Design of self-assembly dipeptide hydrogels and machine learning via their chemical features

Abstract

Hydrogels that are self-assembled by peptides have attracted great interest for biomedical applications. However, the link between chemical structures of peptides and their corresponding hydrogel properties is still unclear. Here, we showed a combinational approach to generate a structurally diverse hydrogel library with more than 2,000 peptides and evaluated their corresponding properties. We used a quantitative structure-property relationship to calculate their chemical features reflecting the topological and physicochemical properties, and applied machine learning to predict the self-assembly behavior. We observed that the stiffness of hydrogels is correlated with the diameter and cross-linking degree of the nanofiber. Importantly, we demonstrated that the hydrogels support cell proliferation in culture, suggesting the biocompatibility of the hydrogel. The combinatorial hydrogel library and the machine learning approach we developed linked the chemical structures with their self-assembly behavior and can accelerate the design of novel peptide structures for biomedical use.self-assembly | dipeptide hydrogels | machine learning H ydrogels that are cross-linked by three-dimensional networks of modified molecules can maintain a large amount of water without dissolving its own chemical structure, which is very similar to natural tissue. As a result of favorable biocompatibility, hydrogels have great potential in biomedical applications such as drug delivery, tissue engineering, sensing, and cell encapsulation (1-7). In the past few years, considerable attention has been directed toward the design of peptide-based hydrogels in particular, not only because of their favorable features such as easy synthesis, decoration, biodegradability, and high compatibility, but also due to their wide applications in the biological and medical fields (8)(9)(10)(11)(12)(13)(14). However, to the best of our knowledge, the prediction and design of peptide-based hydrogels is still challenging, which limits our research choices on peptide-based hydrogels (15,16). Therefore, the design strategy for hydrogels based on peptides is of great significance. Our aim is to reveal the relationship between molecular structure and hydrogel behavior, which can help us to predict and design peptide hydrogels with new chemical structures.There are approaches using molecular dynamics simulation to model the self-assembly behavior of peptides into different types of nanostructures, including nanofibers, which can subsequently form hydrogels (17)(18)(19). However, it is difficult to evaluate the actual prediction accuracy of the molecular dynamics simulation methods because only a few positive peptides were selected and synthesized to test whether they could form a hydrogel. Additionally, the current reported synthetic method on 9fluorenylmethyloxycarbonyl (Fmoc)-peptide is limited to the traditional peptide synthesis method, involving step-by-step protection and deprotection. Since a high-throughput peptide generation method is not available, our first ...

Controlling the properties of the micellar and gel phase by varying the counterion in functionalised-dipeptide systems

“…5 Computational prediction tools are improving, but are still limited in scope. [6][7][8] Second, it is not possible to predict the properties of the gels if they are formed. These two issues hold the field back and many useful systems are discovered accidentally.…”

“…3). The 7 Li, 23 Na and 133 Cs resonances exhibit quadrupolar splitting while the 87 Rb resonance is significantly broadened relative to the native hydroxide (Fig. S4, ESI †).…”

Progress of new strategies on screening of targeting peptides and applications in tumor immunotherapy

“…(c) The peptides in the microwell array are transferred onto the SPRi through the "imprinting" strategy, which realized qualitative and quantitative analysis simultaneously [15] [19] . (b) 利用深度 学习设计水凝胶自组装行为的筛选程序, 构建文库预测未知水凝胶的形成并指导多肽设计 [22] (网络版彩图) 肽与PD-L1结合形成的复合物晶体结构也为PD-1/PD-L1途径的小分子阻断剂的设计提供了依据 [29,30] . 纳入临床试验的PD-1/PD-L1通路多肽类阻断剂 [36] .…”

“…(a) Real-time screening of high-throughput peptide self-assembly libraries through the orthogonal arrangement of regulatory units by Michael addition reaction strategy[19]. (b) Self-assembled hydrogel design and construction using a deep learning program, which can construct a library to predict the formation of unknown hydrogels as well as guide the peptide design[22] (color online). .…”

On the Mechanical Properties of N-Functionalised Dipeptide Gels

“…Such gelators are able to form gels by self-assembling into a fibrous network that can immobilize the solvent. Gels can be formed in different ways, including pH switches or the in-situ formation of the dipeptide using an enzyme [2,3,6,7]. A highly effective method is to use a solvent switch approach, whereby the dipeptide is first dissolved in a water-miscible organic solvent, such as dimethyl sulfoxide (DMSO), and then water is added [8,9,10,11,12,13,14].…”