In termination of protein synthesis, the bacterial release factors RF1 and RF2 bind to the ribosome through specific recognition of messenger RNA stop codons and trigger hydrolysis of the bond between the nascent polypeptide and the transfer RNA at the peptidyl-tRNA site, thereby releasing the newly synthesized protein. The release factors are highly specific for a U in the first stop-codon position and recognize different combinations of purines in the second and third positions, with RF1 reading UAA and UAG and RF2 reading UAA and UGA. With recently determined crystal structures of termination complexes, it has become possible to decipher the energetics of stop-codon reading by computational analysis and to clarify the origin of the high release-factor binding accuracy. Here we report molecular dynamics free-energy calculations on different cognate and non-cognate termination complexes. The simulations quantitatively explain the basic principles of decoding in all three codon positions and reveal the key elements responsible for specificity of the release factors. The overall reading mechanism involves hitherto unidentified interactions and recognition switches that cannot be described in terms of a tripeptide anticodon model. Further simulations of complexes with tRNA(Trp), the tRNA recognizing the triplet codon for Trp, explain the observation of a 'leaky' stop codon and highlight the fundamentally different third position reading by RF2, which leads to a high stop-codon specificity with strong discrimination against the Trp codon. The simulations clearly illustrate the versatility of codon reading by protein, which goes far beyond tRNA mimicry.

The origin of high fidelity in bacterial protein synthesis on the ribosome remains a fundamental unsolved problem despite available three-dimensional structures of different stages of the translation process. However, these structures open up the possibility of directly computing the energetics of tRNA selection that is required for an authentic understanding of fidelity in decoding. Here, we report extensive computer simulations that allow us to quantitatively calculate tRNA discrimination and uncover the energetics underlying accuracy in code translation. We show that the tRNA-mRNA interaction energetics varies drastically along the path from initial selection to peptide bond formation. While the selection process is obviously controlled by kinetics, the underlying thermodynamics explains the origin of the high degree of accuracy. The existence of both low- and high-selectivity states provides an efficient mechanism for initial selection and proofreading that does not require codon-dependent long-range structural signaling within the ribosome. It is instead the distinctly unequal population of the high-selectivity states for cognate and noncognate substrates that is the key discriminatory factor. The simulations reveal the essential roles played both by the 30S subunit conformational switch and by the common tRNA modification at position 37 in amplifying the accuracy.

A key feature of mitochondrial translation is the reduced number of transfer RNAs and reassignment of codons. For human mitochondria, a major unresolved problem is how the set of stop codons are decoded by the release factors mtRF1a and mtRF1. Here we present threedimensional structural models of human mtRF1a and mtRF1 based on their homology to bacterial RF1 in the codon recognition domain, and the strong conservation between mitochondrial and bacterial ribosomal RNA in the decoding region. Sequence changes in the less homologous mtRF1 appear to be correlated with specific features of the mitochondrial rRNA. Extensive computer simulations of the complexes with the ribosomal decoding site show that both mitochondrial factors have similar specificities and that neither reads the putative vertebrate stop codons AGA and AGG. Instead, we present a structural model for a mechanism by which the ICT1 protein causes termination by sensing the presence of these codons in the A-site of stalled ribosomes.

The linear interaction energy (LIE) method to compute binding free energies is applied to lectin-monosaccharide complexes. Here, we calculate the binding free energies of monosaccharides to the Ralstonia solanacearum lectin (RSL) and the Pseudomonas aeruginosa lectin-II (PA-IIL). The standard LIE model performs very well for RSL, whereas the PA-IIL system, where ligand binding involves two calcium ions, presents a major challenge. To overcome this, we explore a new variant of the LIE model, where ligand-metal ion interactions are scaled separately. This model also predicts the saccharide binding preference of PA-IIL on mutation of the receptor, which may be useful for protein engineering of lectins.

The progress of RNA research has suggested a wide variety of RNA molecules as possible targets for pharmaceutical drug molecules. Structure-based computational methods for predicting binding modes and affinities are now important tools in drug discovery, but these methods have mainly been focused on protein targets. Here we employ molecular dynamics free-energy perturbation calculations and the linear interaction energy method to analyze the energetics of ligand binding to purine riboswitches. Calculations are carried out for 14 different purine complexes with the guanine and adenine riboswitches in order to examine their ligand recognition principles. The simulations yield binding affinities in good agreement with experimental data and rationalize the selectivity of the riboswitches for different ligands. In particular, it is found that these receptors have an unusually high degree of electrostatic preorganization for their cognate ligands, and this effect is further quantified by explicit free-energy calculations, which show that the standard electrostatic linear interaction energy parametrization is suboptimal in this case. The adenine riboswitch specifically uses the electrostatic preorganization to discriminate against guanine by preventing the formation of a G-U wobble base pair.