Selectivity and specificity of substrate binding in methionyl-tRNA synthetase

Easy Production of "Difficult Peptides" Using Cell-Free Protein Synthesis and a New Methionine Analogue as a Latent Peptide Cleavage Site

Aliphatic γ-chloro-α-amino acids incorporated in place of their canonical analogues through cell-free protein synthesis act as heat-labile linkers, offering a useful strategy for the straightforward production of target peptides as fusion proteins, from which the targets are readily released. Until now, the natural abundance of aliphatic amino acids in peptides has limited the scope of the method, as it leads to undesired cleavage sites in synthesized products, but here the authors report the development of a new cleavable chloro amino acid that incorporates in place of the relatively rare amino acid methionine, thus greatly expanding the scope of producible targets. This new strategy is employed for simplified peptide synthesis with a methionine-free fusion partner, allowing single-site incorporation of the cleavable linker for clean release and easy purification of the target peptide. Its utility is demonstrated through the straightforward preparation of two peptides reported to be challenging targets and not accessible through standard solid-phase chemical methodologies, as well as analogues.

Study of the Binding Energies between Unnatural Amino Acids and Engineered Orthogonal Tyrosyl-tRNA Synthetases

We utilized several computational approaches to evaluate the binding energies of tyrosine (Tyr) and several unnatural Tyr analogs, to several orthogonal aaRSes derived from Methanocaldococcus jannaschii and Escherichia coli tyrosyl-tRNA synthetases. The present study reveals the following: (1) AutoDock Vina and ROSETTA were able to distinguish binding energy differences for individual pairs of favorable and unfavorable aaRS-amino acid complexes, but were unable to cluster together all experimentally verified favorable complexes from unfavorable aaRS-Tyr complexes; (2) MD-MM/PBSA provided the best prediction accuracy in terms of clustering favorable and unfavorable enzyme-substrate complexes, but also required the highest computational cost; and (3) MM/PBSA based on single energy-minimized structures has a significantly lower computational cost compared to MD-MM/PBSA, but still produced sufficiently accurate predictions to cluster aaRS-amino acid interactions. Although amino acid-aaRS binding is just the first step in a complex series of processes to acylate a tRNA with its corresponding amino acid, the difference in binding energy, as shown by MD-MM/PBSA, is important for a mutant orthogonal aaRS to distinguish between a favorable unnatural amino acid (unAA) substrate from unfavorable natural amino acid substrates. Our computational study should assist further designing and engineering of orthogonal aaRSes for the genetic encoding of novel unAAs.

Steric and thermodynamic limits of design for the incorporation of large unnatural amino acids in aminoacyl-tRNA synthetase enzymes

Orthogonal aminoacyl-tRNA synthetase/tRNA pairs from archaea have been evolved to facilitate site specific in vivo incorporation of unnatural amino acids into proteins in Escherichia coli. Using this approach, unnatural amino acids have been successfully incorporated with high translational efficiency and fidelity. In this study, CHARMM-based molecular docking and free energy calculations were used to evaluate rational design of specific protein-ligand interactions for aminoacyl-tRNA synthetases. A series of novel unnatural amino acid ligands were docked into the p-benzoyl-L-phenylalanine tRNA synthetase, which revealed that the binding pocket of the enzyme does not provide sufficient space for significantly larger ligands. Specific binding site residues were mutated to alanine to create additional space to accommodate larger target ligands, and then mutations were introduced to improve binding free energy. This approach was used to redesign binding sites for several different target ligands, which were then tested against the standard 20 amino acids to verify target specificity. Only the synthetase designed to bind Man-alpha-O-Tyr was predicted to be sufficiently selective for the target ligand and also thermodynamically stable. Our study suggests that extensive redesign of the tRNA synthatase binding pocket for large bulky ligands may be quite thermodynamically unfavorable.

Prediction of the 3D structure and dynamics of human DP G-protein coupled receptor bound to an agonist and an antagonist

Prostanoids play important physiological roles in the cardiovascular and immune systems and in pain sensation in peripheral systems through their interactions with eight G-protein coupled receptors. These receptors are important drug targets, but development of subtype specific agonists and antagonists has been hampered by the lack of 3D structures for these receptors. We report here the 3D structure for the human DP G-protein coupled receptor (GPCR) predicted by the MembStruk computational method. To validate this structure, we use the HierDock computational method to predict the binding mode for the endogenous agonist (PGD2) to DP. Based on our structure, we predicted the binding of different antagonists and optimized them. We find that PGD2 binds vertically to DP in the TM1237 region with the alpha chain toward the extracellular (EC) region and the omega chain toward the middle of the membrane. This structure explains the selectivity of the DP receptor and the residues involved in the predicted binding site correlate very well with available mutation experiments on DP, IP, TP, FP, and EP subtypes. We report molecular dynamics of DP in explicit lipid and water and find that the binding of the PGD2 agonist leads to correlated rotations of helices of TM3 and TM7, whereas binding of antagonist leads to no such rotations. Thus, these motions may be related to the mechanism of activation.

Prediction of the 3-D structure of rat MrgA G protein-coupled receptor and identification of its binding site

Mrg receptors are orphan G protein-coupled receptors (GPCRs) located mainly at the specific set of sensory neurons in the dorsal root ganglia, suggesting a role in nociception. We report here the 3-D structure of rat MrgA (rMrgA) receptor [obtained from homology modeling to the recently validated predicted structures of mouse MrgA1 and MrgC11] and the structure of adenine (a known agonist, K(i)=18nM) bound to rMrgA. This predicted binding site is located within transmembrane helical domains (TMs) 3, 4, 5 and 6, with Asn residues in TM3 and TM4 identified as the key residues for adenine binding. Here the side chain of Asn88 (TM3) forms two pairs of hydrogen bonds with N3 and N9 of adenine while Asn146 (TM4) makes two pairs of hydrogen bonds with N1 and N6 of adenine. These interactions lock adenine tightly in the binding pocket. We also predict the binding site of guanine (not an agonist) and seven other derivatives. Guanine cannot make the hydrogen bond to Asn146 (TM4), leading to binding too weak to be observed experimentally. The predicted binding affinity for other adenine derivatives correlates with the availability of the hydrogen bonds to these two Asn residues. These results validate the predicted structure for rat MrgA and suggest mutation experiments that could further validate the structure. Moreover, the predicted structure and binding site should be useful for seeking other small molecule agonists and antagonists.

Fidelity of seryl-tRNA synthetase to binding of natural amino acids from HierDock first principles computations

Seryl-tRNA synthetase (SerRS) charges serine to tRNA(Ser) following the formation of a seryl adenylate intermediate, but the extent to which other non-cognate amino acids compete with serine to bind to SerRS or for the formation of the activated seryl adenylate intermediate is not known. To examine the mechanism of discrimination against non-cognate amino acids, we calculated the relative binding energies of the 20 natural amino acids to SerRS. Starting with the crystal structure of SerRS from Thermus thermophilus with seryl adenylate bound, we used the HierDock and SCREAM (Side-Chain Rotamer Energy Analysis Method) computational methods to predict the binding conformation and binding energy of each of the 20 natural amino acids in the binding site in the best-binding mode and the activating mode. The ordering of the calculated binding energies in the activated mode agrees with kinetic measurements in yeast SerRS that threonine will compete with serine for formation of the activated intermediate while alanine and glycine will not compete significantly. In addition, we predict that asparagine will compete with serine for formation of the activated intermediate. Experiments to check the accuracy of this prediction would be useful in further validating the use of HierDock and SCREAM for designing novel amino acids to incorporate into proteins and for determining mutations in aminoacyl-tRNA synthetase design to facilitate the incorporation of amino acid analogs into proteins.