Population-based heteropolymer design to mimic protein mixtures
- Univ. of California, Berkeley, CA (United States)
- Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
- Univ. of California, Berkeley, CA (United States); Xiamen Univ. (China). MOE Key Laboratory of Spectrochemical Analysis and Instrumentation
- Univ. of California, Berkeley, CA (United States); Northwestern Univ., Evanston, IL (United States)
- Univ. of California, Berkeley, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Biological fluids, the most complex blends, have compositions that constantly vary and cannot be molecularly defined. Despite these uncertainties, proteins fluctuate, fold, function and evolve as programmed. We propose that in addition to the known monomeric sequence requirements, protein sequences encode multi-pair interactions at the segmental level to navigate random encounters; synthetic heteropolymers capable of emulating such interactions can replicate how proteins behave in biological fluids individually and collectively. Here, we extracted the chemical characteristics and sequential arrangement along a protein chain at the segmental level from natural protein libraries and used the information to design heteropolymer ensembles as mixtures of disordered, partially folded and folded proteins. For each heteropolymer ensemble, the level of segmental similarity to that of natural proteins determines its ability to replicate many functions of biological fluids including assisting protein folding during translation, preserving the viability of fetal bovine serum without refrigeration, enhancing the thermal stability of proteins and behaving like synthetic cytosol under biologically relevant conditions. Molecular studies further translated protein sequence information at the segmental level into intermolecular interactions with a defined range, degree of diversity and temporal and spatial availability. This framework provides valuable guiding principles to synthetically realize protein properties, engineer bio/abiotic hybrid materials and, ultimately, realize matter-to-life transformations.
- Research Organization:
- Argonne National Laboratory (ANL), Argonne, IL (United States). Advanced Photon Source (APS); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- Defense Threat Reduction Agency (DTRA); National Science Foundation (NSF); US Army Research Office (ARO); USDOD; USDOE Office of Science (SC), Basic Energy Sciences (BES). Materials Sciences & Engineering Division (MSE)
- Grant/Contract Number:
- AC02-05CH11231
- OSTI ID:
- 2229313
- Journal Information:
- Nature (London), Journal Name: Nature (London) Journal Issue: 7951 Vol. 615; ISSN 0028-0836
- Publisher:
- Nature Publishing GroupCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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