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• W4381996522 abstract "Targeted delivery of therapeutic anticancer chimeric molecules enhances the efficacy of drug by improving cellular uptake and circulation time. Engineering the molecules to facilitate the specific interaction between chimeric protein and its receptor is critical to elucidate biological mechanism as well as accuracy in modeling of complexes. A theoretically designed novel protein-protein interfaces can serve as a bottom-up method for comprehensive understanding of interacting protein residues. This study was aimed for in silico analyses of a chimeric fusion protein against breast cancer. The amino acid sequences of the interleukin 24 (IL-24) and LK-6 peptide were used to design the chimeric fusion protein via a rigid linker. The secondary and tertiary structures along with physicochemical properties by ProtParam and solubility were predicted using online software. The validation and quality of the fusion protein was confirmed by Rampage and ERRAT2. The newly designed fusion construct has a total length of 179 amino acids. The top-ranked structure from alpha fold2 showed 18.1 KD molecular weight by ProtParam, quality factor of 94.152 by ERRAT, and a valid structure by a Ramachandran plot with 88.5% residues in the favored region. Finally, the docking and simulation studies were performed using HADDOCK and Desmond module of Schrodinger. The quality, validity, interaction analysis, and stability of the fusion protein depict a functional molecule. The fusion gene IL24-LK6 after cloning and expression in a suitable prokaryotic cell might be a useful candidate for developing a novel anticancer therapy." @default.
• W4381996522 created "2023-06-26" @default.
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• W4381996522 date "2023-01-01" @default.
• W4381996522 modified "2023-10-01" @default.
• W4381996522 title "In Silico Investigation of a Chimeric IL24-LK6 Fusion Protein as a Potent Candidate Against Breast Cancer" @default.
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• W4381996522 doi "https://doi.org/10.1177/11779322231182560" @default.
• W4381996522 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37377793" @default.
• W4381996522 hasPublicationYear "2023" @default.
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