Advances in Hematology and Oncology Research(AHOR)

Delhi Public School East, Bangalore, India

Publications

• Research Article   
  A Novel Machine Learning Approach to PTEN Missense Variant Classification Using Alpha Fold 3
  Author(s): Yash Jayesh Laddha*, Arwen Shah and Shubh Jayesh Laddha
  
  PTEN is among the most commonly mutated tumor suppressor genes across human cancers. Yet, hundreds of its missense variants remain classified as variants of uncertain significance (VUS), limiting clinicians' ability to assess cancer risk. Existing predictors rely mainly on sequence conservation and cannot evaluate the three-dimensional structural changes that influence PTEN function, leaving a significant gap in variant classification. This study aimed to determine whether structural changes caused by PTEN missense mutations could reliably distinguish cancer-associated variants from benign ones. All known PTEN missense variants were collected from UniProt, and structural models were generated using Alpha Fold 3 for the wild type and 1,514 mutant sequences. After aligning each mutant to the wild-type structure, seventeen structural features were extracted using PyMOL, Bio python, a.. Read More»
  

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