Integrated structural and network-based characterization of ABL1 as a central hub in leukemia, using protein interaction and motif analysis with Biopython
Uma Kumari, Shivangi Koundal, Sumita katal · Journal of Emerging Technologies and Innovative Research · 2025
Abelson tyrosine kinase 1 (ABL1) is a critical regulator of cell growth, DNA damage response, cytoskeletal remodeling, and apoptosis, and its dysregulation is central to the development of myeloid leukemia. In this study, an integrated structure-guided computational analysis was performed to characterize the human ABL1 kinase domain using the crystal structure PDB ID: 8I7S. Structural visualization and active-site mapping were conducted using RasMol, while hydrogen bond interactions and structural alignment were analyzed using PyMOL. Protein–protein interaction analysis using the STRING database identified ABL1 as a central signalling hub interacting with adaptor, regulatory, and oncogenic proteins, including CRK, GRB2, CRKL, CBL, ATM, STAT5B, and BCR, with high-confidence interaction scores (≥0.99). B-factor analysis highlighted flexible loop and regulatory regions near the active site, while root mean square deviation (RMSD) analysis demonstrated strong structural conservation of 8I7S compared to reference structures (0.247 Å with 7W7Y and 1.2 Å with 6XR6). Structure validation yielded a high overall quality score of 98.14, with localized deviations restricted to flexible regions. Ramachandran plot analysis, generated using BioPython, confirmed good stereochemical quality, with most residues occupying favoured conformational regions. Sequence and motif annotation using PROSITE identified conserved kinase-specific motifs, including the ATP-binding glycine-rich loop and a catalytic active-site motif, confirming the functional integrity of ABL1(kumari et al 2025).Overall, this comprehensive analysis establishes the structural reliability and functional relevance of ABL1, providing a robust foundation for structure-guided drug design and CRISPR-based therapeutic targeting in myeloid leukemia (Kumari et al., 2023-2025)