ALA‐A2 Is a Novel Anticancer Peptide Inspired by Alpha‐Lactalbumin: A Discovery from a Computational Peptide Library, In Silico Anticancer Peptide Screening and In Vitro Experimental Validation
Abstract Anticancer peptides (ACPs) are rising as a new strategy for cancer therapy. However, traditional laboratory screening to find and identify novel ACPs from hundreds to thousands of peptides is costly and time consuming. Here, a sequential procedure is applied to identify candidate ACPs from...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-03-01
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| Series: | Global Challenges |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/gch2.202200213 |
| _version_ | 1827993423014002688 |
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| author | Tassanee Lerksuthirat Pasinee On‐yam Sermsiri Chitphuk Wasana Stitchantrakul David S. Newburg Ardythe L. Morrow Suradej Hongeng Wararat Chiangjong Somchai Chutipongtanate |
| author_facet | Tassanee Lerksuthirat Pasinee On‐yam Sermsiri Chitphuk Wasana Stitchantrakul David S. Newburg Ardythe L. Morrow Suradej Hongeng Wararat Chiangjong Somchai Chutipongtanate |
| author_sort | Tassanee Lerksuthirat |
| collection | DOAJ |
| description | Abstract Anticancer peptides (ACPs) are rising as a new strategy for cancer therapy. However, traditional laboratory screening to find and identify novel ACPs from hundreds to thousands of peptides is costly and time consuming. Here, a sequential procedure is applied to identify candidate ACPs from a computer‐generated peptide library inspired by alpha‐lactalbumin, a milk protein with known anticancer properties. A total of 2688 distinct peptides, 5–25 amino acids in length, are generated from alpha‐lactalbumin. In silico ACP screening using the physicochemical and structural filters and three machine learning models lead to the top candidate peptides ALA‐A1 and ALA‐A2. In vitro screening against five human cancer cell lines supports ALA‐A2 as the positive hit. ALA‐A2 selectively kills A549 lung cancer cells in a dose‐dependent manner, with no hemolytic side effects, and acts as a cell penetrating peptide without membranolytic effects. Sequential window acquisition of all theorical fragment ions‐proteomics and functional validation reveal that ALA‐A2 induces autophagy to mediate lung cancer cell death. This approach to identify ALA‐A2 is time and cost‐effective. Further investigations are warranted to elucidate the exact intracellular targets of ALA‐A2. Moreover, these findings support the use of larger computational peptide libraries built upon multiple proteins to further advance ACP research and development. |
| first_indexed | 2024-04-10T04:25:46Z |
| format | Article |
| id | doaj.art-18ae5a0382bb4d9a89f3fd160df78fda |
| institution | Directory Open Access Journal |
| issn | 2056-6646 |
| language | English |
| last_indexed | 2024-04-10T04:25:46Z |
| publishDate | 2023-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | Global Challenges |
| spelling | doaj.art-18ae5a0382bb4d9a89f3fd160df78fda2023-03-10T14:08:10ZengWileyGlobal Challenges2056-66462023-03-0173n/an/a10.1002/gch2.202200213ALA‐A2 Is a Novel Anticancer Peptide Inspired by Alpha‐Lactalbumin: A Discovery from a Computational Peptide Library, In Silico Anticancer Peptide Screening and In Vitro Experimental ValidationTassanee Lerksuthirat0Pasinee On‐yam1Sermsiri Chitphuk2Wasana Stitchantrakul3David S. Newburg4Ardythe L. Morrow5Suradej Hongeng6Wararat Chiangjong7Somchai Chutipongtanate8Research Center Faculty of Medicine Ramathibodi Hospital Mahidol University Bangkok 10400 ThailandPediatric Translational Research Unit Department of Pediatrics Faculty of Medicine Ramathibodi Hospital Mahidol University Bangkok 10400 ThailandResearch Center Faculty of Medicine Ramathibodi Hospital Mahidol University Bangkok 10400 ThailandResearch Center Faculty of Medicine Ramathibodi Hospital Mahidol University Bangkok 10400 ThailandDivision of Epidemiology Department of Environmental and Public Health Sciences University of Cincinnati College of Medicine Cincinnati OH 45267 USADivision of Epidemiology Department of Environmental and Public Health Sciences University of Cincinnati College of Medicine Cincinnati OH 45267 USADivision of Hematology and Oncology Department of Pediatrics Faculty of Medicine Ramathibodi Hospital Mahidol University Bangkok 10400 ThailandPediatric Translational Research Unit Department of Pediatrics Faculty of Medicine Ramathibodi Hospital Mahidol University Bangkok 10400 ThailandPediatric Translational Research Unit Department of Pediatrics Faculty of Medicine Ramathibodi Hospital Mahidol University Bangkok 10400 ThailandAbstract Anticancer peptides (ACPs) are rising as a new strategy for cancer therapy. However, traditional laboratory screening to find and identify novel ACPs from hundreds to thousands of peptides is costly and time consuming. Here, a sequential procedure is applied to identify candidate ACPs from a computer‐generated peptide library inspired by alpha‐lactalbumin, a milk protein with known anticancer properties. A total of 2688 distinct peptides, 5–25 amino acids in length, are generated from alpha‐lactalbumin. In silico ACP screening using the physicochemical and structural filters and three machine learning models lead to the top candidate peptides ALA‐A1 and ALA‐A2. In vitro screening against five human cancer cell lines supports ALA‐A2 as the positive hit. ALA‐A2 selectively kills A549 lung cancer cells in a dose‐dependent manner, with no hemolytic side effects, and acts as a cell penetrating peptide without membranolytic effects. Sequential window acquisition of all theorical fragment ions‐proteomics and functional validation reveal that ALA‐A2 induces autophagy to mediate lung cancer cell death. This approach to identify ALA‐A2 is time and cost‐effective. Further investigations are warranted to elucidate the exact intracellular targets of ALA‐A2. Moreover, these findings support the use of larger computational peptide libraries built upon multiple proteins to further advance ACP research and development.https://doi.org/10.1002/gch2.202200213anticancer peptidescytotoxic screeningdrug discoverylung adenocarcinomamachine learningpeptide library |
| spellingShingle | Tassanee Lerksuthirat Pasinee On‐yam Sermsiri Chitphuk Wasana Stitchantrakul David S. Newburg Ardythe L. Morrow Suradej Hongeng Wararat Chiangjong Somchai Chutipongtanate ALA‐A2 Is a Novel Anticancer Peptide Inspired by Alpha‐Lactalbumin: A Discovery from a Computational Peptide Library, In Silico Anticancer Peptide Screening and In Vitro Experimental Validation Global Challenges anticancer peptides cytotoxic screening drug discovery lung adenocarcinoma machine learning peptide library |
| title | ALA‐A2 Is a Novel Anticancer Peptide Inspired by Alpha‐Lactalbumin: A Discovery from a Computational Peptide Library, In Silico Anticancer Peptide Screening and In Vitro Experimental Validation |
| title_full | ALA‐A2 Is a Novel Anticancer Peptide Inspired by Alpha‐Lactalbumin: A Discovery from a Computational Peptide Library, In Silico Anticancer Peptide Screening and In Vitro Experimental Validation |
| title_fullStr | ALA‐A2 Is a Novel Anticancer Peptide Inspired by Alpha‐Lactalbumin: A Discovery from a Computational Peptide Library, In Silico Anticancer Peptide Screening and In Vitro Experimental Validation |
| title_full_unstemmed | ALA‐A2 Is a Novel Anticancer Peptide Inspired by Alpha‐Lactalbumin: A Discovery from a Computational Peptide Library, In Silico Anticancer Peptide Screening and In Vitro Experimental Validation |
| title_short | ALA‐A2 Is a Novel Anticancer Peptide Inspired by Alpha‐Lactalbumin: A Discovery from a Computational Peptide Library, In Silico Anticancer Peptide Screening and In Vitro Experimental Validation |
| title_sort | ala a2 is a novel anticancer peptide inspired by alpha lactalbumin a discovery from a computational peptide library in silico anticancer peptide screening and in vitro experimental validation |
| topic | anticancer peptides cytotoxic screening drug discovery lung adenocarcinoma machine learning peptide library |
| url | https://doi.org/10.1002/gch2.202200213 |
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