Peptide design: Starting from known anticancer peptides (ACPs), new amino acid sequences were computationally generated and optimized in iterative design–synthesize–test cycles. The degree of peptide dimerization seems to play a critical role for membranolytic anticancer activity.
Abstract
A computational technique based on a simulated molecular evolution protocol was employed for anticancer peptide (ACP) design. Starting from known ACPs, innovative bioactive peptides were automatically generated in computer‐assisted design–synthesize–test cycles. This design algorithm offers a viable strategy for the generation of novel peptide sequences, without requiring a priori structure–activity knowledge. Sequence morphing and activity improvement were achieved through iterative amino acid variation and selection. Results show that not only the interaction of ACPs with the target membrane is important for their anticancer activity, but also the degree of peptide dimerization, which was corroborated by temperature profiling and electrospray mass spectrometry.
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Although many of the most widely recognized post-translational modifications are characteristic of secretory or cell-surface proteins, most proteins, whatever their ultimate cellular desination, Peptide N-Terminal Modification
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