| Autor: |
Naz S; Biodesign Center, Key Laboratory of Engineering Biology for Low-carbon Manufacturing, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China., Liu P; Biodesign Center, Key Laboratory of Engineering Biology for Low-carbon Manufacturing, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China., Liu C; Biodesign Center, Key Laboratory of Engineering Biology for Low-carbon Manufacturing, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China., Cui M; Biodesign Center, Key Laboratory of Engineering Biology for Low-carbon Manufacturing, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China., Ma H; Biodesign Center, Key Laboratory of Engineering Biology for Low-carbon Manufacturing, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China. |
| Abstrakt: |
Allosteric feedback inhibition of the committed step in amino acid biosynthetic pathways is a major concern for production of amino acids at industrial scale. Anthranilate synthase (AS) catalyzes the first reaction of tryptophan biosynthetic pathway found in microorganisms and is feedback inhibited by its own product i.e. tryptophan. Here, we identified new mutant sites in AS using computational mutagenesis approach. MD simulations (20 ns) followed by MMPBSA and per residue decomposition energy analysis identified seven amino acid residues with best binding affinity for tryptophan. All 19 mutant structures were generated for each identified amino acid residue followed by simulation to evaluate effect of mutation on protein stability. Later, molecular docking studies were employed to generate mutant-tryptophan complex and structures with binding energies (kcal/mol) much higher than wild-type AS were selected. Finally, two mutants i.e., S37W and S37H were identified on the basis of positive binding scores and loss of tryptophan binding inside pocket. Further, MD simulations run for 200 ns were performed over these mutant-tryptophan complexes followed by RMSD, RMSF, radius of gyration , solvent accessible surface area , intra-protein hydrogen bond numbers, principal component analysis, free energy landscape (FEL) and secondary structure analysis to rationale effect of mutations on stability of protein. Cross correlation analysis of mutant site amino acids (S37W) with key residues of catalytic site (G325, T326, H395 and G482) was done to evaluate the effect of mutations on catalytic site conformation. Current computational mutagenesis approach predicted two mutants S37W and S37H with proposed deregulated feedback inhibition by tryptophan and retained catalytic activity.Communicated by Ramaswamy H. Sarma. |
