Nature offers a rich repertoire of adhesive materials derived from plants, animals, and microorganisms, promising transformative applications in underwater construction and biomedicine. Despite their potential, translating these natural materials into practical applications remains challenging due to a limited understanding of their underlying adhesion mechanisms. To bridge this knowledge gap and accelerate the development of bioinspired adhesives, this work presents a molecular-thermodynamic model for predicting the adhesion forces of mussel-inspired peptides under various solution conditions. The coarse-grained model accounts for the sequence and characteristics of amino-acid residues based on their electrical charge, excluded molecular volume, and nonelectrostatic interactions including the surface binding capability. Its numerical performance was validated with experimental data from surface force measurements for three mussel-inspired peptides. We find that the optimal adhesion to the surface reflects a delicate balance between electrostatic attraction and hydrogen bonding. By incorporating a genetic algorithm to explore the peptide sequence space, we demonstrate that the adhesion strength of mussel-derived peptides can be improved by nearly one-third.

中文翻译：

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通过逆向设计提高青口肽的粘附力


大自然提供了丰富的来自植物、动物和微生物的胶粘剂材料，有望在水下建筑和生物医学中实现变革性应用。尽管它们具有潜力，但由于对其潜在粘附机制的了解有限，将这些天然材料转化为实际应用仍然具有挑战性。为了弥合这一知识差距并加速仿生胶粘剂的发展，本研究提出了一种分子热力学模型，用于预测贻贝启发肽在各种溶液条件下的粘附力。粗粒度模型根据氨基酸残基的电荷、排除的分子量和非静电相互作用（包括表面结合能力）来解释氨基酸残基的顺序和特征。其数值性能通过三种青口启发肽的表面力测量实验数据得到验证。我们发现，对表面的最佳附着力反映了静电吸引和氢键之间的微妙平衡。通过结合遗传算法来探索肽序列空间，我们证明贻贝衍生肽的粘附强度可以提高近三分之一。