Next Generation Sequencing and Insilico Identification of Human Anaplastic Lymphoma Kinase in Human Cancer with Biopython

Abstract

Abstract: In this comprehensive molecular investigation, the focus centers on the anaplastic lymphoma kinase (ALK) within the context of lung cancer. Specifically, utilizing the sample with the PDB code 3AOX, the study employs a multifaceted approach combining advanced bioinformatics tools and structural biology methodologies.Commencing with RasMol, the analysis of the protein sample reveals a complex network of 196 hydrogen bonds within the ALK structure. This foundational information sets the stage for subsequent investigations. Visual representation is meticulously addressed, with RasMol utilized for color-coding alpha helices in magenta, beta helices in yellow, and the remaining residues in white. The presentation mode emphasizes helices in red, sheets in yellow, and loops in green, providing a vivid depiction of the structural elements within the ALK protein.Moving beyond visualization, PyMOL is engaged to represent the surface form, providing insights into the interactions between ALK and its environment. This is particularly crucial in understanding the structural dynamics of ALK in the context of lung cancer, where the protein sample serves as a representative model.Active site identification in Chain A is pursued using tools such as PyMol, offering a glimpse into potential functional regions crucial for ALK's role in lung cancer pathogenesis. The study extends to biophysical aspects, incorporating protein-ligand docking studies with Mektovi and Almita through CB DOCK. This approach sheds light on the intricate molecular interactions between ALK and specific ligands, providing valuable information for targeted therapies.Structural validation becomes paramount in ensuring the reliability of the 3AOX sample. The ERRAT structure validation server evaluates the overall quality factor, while Procheck on the SAVES server scrutinizes the Ramachandran plot, ensuring the conformational consistency of ALK's backbone dihedral angles.Biopython scripts play a pivotal role in extracting and analyzing data related to the alpha-beta class representation within the CATH database. This bioinformatics analysis adds another layer of understanding to ALK's structural classification, offering insights into its role in lung cancer.