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Published May 14, 2002 | Published
Journal Article Open

Structure-based design of mutant Methanococcus jannaschii tyrosyl-tRNA synthetase for incorporation of O-methyl-L-tyrosine

Abstract

Although incorporation of amino acid analogs provides a powerful means of producing new protein structures with interesting functions, many amino acid analogs cannot be incorporated easily by using the wild-type aminoacyl-tRNA synthetase (aaRS). To be able to incorporate specific amino acid analogs site-specifically, it is useful to build a mutant aaRS that preferentially activates the analog compared with the natural amino acids. Experimental combinatorial studies to find such mutant aaRSs have been successful but can easily become costly and time-consuming. In this article, we describe the clash opportunity progressive (COP) computational method for designing a mutant aaRS to preferentially take up the analog compared with the natural amino acids. To illustrate this COP procedure, we apply it to the design of mutant Methanococcus jannaschii tyrosyl-tRNA synthetase (M.jann-TyrRS). Because the three-dimensional structure for M.jann-TyrRS was not available, we used the STRUCTFAST homology modeling procedure plus molecular dynamics with continuum solvent forces to predict the structure of wild-type M.jann-TyrRS. We validate this structure by predicting the binding site for tyrosine and calculating the binding energies of the 20 natural amino acids, which shows that tyrosine binds the strongest. With the COP design algorithm we then designed a mutant tyrosyl tRNA synthetase to activate O-methyl-l-tyrosine preferentially compared with l-tyrosine. This mutant [Y32Q, D158A] is similar to the mutant designed with combinatorial experiments, [Y32Q, D158A, E107T, L162P], by Wang et al. [Wang, L., Brock, A., Herberich, B. & Schultz, P. G. (2001) Science 292, 498–500]. We predict that the new one will have much greater activity while retaining significant discrimination between O-methyl-l-tyrosine and tyrosine.

Additional Information

© 2002 The National Academy of Sciences. Contributed by William A. Goddard III, March 12, 2002. We thank Dr. Peter G. Schultz, Mr. Lei Wang, and Mr. Sheng Ding for suggesting this project to us. This research was supported by National Institutes of Health/BioEngineering Research Group Grant GM62523. The computing facilities for this project were provided by an IBM Shared University Research grant. The facilities of the Materials and Process Simulation Center used in this project are supported also by the Department of Energy/Accelerated Strategic Computing Initiative/Academic Strategic Alliances Program, National Science Foundation Grants CHE9985574 and MRI99–77872), the National Institutes of Health, the Army Research Office-Multidisciplinary University Research Initiative, Chevron Corp., the Defense Advanced Research Planning Agency, 3M, Seiko–Epson, Avery–Dennison Corp., Kellogg's, General Motors, Beckman Institute, Asahi Chemical, and the Office of Naval Research.

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August 19, 2023
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