Self-assembling peptides are biomedical materials with unique structures that are formed in response to various environmental conditions. Governed by their physicochemical characteristics, the peptides can form a variety of structures with greater reactivity than conventional non-biological materials. The structural divergence of self-assembling peptides allows for various functional possibilities; when assembled, they can be used as scaffolds for cell and tissue regeneration, and vehicles for drug delivery, conferring controlled release, stability, and targeting, and avoiding side effects of drugs. These peptides can also be used as drugs themselves. In this review, we describe the basic structure and characteristics of self-assembling peptides and the various factors that affect the formation of peptide-based structures. We also summarize the applications of self-assembling peptides in the treatment of various diseases, including cancer. Furthermore, the in-cell self-assembly of peptides, termed reverse self-assembly, is discussed as a novel paradigm for self-assembling peptide-based nanovehicles and nanomedicines.

Detecting amyloid beta (Aβ) in unpurified blood to diagnose Alzheimer’s disease (AD) is challenging owing to low concentrations of Aβ and the presence of many other substances in the blood. Here, we propose a 3D sensor for AD diagnosis using blood plasma, with pairs of 3D silicon micropillar electrodes with a comprehensive circuit configuration. The sensor is developed with synthesized artificial peptide and impedance analysis based on a maximum signal-to-noise ratio. Its sensitivity and selectivity were verified using an in vitro test based on samples of human blood serum, which showed its feasibility for application in diagnosis of AD by testing blood plasma of the AD patient. The 3D sensor is designed to improve reliability by checking the impedance of each pair multiple times via constructing a reference pair and a working pair on the same sensor. Therefore, we demonstrate the ability of the 3D sensor to recognize cases of AD using blood plasma and introduce its potential as a self-health care sensor for AD patients.