A novel steroid hydroxylase from Nigrospora sphaerica with various hydroxylation capabilities to different steroid
Shuailin Li1, Yaowen Chang1, Yingnan Liu1
1School of Life Science and Biopharmaceutics, Shenyang Pharmaceutical University, Shenyang 110016, Liaoning, People's Republic of China.
Abstract:
Fungal hydroxylation of steroids is a key step in the industrial production of various steroid drugs. The main enzymes that enable these reactions are Cytochrome P450s (CYP), though very few industrially important CYPs have been identified and characterized. In this study, we identified a CYP enzyme (CYP-N2) and a cytochrome P450 reductase (CPRns) from Nigrospora sphaerica 722 by a combination of transcriptome sequencing and heterologous expression in Pichia pastoris. Gene CYP-N2 co-expressed with CPRns in Pichia pastoris GS115 showed 6β- and 15α-hydroxylation activities on progesterone. Different hydroxylation specificity of CYP-N2 was observed on different steroid substrates. CYP-N2 showed 1α-hydroxylation on cortisone and 1α-hydroxylation and 6β-hydroxylation activities on androstenedione (AD). With dehydroepiandrosterone (DHEA) as a substrate, the hydroxylated products of CYP-N2 included 7α-hydroxy-DHEA and 7α,15α-dihydroxy-DHEA. In order to precisely elucidate CYP-N2 biological function and find out the key amino acids influencing its hydroxylation capabilities in the binding pocket, new generation artificial intelligence technology AlphaFold 2 was used to predict the function-structure of CYP-N2 with high reliability. Through molecular docking, it was concluded that the residues almost binding all substrates were located in the same substrate binding pocket and the various hydroxylation abilities might be due to the different binding conformations of different substrates in the binding pocket. Alanine scanning mutagenesis was used to verify key amino acids identified by the molecular docking with steroid substrates. The 128 THR mutation resulted in conversion rate increase for substrates AD and cortisone by 2.6-fold and 2.1-fold respectively. The information obtained in this study is beneficial to facilitating the engineering of more efficient steroid hydroxylases for industrial applications.
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