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      Computational Aminoacyl-tRNA Synthetase Library Design for Photocaged Tyrosine

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          Abstract

          Engineering aminoacyl-tRNA synthetases (aaRSs) provides access to the ribosomal incorporation of noncanonical amino acids via genetic code expansion. Conventional targeted mutagenesis libraries with 5–7 positions randomized cover only marginal fractions of the vast sequence space formed by up to 30 active site residues. This frequently results in selection of weakly active enzymes. To overcome this limitation, we use computational enzyme design to generate a focused library of aaRS variants. For aaRS enzyme redesign, photocaged ortho-nitrobenzyl tyrosine (ONBY) was chosen as substrate due to commercial availability and its diverse applications. Diversifying 17 first- and second-shell sites and performing conventional aaRS positive and negative selection resulted in a high-activity aaRS. This MjTyrRS variant carries ten mutations and outperforms previously reported ONBY-specific aaRS variants isolated from traditional libraries. In response to a single in-frame amber stop codon, it mediates the in vivo incorporation of ONBY with an efficiency matching that of the wild type MjTyrRS enzyme acylating cognate tyrosine. These results exemplify an improved general strategy for aaRS library design and engineering.

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          ROSETTA3: an object-oriented software suite for the simulation and design of macromolecules.

          We have recently completed a full re-architecturing of the ROSETTA molecular modeling program, generalizing and expanding its existing functionality. The new architecture enables the rapid prototyping of novel protocols by providing easy-to-use interfaces to powerful tools for molecular modeling. The source code of this rearchitecturing has been released as ROSETTA3 and is freely available for academic use. At the time of its release, it contained 470,000 lines of code. Counting currently unpublished protocols at the time of this writing, the source includes 1,285,000 lines. Its rapid growth is a testament to its ease of use. This chapter describes the requirements for our new architecture, justifies the design decisions, sketches out central classes, and highlights a few of the common tasks that the new software can perform. © 2011 Elsevier Inc. All rights reserved.
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            Adding new chemistries to the genetic code.

            The development of new orthogonal aminoacyl-tRNA synthetase/tRNA pairs has led to the addition of approximately 70 unnatural amino acids (UAAs) to the genetic codes of Escherichia coli, yeast, and mammalian cells. These UAAs represent a wide range of structures and functions not found in the canonical 20 amino acids and thus provide new opportunities to generate proteins with enhanced or novel properties and probes of protein structure and function.
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              Conformer Generation with OMEGA: Algorithm and Validation Using High Quality Structures from the Protein Databank and Cambridge Structural Database

              Here, we present the algorithm and validation for OMEGA, a systematic, knowledge-based conformer generator. The algorithm consists of three phases: assembly of an initial 3D structure from a library of fragments; exhaustive enumeration of all rotatable torsions using values drawn from a knowledge-based list of angles, thereby generating a large set of conformations; and sampling of this set by geometric and energy criteria. Validation of conformer generators like OMEGA has often been undertaken by comparing computed conformer sets to experimental molecular conformations from crystallography, usually from the Protein Databank (PDB). Such an approach is fraught with difficulty due to the systematic problems with small molecule structures in the PDB. Methods are presented to identify a diverse set of small molecule structures from cocomplexes in the PDB that has maximal reliability. A challenging set of 197 high quality, carefully selected ligand structures from well-solved models was obtained using these methods. This set will provide a sound basis for comparison and validation of conformer generators in the future. Validation results from this set are compared to the results using structures of a set of druglike molecules extracted from the Cambridge Structural Database (CSD). OMEGA is found to perform very well in reproducing the crystallographic conformations from both these data sets using two complementary metrics of success.
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                Author and article information

                Journal
                Int J Mol Sci
                Int J Mol Sci
                ijms
                International Journal of Molecular Sciences
                MDPI
                1422-0067
                11 May 2019
                May 2019
                : 20
                : 9
                : 2343
                Affiliations
                [1 ]Institut für Chemie, Technische Universität Berlin, Müller-Breslau-Straße 10, 10623 Berlin, Germany; tobias.baumann@ 123456tu-berlin.de (T.B.); matthias.hauf@ 123456tu-berlin.de (M.H.)
                [2 ]Biophysikalische Chemie, Institut für Biologie, Humboldt-Universität zu Berlin, 10115 Berlin, Germany; flosopher@ 123456gmail.com (F.R.); andreas.moeglich@ 123456uni-bayreuth.de (A.M.)
                [3 ]Institute of Biochemistry and Molecular Biology, University of Hamburg, 20146 Hamburg, Germany; albers@ 123456chemie.uni-hamburg.de (S.A.); zoya.ignatova@ 123456chemie.uni-hamburg.de (Z.I.)
                [4 ]Lehrstuhl für Biochemie, Universität Bayreuth, 95447 Bayreuth, Germany
                [5 ]Department of Chemistry, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
                Author notes
                [* ]Correspondence: nediljko.budisa@ 123456tu-berlin.de or nediljko.budisa@ 123456umanitoba.ca ; Tel.: +49-30-314-28821 or +1-204-474-9178
                [†]

                These authors contributed equally to this manuscript.

                [‡]

                Present address: Bayer AG, Pharmaceuticals, Protein Engineering and Assays, Nattermannallee 1, 50829 Köln, Germany.

                Author information
                https://orcid.org/0000-0001-7480-7809
                https://orcid.org/0000-0002-7382-2772
                https://orcid.org/0000-0001-8437-7304
                Article
                ijms-20-02343
                10.3390/ijms20092343
                6539999
                31083552
                48c459da-ddc2-456d-b7c9-2eaf4f5dd1cc
                © 2019 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 16 April 2019
                : 09 May 2019
                Categories
                Article

                Molecular biology
                enzyme design,noncanonical amino acids,protein modification,directed evolution,mutagenesis,gene libraries,genetic code expansion,unnatural amino acids,protein engineering

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