摘要：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.
