Predicting rates of in vivo degradation of recombinant spider silk proteins.

Developing fundamental tools and insight into biomaterial designs for predictive functional outcomes remains critical for the field. Silk is a promising candidate as a biomaterial for tissue engineering scaffolds, particularly where high mechanical loads or slow rates of degradation are desirable. Although bioinspired synthetic spider silks are feasible biomaterials for this purpose, insight into how well the degradation rate can be programmed by fine tuning the sequence remains to be determined. Here we integrated experimental approaches and computational modelling to investigate the degradation of two bioengineered spider silk block copolymers, H(AB)2 and H(AB)12 , which were designed based on the consensus domains of Nephila clavipes dragline silk. The effect of protein chain length and secondary structure on degradation was analysed in vivo. The degradation rate of H(AB)12 , the silk with longer chain length/higher molecular weight, and higher crystallinity, was slower when compared to H(AB)2 . Using full atomistic modelling, it was determined that the faster degradation of H(AB)2 was due to the lower folded molecular structure of the silk and the greater accessibility to solvent. Comparison of the specific surface areas of proteins via modelling showed that higher exposure of random coil and lower exposure of ordered domains in H(AB)2 led to the more reactive silk with a higher degradation rate when compared with H(AB)12 , as validated by the experimental results. The study, based on two simple silk designs demonstrated that the control of sequence can lead to programmable degradation rates for these biomaterials, providing a suitable model system with which to study variables in protein polymer design to predict degradation rates in vivo. This approach should reduce the use of animal screening, while also accelerating translation of such biomaterials for repair and regenerative systems.