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BioinformaticsBioinformatics
Peer-reviewed journal article

Accurate and efficient protein sequence design through learning concise local environment of residues

Bin HuangiD, Tingwen Fan, Kaiyue WangiD, Haicang ZhangiD, Chungong YuiD, Shuyu Nie, Yangshuo Qi, Wei‐Mou ZhengiD, Jian Zhong HaniD, Zheng FaniD, Shiwei SuniD, Sheng YeiD, Huaiyi YangiD, Dongbo BuiD

Abstract

Protein sequence design has been widely applied in rational protein engineering and increasing the design accuracy and efficiency is highly desired. Here we present ProDESIGN-LE, an accurate and efficient design approach, which adopts a concise but informative representation of residues local environment and trains a transformer to select an appropriate residue at a position from its local environment. ProDESIGN-LE iteratively applies the transformer on the positions in the target structure, eventually acquiring a designed sequence with all residues fitting well with their local environments. ProDESIGN-LE designed sequences for 68 naturally occurring and 129 hallucinated proteins within 20 seconds per protein on average, and the predicted structures from the designed sequences perfectly resemble the target structures with state-of-the-art average TM-score exceeding 0.80. We further experimentally validated ProDESIGN-LE by designing five sequences for an enzyme, chloramphenicol O-acetyltransferase type III (CAT III), and recombinantly expressing the proteins in E. coli. Of these proteins, three exhibited excellent solubility, and one yielded monomeric species with circular dichroism spectra consistent with the natural CAT III protein.

02 /Specification & Classification

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