Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Rajagopal, Kalirajan, Kalusalingam, Anandarajagopal, Bharathidasan, Anubhav Raj, Sivaprakash, Aadarsh, Shanmugam, Krutheesh, Sundaramoorthy, Monall, Byran, Gowramma
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
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
_version_ 1785050007057989632
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
work_keys_str_mv AT rajagopalkalirajan insilicodrugdesignofantibreastcanceragents
AT kalusalingamanandarajagopal insilicodrugdesignofantibreastcanceragents
AT bharathidasananubhavraj insilicodrugdesignofantibreastcanceragents
AT sivaprakashaadarsh insilicodrugdesignofantibreastcanceragents
AT shanmugamkrutheesh insilicodrugdesignofantibreastcanceragents
AT sundaramoorthymonall insilicodrugdesignofantibreastcanceragents
AT byrangowramma insilicodrugdesignofantibreastcanceragents