Precious A Akinnusi, Samuel O Olubode, Ayomide O Adebesin, Toluwani A Nana, Sidiqat A Shodehinde
{"title":"发现表皮生长因子受体(EGFR)、人表皮生长因子受体2 (HER2)、雌激素受体(ER)和磷脂酰肌醇-3-激酶a (PI3Ka)用于个性化乳腺癌治疗的有希望的抑制剂","authors":"Precious A Akinnusi, Samuel O Olubode, Ayomide O Adebesin, Toluwani A Nana, Sidiqat A Shodehinde","doi":"10.1177/11769351221127862","DOIUrl":null,"url":null,"abstract":"<p><p>Despite the rapid developments and advancements to improve treatments, Breast cancer remains one of the deadliest health challenges and the most frequently diagnosed tumor. One of the major problems with treatment is the unique difference that each cancerous cell exhibits. As a result, treatment of breast cancer has now become more personalized based on the specific features of the tumor such as overexpression of growth factor receptors (Epidermal growth factor receptor (EGFR), Human Epidermal Growth Factor Receptor 2 (HER2)), hormone receptors (Human Estrogen receptor alpha (ER)) and kinases involved in pivotal signaling associated with growth (Phosphatidylinositol 3-kinase (PI3K)). Several chemotherapeutic agents have been developed to curb the menace, but the associated adverse drug effects cannot be overlooked. To this end, this study employed a molecular modeling approach to identify novel compounds of natural origin that can potentially antagonize the receptors (mentioned above) associated with the pathophysiology of breast cancer and at the same time pose very little or no side effects. The results of the molecular model of biological interactions between a library of 118 anthocyanins and the binding pockets of the protein targets identified 5 compounds (Pelargonin, Delphinidin 3-<i>O</i>-rutinoside, Malvin, Cyanidin-3-(6-acetylglucoside), and Peonidin 3-<i>O</i>-rutinoside) with good binding affinities to the protein targets. Further MM-GBSA calculations returned high binding energies. The specific molecular interactions between the compounds and the targets were analyzed and reported herein. Also, all the compounds exhibited good pharmacokinetic profiles and are therefore recommended for further analyses as they could be explored as new treatment options for a broad range and personalized breast cancer treatments.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":" ","pages":"11769351221127862"},"PeriodicalIF":2.4000,"publicationDate":"2022-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/69/89/10.1177_11769351221127862.PMC9536107.pdf","citationCount":"2","resultStr":"{\"title\":\"Discovery of Promising Inhibitors of Epidermal Growth Factor Receptor (EGFR), Human Epidermal Growth Factor Receptor 2 (HER2), Estrogen Receptor (ER), and Phosphatidylinositol-3-kinase a (PI3Ka) for Personalized Breast Cancer Treatment.\",\"authors\":\"Precious A Akinnusi, Samuel O Olubode, Ayomide O Adebesin, Toluwani A Nana, Sidiqat A Shodehinde\",\"doi\":\"10.1177/11769351221127862\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Despite the rapid developments and advancements to improve treatments, Breast cancer remains one of the deadliest health challenges and the most frequently diagnosed tumor. One of the major problems with treatment is the unique difference that each cancerous cell exhibits. As a result, treatment of breast cancer has now become more personalized based on the specific features of the tumor such as overexpression of growth factor receptors (Epidermal growth factor receptor (EGFR), Human Epidermal Growth Factor Receptor 2 (HER2)), hormone receptors (Human Estrogen receptor alpha (ER)) and kinases involved in pivotal signaling associated with growth (Phosphatidylinositol 3-kinase (PI3K)). Several chemotherapeutic agents have been developed to curb the menace, but the associated adverse drug effects cannot be overlooked. To this end, this study employed a molecular modeling approach to identify novel compounds of natural origin that can potentially antagonize the receptors (mentioned above) associated with the pathophysiology of breast cancer and at the same time pose very little or no side effects. The results of the molecular model of biological interactions between a library of 118 anthocyanins and the binding pockets of the protein targets identified 5 compounds (Pelargonin, Delphinidin 3-<i>O</i>-rutinoside, Malvin, Cyanidin-3-(6-acetylglucoside), and Peonidin 3-<i>O</i>-rutinoside) with good binding affinities to the protein targets. Further MM-GBSA calculations returned high binding energies. The specific molecular interactions between the compounds and the targets were analyzed and reported herein. Also, all the compounds exhibited good pharmacokinetic profiles and are therefore recommended for further analyses as they could be explored as new treatment options for a broad range and personalized breast cancer treatments.</p>\",\"PeriodicalId\":35418,\"journal\":{\"name\":\"Cancer Informatics\",\"volume\":\" \",\"pages\":\"11769351221127862\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2022-10-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/69/89/10.1177_11769351221127862.PMC9536107.pdf\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cancer Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/11769351221127862\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2022/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"MATHEMATICAL & COMPUTATIONAL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/11769351221127862","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
Discovery of Promising Inhibitors of Epidermal Growth Factor Receptor (EGFR), Human Epidermal Growth Factor Receptor 2 (HER2), Estrogen Receptor (ER), and Phosphatidylinositol-3-kinase a (PI3Ka) for Personalized Breast Cancer Treatment.
Despite the rapid developments and advancements to improve treatments, Breast cancer remains one of the deadliest health challenges and the most frequently diagnosed tumor. One of the major problems with treatment is the unique difference that each cancerous cell exhibits. As a result, treatment of breast cancer has now become more personalized based on the specific features of the tumor such as overexpression of growth factor receptors (Epidermal growth factor receptor (EGFR), Human Epidermal Growth Factor Receptor 2 (HER2)), hormone receptors (Human Estrogen receptor alpha (ER)) and kinases involved in pivotal signaling associated with growth (Phosphatidylinositol 3-kinase (PI3K)). Several chemotherapeutic agents have been developed to curb the menace, but the associated adverse drug effects cannot be overlooked. To this end, this study employed a molecular modeling approach to identify novel compounds of natural origin that can potentially antagonize the receptors (mentioned above) associated with the pathophysiology of breast cancer and at the same time pose very little or no side effects. The results of the molecular model of biological interactions between a library of 118 anthocyanins and the binding pockets of the protein targets identified 5 compounds (Pelargonin, Delphinidin 3-O-rutinoside, Malvin, Cyanidin-3-(6-acetylglucoside), and Peonidin 3-O-rutinoside) with good binding affinities to the protein targets. Further MM-GBSA calculations returned high binding energies. The specific molecular interactions between the compounds and the targets were analyzed and reported herein. Also, all the compounds exhibited good pharmacokinetic profiles and are therefore recommended for further analyses as they could be explored as new treatment options for a broad range and personalized breast cancer treatments.
期刊介绍:
The field of cancer research relies on advances in many other disciplines, including omics technology, mass spectrometry, radio imaging, computer science, and biostatistics. Cancer Informatics provides open access to peer-reviewed high-quality manuscripts reporting bioinformatics analysis of molecular genetics and/or clinical data pertaining to cancer, emphasizing the use of machine learning, artificial intelligence, statistical algorithms, advanced imaging techniques, data visualization, and high-throughput technologies. As the leading journal dedicated exclusively to the report of the use of computational methods in cancer research and practice, Cancer Informatics leverages methodological improvements in systems biology, genomics, proteomics, metabolomics, and molecular biochemistry into the fields of cancer detection, treatment, classification, risk-prediction, prevention, outcome, and modeling.