The amino acid sequences of peptides determine their self-assembling properties. Accurate prediction of peptidic hydrogel formation, however, remains a challenging task. This work describes an interactive approach involving the mutual information exchange between experiment and machine learning for robust prediction and design of (tetra)peptide hydrogels. We chemically synthesize more than 160 natural tetrapeptides and evaluate their hydrogel-forming ability, and then employ machine learning-experiment iterative loops to improve the accuracy of the gelation prediction. We construct a score function coupling the aggregation propensity, hydrophobicity, and gelation corrector Cg, and generate an 8,000-sequence library, within which the success rate of predicting hydrogel formation reaches 87.1%. Notably, the de novo-designed peptide hydrogel selected from this work boosts the immune response of the receptor binding domain of SARS-CoV-2 in the mice model. Our approach taps into the potential of machine learning for predicting peptide hydrogelator and significantly expands the scope of natural peptide hydrogels.

Chirality correction, asymmetry, ring‐chain tautomerism and hierarchical assemblies are fundamental phenomena in nature. They are geometrically related and may impact the biological roles of a protein or other supermolecules. It is challenging to study those behaviors within an artificial system due to the complexity of displaying these features. Herein, we design an alternating D,L peptide to recreate and validate the naturally occurring chirality inversion prior to cyclization in water. The resulting asymmetrical cyclic peptide containing a 4‐imidazolidinone ring provides an excellent platform to study the ring‐chain tautomerism, thermostability and dynamic assembly of the nanostructures. Different from traditional cyclic D,L peptides, the formation of 4‐imidazolidinone promotes the formation of intertwined nanostructures. Analysis of the nanostructures confirmed the left‐handedness, representing chirality induced self‐assembly. This proves that a rationally designed peptide can mimic multiple natural phenomena and could promote the development of functional biomaterials, catalysts, antibiotics, and supermolecules.

The self-assembly of peptides plays an important role in optics, catalysis, medicine, and disease treatment. In recent years, peptide-based materials have exhibited great potential for cancer therapy and disease imaging due to their excellent biocompatibility, structural tenability, and ease of functionality. Peptides could self-assemble into diverse nanostructures in vivo triggered by endogenous stimuli, which initiated chemical reactions and self-assembled to achieve desired biological functions in the tumor microenvironment.This concept introduces the utilization of endogenous triggers to construct functional nanostructures in vivo and their corresponding biological applications. After briefly discussing the representative example of chemical reactions induced self-assembly of peptides in the living system, we describe the several stimuli triggered self-assembly for constructing therapeutic assemblies and serving as an imaging probe. Finally, we give a brief outlook to discuss the future direction of this exciting new field.

Chirality correction, asymmetry, ring‐chain tautomerism and hierarchical assemblies are fundamental phenomena in nature. They are geometrically related and may impact the biological roles of a protein or other supermolecules. It is challenging to study those behaviors within an artificial system due to the complexity of displaying these features. Herein, we design an alternating D,L peptide to recreate and validate the naturally occurring chirality inversion prior to cyclization in water. The resulting asymmetrical cyclic peptide containing a 4‐imidazolidinone ring provides an excellent platform to study the ring‐chain tautomerism, thermostability and dynamic assembly of the nanostructures. Different from traditional cyclic D,L peptides, the formation of 4‐imidazolidinone promotes the formation of intertwined nanostructures. Analysis of the nanostructures confirmed the left‐handedness, representing chirality induced self‐assembly. This proves that a rationally designed peptide can mimic multiple natural phenomena and could promote the development of functional biomaterials, catalysts, antibiotics, and supermolecules.

The lack of effective treatments for pulmonary diseases poses a global health burden. The direct local gene therapy serves as one of the alternative administrations to treat pulmonary diseases. Compared with the conventional viral/nonviral system, the peptide–vector‐mediated in vivo lung gene therapies exhibit various benefits. However, the related clinical trials are still in their infancy. The major obstacle to the pulmonary delivery of gene cargoes may be the barriers from various extracellular mucosal layers and intracellular membranes. This review highlights the recent development of peptide‐based gene delivery systems and their applications. The peptide designing rules for the barrier‐permeable pulmonary gene delivery are described first. After briefly summarizing how oligopeptides facilitate the local gene therapy in lung tissue with the focus on cell‐penetrating peptides, the local delivery system of the polypeptide and several alternative hybridizing systems of the peptide with other types of materials are discussed. Finally, the blueprint and the remaining challenges in peptide designations are discussed before they enter into the real translation process.