title: Protein design with a comprehensive statistical energy function and boosted by experimental selection for foldability.
abstract: The de novo design of amino acid sequences to fold into desired structures is a way to reach a more thorough understanding of how amino acid sequences encode protein structures and to supply methods for protein engineering. Notwithstanding significant breakthroughs, there are noteworthy limitations in current computational protein design. To overcome them needs computational models to complement current ones and experimental tools to provide extensive feedbacks to theory. Here we develop a comprehensive statistical energy function for protein design with a new general strategy and verify that it can complement and rival current well-established models. We establish that an experimental approach can be used to efficiently assess or improve the foldability of designed proteins. We report four de novo proteins for different targets, all experimentally verified to be well-folded, solved solution structures for two being in excellent agreement with respective design targets.
authors.affiliation: School of Life Sciences, University of Science and Technology of China, 443 Huangshan Road, Hefei, Anhui 230027, China.
authors.forename: Peng
authors.initials: P
authors.lastname: Xiong
authors.affiliation: School of Life Sciences, University of Science and Technology of China, 443 Huangshan Road, Hefei, Anhui 230027, China.
authors.forename: Meng
authors.initials: M
authors.lastname: Wang
authors.affiliation: School of Life Sciences, University of Science and Technology of China, 443 Huangshan Road, Hefei, Anhui 230027, China.
authors.forename: Xiaoqun
authors.initials: X
authors.lastname: Zhou
authors.affiliation: School of Life Sciences, University of Science and Technology of China, 443 Huangshan Road, Hefei, Anhui 230027, China.
authors.forename: Tongchuan
authors.initials: T
authors.lastname: Zhang
authors.affiliation: School of Life Sciences, University of Science and Technology of China, 443 Huangshan Road, Hefei, Anhui 230027, China.
authors.forename: Jiahai
authors.initials: J
authors.lastname: Zhang
authors.affiliation: School of Life Sciences, University of Science and Technology of China, 443 Huangshan Road, Hefei, Anhui 230027, China.
authors.forename: Quan
authors.initials: Q
authors.lastname: Chen
authors.affiliation: 1] School of Life Sciences, University of Science and Technology of China, 443 Huangshan Road, Hefei, Anhui 230027, China [2] Hefei National Laboratory for Physical Sciences at the Microscales, Hefei, Anhui 230027, China [3] Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui 230031, China.
authors.forename: Haiyan
authors.initials: H
authors.lastname: Liu
mesh_terms: D000595:Amino Acid Sequence; D019020:Directed Molecular Evolution; D004352:Drug Resistance, Microbial; D009682:Magnetic Resonance Spectroscopy; D008969:Molecular Sequence Data; D050505:Mutant Proteins / Q000737:chemistry / Q000378:metabolism; D015202:Protein Engineering / Q000379:methods*; D017510:Protein Folding; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*; D012996:Solutions; D013223:Statistics as Topic; D013816:Thermodynamics; D001618:beta-Lactamases / Q000378:metabolism
chemical_list: D050505:Mutant Proteins; D011506:Proteins; D012996:Solutions; D001618:beta-Lactamases