High-yield spidroin mimics for bioinspired fibers via computational design

The exceptional mechanical properties, biocompatibility, and biodegradability of spider silk make it a promising biomaterial, yet large-scale production remains hindered by challenges in heterologous expression. Existing prokaryotic systems face bottlenecks due to spidroins' high molecular weight, repetitive sequences, and GC-rich motifs, leading to low yields, premature transcription termination, and insoluble inclusion bodies. Addressing these challenges, the study integrates deep learning and bioengineering to design water-soluble, β-sheet-rich spidroin mimics optimized for efficient prokaryotic expression. By replacing polyalanine motifs in Nephila clavipes MaSp1 with computationally screened sequences (e.g., ITVQQ from Burkholderia OspA), five functional spidroins were engineered and solubly expressed in E. coli, achieving yields up to 0.99 g/L. Circular dichroism revealed that modified spidroins (e.g., 3rep-ITVQQ) exhibited β-sheet content up to 81.3% under thermal induction, surpassing unmodified MaSp1 (41.5%). Structural analysis via SEM demonstrated dense, uniform networks in 3rep-ITVQQ, correlating with enhanced mechanical potential. And 24rep-ITVQQ nanofibers were successfully prepared by electrostatic spinning. Coarse-grained molecular dynamics simulations validated progressive self-assembly with reduced solvent-accessible surface area over 1,000 ns. This work bridges the gap between sequence design and scalable production by overcoming expression barriers, simplifying purification, and leveraging β-sheet stacking for tunable mechanical properties. The results provide a blueprint for high-performance biomimetic fibers, advancing applications (e.g., surgical sutures, scaffolds) in tissue engineering and functional materials while addressing the limitations of conventional spidroin production systems.