ReviewMolecules (Basel, Switzerland)2026
Anticancer Peptides: Design Principles, Translational Bottlenecks, and Emerging Opportunities.
Review in Molecules (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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2 authors.
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Abstract
Anticancer peptides (ACPs) are frequently discussed as a single therapeutic class, yet the term encompasses molecules that perform markedly different jobs: direct tumor-cell killing, intracellular target modulation, tumor homing and penetration, or selective delivery of a separate payload. This functional diversity creates opportunity, but it also obscures why many potent peptides fail during translation. In this review, we organize ACPs according to their intended pharmacologic role and examine the molecular and product-development principles that determine whether an active sequence can become a useful medicine. Charge, amphipathicity, conformation, target affinity, cellular entry, protease resistance, tissue exposure, and manufacturability must be optimized as an integrated profile rather than as independent attributes. Representative clinical programs-including the oncolytic peptide LTX-315, the cell-penetrating peptide p28, the stapled peptide ALRN-6924, the tumor-penetrating peptide CEND-1, and the cyclic integrin inhibitor cilengitide-illustrate both the reach of peptide pharmacology and recurrent causes of attrition. We propose a developability-centered workflow that links mechanism, route of administration, pharmacokinetics, pharmacodynamics, biomarker strategy, formulation and chemistry, manufacturing, and controls from the beginning of discovery. For the next generation of ACP development, the most credible opportunities lie in route-matched local or regional therapy, mechanism-based combinations, experimentally constrained artificial intelligence, and peptide-enabled delivery systems supported by fit-for-purpose translational models.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.