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Discovery of potent ALK tyrosine kinase inhibitors for thyroid cancer via machine learning modeling, molecular docking, MD simulations, and DFT study.

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Title: Discovery of potent ALK tyrosine kinase inhibitors for thyroid cancer via machine learning modeling, molecular docking, MD simulations, and DFT study.
Authors: Anjum, Muhammad Naveed1, Nadeem, Sumaira1,2, Al-Amin, Md.3, Saalim, Muhammad4, Siddique, Farhan1, drfarhansiddique@bzu.edu.pk, Afzal, Samina1, Nisar, Nida1
Source: Computational Biology & Chemistry; Aug2026, Vol. 123, pN.PAG-N.PAG, 1p
Database: Applied Science & Technology Source
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  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 193535284
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Discovery of potent ALK tyrosine kinase inhibitors for thyroid cancer via machine learning modeling, molecular docking, MD simulations, and DFT study.
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1016/j.compbiolchem.2026.108960
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      – Code: eng
        Text: English
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        PageCount: 1
        StartPage: N.PAG
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      – TitleFull: Discovery of potent ALK tyrosine kinase inhibitors for thyroid cancer via machine learning modeling, molecular docking, MD simulations, and DFT study.
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      – PersonEntity:
          Name:
            NameFull: Anjum, Muhammad Naveed
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            NameFull: Nadeem, Sumaira
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            NameFull: Al-Amin, Md.
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            NameFull: Saalim, Muhammad
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            NameFull: Siddique, Farhan
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            NameFull: Afzal, Samina
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          Dates:
            – D: 01
              M: 08
              Text: Aug2026
              Type: published
              Y: 2026
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              Value: 123
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            – TitleFull: Computational Biology & Chemistry
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