Identification of potential therapeutic dual inhibitors of EGFR/HER2 in breast cancer
Breast cancer (BC) is the leading cause of death among women worldwide. According to the Breast Cancer Research Foundation (BCRF), 25% of all cases of BC are positive for human epidermal growth factor receptor 2 (HER2), which is the most aggressive phenotype among the five BC subtypes. Previous stud...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-08-01
|
| Series: | European Journal of Medicinal Chemistry Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772417424000153 |
| _version_ | 1797263628027559936 |
|---|---|
| author | Megha Jethwa Aditi Gangopadhyay Achintya Saha |
| author_facet | Megha Jethwa Aditi Gangopadhyay Achintya Saha |
| author_sort | Megha Jethwa |
| collection | DOAJ |
| description | Breast cancer (BC) is the leading cause of death among women worldwide. According to the Breast Cancer Research Foundation (BCRF), 25% of all cases of BC are positive for human epidermal growth factor receptor 2 (HER2), which is the most aggressive phenotype among the five BC subtypes. Previous studies have reported that the epidermal growth factor receptor (EGFR) is also overexpressed in HER2-positive BC, which elevates disease severity. Based on these findings, the present study aimed to identify dual inhibitors of EGFR and HER2 by employing chemometric modelling techniques. A dataset of chemical molecules with affinity for both EGFR and HER2 was prepared by literature review. The dataset was split into training and test sets based on the inhibitory concentration (IC50) for EGFR and HER2. The training set was used to generate two pharmacophore models, one each for EGFR (n = 30, R2 value = 0.82 with RMSD = 1.4, Δ cost = 151.84, and configuration cost = 20.3) and HER2 (n = 30, R2 value = 0.84 with RMSD = 1.0, Δ cost = 68.47, and configuration cost = 22.2). The developed models were validated using the test set (n = 214 and 201, andR2pred = 0.73 and 0.70, for EGFR and HER2, respectively), decoy set (decoys = 104, actives = 18), and an external dataset (n = 20). The robustness of the models was validated using Fischer's randomization method (at 95% confidence) and applicability domain analysis. The validated models for EGFR and HER2 were used to screen the Asinex library (n = 575,302) for identifying consensus hits against both targets. Molecules with predicted IC50 < 20 nM were subsequently screened, and their toxicity profiles were evaluated using ProTox II. The interactions, ligand efficiency, and binding affinities of the selected compounds were assessed from the docking scores and molecular mechanics with generalized Born and surface area solvation (MMGBSA) energy. Hit selection against EGFR and HER2 was finally achieved by molecular dynamics simulations using the OPLS4 force field in Desmond. The identified hit can serve as a reference for developing dual inhibitors of EGFR and HER2 in future. |
| first_indexed | 2024-04-25T00:16:01Z |
| format | Article |
| id | doaj.art-c5f9d0354fd7444f816c220c0cf077cd |
| institution | Directory Open Access Journal |
| issn | 2772-4174 |
| language | English |
| last_indexed | 2024-04-25T00:16:01Z |
| publishDate | 2024-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | European Journal of Medicinal Chemistry Reports |
| spelling | doaj.art-c5f9d0354fd7444f816c220c0cf077cd2024-03-13T04:46:32ZengElsevierEuropean Journal of Medicinal Chemistry Reports2772-41742024-08-0111100143Identification of potential therapeutic dual inhibitors of EGFR/HER2 in breast cancerMegha Jethwa0Aditi Gangopadhyay1Achintya Saha2Department of Chemical Technology, University of Calcutta, 92 APC Road, Kolkata, 700009, IndiaDepartment of Chemical Technology, University of Calcutta, 92 APC Road, Kolkata, 700009, IndiaCorresponding author.; Department of Chemical Technology, University of Calcutta, 92 APC Road, Kolkata, 700009, IndiaBreast cancer (BC) is the leading cause of death among women worldwide. According to the Breast Cancer Research Foundation (BCRF), 25% of all cases of BC are positive for human epidermal growth factor receptor 2 (HER2), which is the most aggressive phenotype among the five BC subtypes. Previous studies have reported that the epidermal growth factor receptor (EGFR) is also overexpressed in HER2-positive BC, which elevates disease severity. Based on these findings, the present study aimed to identify dual inhibitors of EGFR and HER2 by employing chemometric modelling techniques. A dataset of chemical molecules with affinity for both EGFR and HER2 was prepared by literature review. The dataset was split into training and test sets based on the inhibitory concentration (IC50) for EGFR and HER2. The training set was used to generate two pharmacophore models, one each for EGFR (n = 30, R2 value = 0.82 with RMSD = 1.4, Δ cost = 151.84, and configuration cost = 20.3) and HER2 (n = 30, R2 value = 0.84 with RMSD = 1.0, Δ cost = 68.47, and configuration cost = 22.2). The developed models were validated using the test set (n = 214 and 201, andR2pred = 0.73 and 0.70, for EGFR and HER2, respectively), decoy set (decoys = 104, actives = 18), and an external dataset (n = 20). The robustness of the models was validated using Fischer's randomization method (at 95% confidence) and applicability domain analysis. The validated models for EGFR and HER2 were used to screen the Asinex library (n = 575,302) for identifying consensus hits against both targets. Molecules with predicted IC50 < 20 nM were subsequently screened, and their toxicity profiles were evaluated using ProTox II. The interactions, ligand efficiency, and binding affinities of the selected compounds were assessed from the docking scores and molecular mechanics with generalized Born and surface area solvation (MMGBSA) energy. Hit selection against EGFR and HER2 was finally achieved by molecular dynamics simulations using the OPLS4 force field in Desmond. The identified hit can serve as a reference for developing dual inhibitors of EGFR and HER2 in future.http://www.sciencedirect.com/science/article/pii/S2772417424000153Dual inhibitorEGFRHER2Pharmacophore modelDockingMolecular dynamics simulation |
| spellingShingle | Megha Jethwa Aditi Gangopadhyay Achintya Saha Identification of potential therapeutic dual inhibitors of EGFR/HER2 in breast cancer European Journal of Medicinal Chemistry Reports Dual inhibitor EGFR HER2 Pharmacophore model Docking Molecular dynamics simulation |
| title | Identification of potential therapeutic dual inhibitors of EGFR/HER2 in breast cancer |
| title_full | Identification of potential therapeutic dual inhibitors of EGFR/HER2 in breast cancer |
| title_fullStr | Identification of potential therapeutic dual inhibitors of EGFR/HER2 in breast cancer |
| title_full_unstemmed | Identification of potential therapeutic dual inhibitors of EGFR/HER2 in breast cancer |
| title_short | Identification of potential therapeutic dual inhibitors of EGFR/HER2 in breast cancer |
| title_sort | identification of potential therapeutic dual inhibitors of egfr her2 in breast cancer |
| topic | Dual inhibitor EGFR HER2 Pharmacophore model Docking Molecular dynamics simulation |
| url | http://www.sciencedirect.com/science/article/pii/S2772417424000153 |
| work_keys_str_mv | AT meghajethwa identificationofpotentialtherapeuticdualinhibitorsofegfrher2inbreastcancer AT aditigangopadhyay identificationofpotentialtherapeuticdualinhibitorsofegfrher2inbreastcancer AT achintyasaha identificationofpotentialtherapeuticdualinhibitorsofegfrher2inbreastcancer |