Future of the Genetic Code

Triphasic Development of the Genetic Code

The genetic code contains an alphabet of genetically encoded amino acids. The ten Phase 1 amino acids, including Gly, Ala, Ser, Asp, Glu, Val, Leu, Ile, Pro and Thr, were available from the prebiotic environment, whereas the ten Phase 2 amino acids, including Phe, Tyr, Arg, His, Trp, Asn, Gln, Lys, Cys, and Met, became available only later from amino acid biosyntheses. In the archaeon Methanopyrus kandleri, the oldest organism known, the standard alphabet of 20 amino acids was "frozen" and no additional amino acid was encoded in the subsequent 3 Gyrs. Four decades ago, it was discovered that the code was frozen because all the organisms were so well adapted to the standard amino acids that oligogenic barriers, consisting of genes that are thoroughly dependent on the standard code, would cause loss of viability upon the deletion of any one amino acid from the code. Once the reason for the freezing of the code was ascertained, procedures were devised by scientists worldwide to enable the encoding of novel noncanonical amino acids (ncAAs). These encoded Phase 3 ncAAs now surpass the 20 canonical Phase 2 amino acids in the code.

Non-Canonical Amino Acids in Analyses of Protease Structure and Function

All known organisms encode 20 canonical amino acids by base triplets in the genetic code. The cellular translational machinery produces proteins consisting mainly of these amino acids. Several hundred natural amino acids serve important functions in metabolism, as scaffold molecules, and in signal transduction. New side chains are generated mainly by post-translational modifications, while others have altered backbones, such as the β- or γ-amino acids, or they undergo stereochemical inversion, e.g., in the case of D-amino acids. In addition, the number of non-canonical amino acids has further increased by chemical syntheses. Since many of these non-canonical amino acids confer resistance to proteolytic degradation, they are potential protease inhibitors and tools for specificity profiling studies in substrate optimization and enzyme inhibition. Other applications include in vitro and in vivo studies of enzyme kinetics, molecular interactions and bioimaging, to name a few. Amino acids with bio-orthogonal labels are particularly attractive, enabling various cross-link and click reactions for structure-functional studies. Here, we cover the latest developments in protease research with non-canonical amino acids, which opens up a great potential, e.g., for novel prodrugs activated by proteases or for other pharmaceutical compounds, some of which have already reached the clinical trial stage.

Genetic codes optimized as a traveling salesman problem

The Standard Genetic Code (SGC) is robust to mutational errors such that frequently occurring mutations minimally alter the physio-chemistry of amino acids. The apparent correlation between the evolutionary distances among codons and the physio-chemical distances among their cognate amino acids suggests an early co-diversification between the codons and amino acids. Here we formulated the co-minimization of evolutionary distances between codons and physio-chemical distances between amino acids as a Traveling Salesman Problem (TSP) and solved it with a Hopfield neural network. In this unsupervised learning algorithm, macromolecules (e.g., tRNAs and aminoacyl-tRNA synthetases) associating codons with amino acids were considered biological analogs of Hopfield neurons associating "tour cities" with "tour positions". The Hopfield network efficiently yielded an abundance of genetic codes that were more error-minimizing than SGC and could thus be used to design artificial genetic codes. We further argue that as a self-optimization algorithm, the Hopfield neural network provides a model of origin of SGC and other adaptive molecular systems through evolutionary learning.

Celebrating wobble decoding: Half a century and still much is new

A simple post-transcriptional modification of tRNA, deamination of adenosine to inosine at the first, or wobble, position of the anticodon, inspired Francis Crick's Wobble Hypothesis 50 years ago. Many more naturally-occurring modifications have been elucidated and continue to be discovered. The post-transcriptional modifications of tRNA's anticodon domain are the most diverse and chemically complex of any RNA modifications. Their contribution with regards to chemistry, structure and dynamics reveal individual and combined effects on tRNA function in recognition of cognate and wobble codons. As forecast by the Modified Wobble Hypothesis 25 years ago, some individual modifications at tRNA's wobble position have evolved to restrict codon recognition whereas others expand the tRNA's ability to read as many as four synonymous codons. Here, we review tRNA wobble codon recognition using specific examples of simple and complex modification chemistries that alter tRNA function. Understanding natural modifications has inspired evolutionary insights and possible innovation in protein synthesis.