In-silico investigation integrated with machine learning to identify potential inhibitors targeting AKT2: Key driver of cancer cell progression and metastasis.

Journal: Computer methods and programs in biomedicine
Published Date: Apr 18, 2025

Abstract

BACKGROUND AND OBJECTIVE: In search of a key driver for the invasive growth of cancer metastasis, AKT2 is found to be exceptionally expressed in colorectal cancer and its metastasis. Again, exceeding genomic arrangements of AKT2 can be held responsible for HGSC (High-grade serous ovarian cancer) and breast cancer cell metastasis. FDA-approved capivasertib, a potential drug targeting the AKT signaling pathway, has a few side effects such as plausible alterations of liver function and gastrointestinal issues. Hence, this research aims to detect compounds with higher drug potency for selective AKT2 inhibition to encounter the incidence of different types of cancer cell metastasis.

Authors

  • Rahat Shahrior
    Department of Biomedical Engineering, Khulna University of Engineering and Technology, Khulna 9203, Bangladesh.
  • Salwa Tamkin
    Department of Computer Science and Engineering, BRAC University, Kha 224, Bir Uttam Rafiqul Islam Avenue, Merul Badda, Dhaka, 1212, Bangladesh.
  • Mohammad Badhruddouza Khan
    Department of Biomedical Engineering, Khulna University of Engineering and Technology, Khulna 9203, Bangladesh.
  • Ahmed Jebail Meraj
    Department of Biomedical Engineering, Khulna University of Engineering and Technology, Khulna 9203, Bangladesh.
  • Hanif Bhuiyan
    Data Scientist, Performance & Analytics Group, City of Gold Coast, Bundall, QLD 4217, Australia. Electronic address: hanifbhuiyan.c@gmail.com.

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