Massively parallel de novo protein design for targeted therapeutics

Aaron Chevalier, Daniel-Adriano Silva, Gabriel J. Rocklin, Derrick R. Hicks, Renan Vergara, Patience Murapa, Steffen M. Bernard, Lu Zhang, Kwok-Ho Lam, Guorui Yao, Christopher D. Bahl, Shin-Ichiro Miyashita, Inna Goreshnik, James T. Fuller, Merika T. Koday, Cody M. Jenkins, Tom Colvin, Lauren Carter, Alan Bohn, Cassie M. BryanD. Alejandro Fernández-Velasco, Lance Stewart, Min Dong, Xuhui Huang, Rongsheng Jin, Ian A. Wilson, Deborah H. Fuller, David Baker

Research output: Contribution to journalArticlepeer-review

311 Scopus citations

Abstract

De novo protein design holds promise for creating small stable proteins with shapes customized to bind therapeutic targets. We describe a massively parallel approach for designing, manufacturing and screening mini-protein binders, integrating large-scale computational design, oligonucleotide synthesis, yeast display screening and next-generation sequencing. We designed and tested 22,660 mini-proteins of 37-43 residues that target influenza haemagglutinin and botulinum neurotoxin B, along with 6,286 control sequences to probe contributions to folding and binding, and identified 2,618 high-affinity binders. Comparison of the binding and non-binding design sets, which are two orders of magnitude larger than any previously investigated, enabled the evaluation and improvement of the computational model. Biophysical characterization of a subset of the binder designs showed that they are extremely stable and, unlike antibodies, do not lose activity after exposure to high temperatures. The designs elicit little or no immune response and provide potent prophylactic and therapeutic protection against influenza, even after extensive repeated dosing.
Original languageEnglish (US)
Pages (from-to)74-79
Number of pages6
JournalNature
Volume550
Issue number7674
DOIs
StatePublished - Sep 27 2017
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: We thank M. Levitt and M. Zhang for discussions, A. Ford for data analysis advice, and Rosetta@Home participants for donating computing time. D.-A.S. thanks T. J. Brunette, J. E. Hsu and M. J. Countryman for their assistance. R.J. thanks K. Perry for X-ray data collection. We acknowledge funding support from: Life Sciences Discovery Fund Launch grant 9598385 (A.C.); PEW Latin-American fellow in the biomedical sciences and a CONACyT postdoctoral fellowship (D.-A.S.); Merck fellow of the Life Sciences Research Foundation (G.J.R.); CONACyT and Doctorado en Ciencias Bioquímicas UNAM (R.V.); NIH (R56AI117675) and Molecular Basis of Viral Pathogenesis Training Grant (T32AI007354-26A1) (S.M.B.); Investigator in the Pathogenesis of Infectious Disease award from the Burroughs Wellcome Fund and NIH (1R01NS080833) (M.D.); CoMotion Mary Gates Innovation Fellow program (T.C.); generous gift from Rocky and Genie Higgins (C.B.); Shenzhen Science and Technology Innovation Committee (JCYJ20170413173837121), Hong Kong Research Grant Council C6009-15G and AoE/P-705/16 (X.H.); PAPIIT UNAM (IN220516), CONACyT (254514) and Facultad de Medicina UNAM (D.A.F.-V.); NIAID grants (AI091823, AI123920, and AI125704) (R.J.); NIAID grant 1R41AI122431 (M.T.K. and D.H.F.); NIAID grant 1R21AI119258 and Life Sciences Discovery Fund grant 20040757 (D.H.F.). We acknowledge computing resources provided by the Supercomputing Laboratory at King Abdullah University of Science and Technology and the Hyak supercomputer system funded by the STF at the University of Washington. The Berkeley Center for Structural Biology is supported in part by the NIH, NIGMS, and HHMI. The Advanced Light Source is a DOE Office of Science User Facility under contract no. DE-AC02-05CH11231. The Northeastern Collaborative Access Team beamlines are funded by NIGMS grant P41 GM103403 and a NIH-ORIP HEI grant (S10OD021527). Advanced Photon Source is a U.S. DOE Office of Science User Facility operated by Argonne National Laboratory under Contract No. DE-AC02-06CH11357.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

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