, Anubhav Raj Sivaprakash, Aadarsh Shanmugam, Krutheesh Sundaramoorthy, Monall Byran, Gowramma |
author_sort | Rajagopal, Kalirajan |
collection | PubMed |
description | Cancer is a condition marked by abnormal cell proliferation that has the potential to invade or indicate other health issues. Human beings are affected by more than 100 different types of cancer. Some cancer promotes rapid cell proliferation, whereas others cause cells to divide and develop more slowly. Some cancers, such as leukemia, produce visible tumors, while others, such as breast cancer, do not. In this work, in silico investigations were carried out to investigate the binding mechanisms of four major analogs, which are marine sesquiterpene, sesquiterpene lactone, heteroaromatic chalcones, and benzothiophene against the target estrogen receptor-α for targeting breast cancer using Schrödinger suite 2021-4. The Glide module handled the molecular docking experiments, the QikProp module handled the ADMET screening, and the Prime MM-GB/SA module determined the binding energy of the ligands. The benzothiophene analog BT_ER_15f (G-score −15.922 Kcal/mol) showed the best binding activity against the target protein estrogen receptor-α when compared with the standard drug tamoxifen which has a docking score of −13.560 Kcal/mol. TRP383 (tryptophan) has the highest interaction time with the ligand, and hence it could act for a long time. Based on in silico investigations, the benzothiophene analog BT_ER_15f significantly binds with the active site of the target protein estrogen receptor-α. Similar to the outcomes of molecular docking, the target and ligand complex interaction motif established a high affinity of lead candidates in a dynamic system. This study shows that estrogen receptor-α targets inhibitors with better potential and low toxicity when compared to the existing market drugs, which can be made from a benzothiophene derivative. It may result in considerable activity and be applied to more research on breast cancer. |
format | Online Article Text |
id | pubmed-10223712 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-102237122023-05-28 In Silico Drug Design of Anti-Breast Cancer Agents Rajagopal, Kalirajan Kalusalingam, Anandarajagopal Bharathidasan, Anubhav Raj Sivaprakash, Aadarsh Shanmugam, Krutheesh Sundaramoorthy, Monall Byran, Gowramma Molecules Article Cancer is a condition marked by abnormal cell proliferation that has the potential to invade or indicate other health issues. Human beings are affected by more than 100 different types of cancer. Some cancer promotes rapid cell proliferation, whereas others cause cells to divide and develop more slowly. Some cancers, such as leukemia, produce visible tumors, while others, such as breast cancer, do not. In this work, in silico investigations were carried out to investigate the binding mechanisms of four major analogs, which are marine sesquiterpene, sesquiterpene lactone, heteroaromatic chalcones, and benzothiophene against the target estrogen receptor-α for targeting breast cancer using Schrödinger suite 2021-4. The Glide module handled the molecular docking experiments, the QikProp module handled the ADMET screening, and the Prime MM-GB/SA module determined the binding energy of the ligands. The benzothiophene analog BT_ER_15f (G-score −15.922 Kcal/mol) showed the best binding activity against the target protein estrogen receptor-α when compared with the standard drug tamoxifen which has a docking score of −13.560 Kcal/mol. TRP383 (tryptophan) has the highest interaction time with the ligand, and hence it could act for a long time. Based on in silico investigations, the benzothiophene analog BT_ER_15f significantly binds with the active site of the target protein estrogen receptor-α. Similar to the outcomes of molecular docking, the target and ligand complex interaction motif established a high affinity of lead candidates in a dynamic system. This study shows that estrogen receptor-α targets inhibitors with better potential and low toxicity when compared to the existing market drugs, which can be made from a benzothiophene derivative. It may result in considerable activity and be applied to more research on breast cancer. MDPI 2023-05-18 /pmc/articles/PMC10223712/ /pubmed/37241915 http://dx.doi.org/10.3390/molecules28104175 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 Rajagopal, Kalirajan Kalusalingam, Anandarajagopal Bharathidasan, Anubhav Raj Sivaprakash, Aadarsh Shanmugam, Krutheesh Sundaramoorthy, Monall Byran, Gowramma In Silico Drug Design of Anti-Breast Cancer Agents |
title | In Silico Drug Design of Anti-Breast Cancer Agents |
title_full | In Silico Drug Design of Anti-Breast Cancer Agents |
title_fullStr | In Silico Drug Design of Anti-Breast Cancer Agents |
title_full_unstemmed | In Silico Drug Design of Anti-Breast Cancer Agents |
title_short | In Silico Drug Design of Anti-Breast Cancer Agents |
title_sort | in silico drug design of anti-breast cancer agents |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10223712/ https://www.ncbi.nlm.nih.gov/pubmed/37241915 http://dx.doi.org/10.3390/molecules28104175 |
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