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Chemical modifications of tRNAs are critical for accurate translation of the genetic code on the ribosome. The discrimination between isoleucine (AUA) and methionine (AUG) codons depends on such modifications of the wobble position in isoleucine tRNA anticodon loops, in all kingdoms of life. Bacteria and archaea employ functionally similar lysine- and agmatine-conjugated cytidine derivatives to ensure decoding fidelity, but the thermodynamics underlying codon discrimination remains unknown. Here, we report structure-based computer simulations that quantitatively reveal the energetics of this decoding strategy in archaea. The results further show that the agmatidine modification confers tRNA specificity primarily by desolvation of the incorrect codon in the non-cognate complex. Tautomerism is found to play no significant role in this decoding system as the usual amino form of the modified tRNA is by far the most stable., (© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

The cationic dummy atom approach provides a powerful nonbonded description for a range of alkaline-earth and transition-metal centers, capturing both structural and electrostatic effects. In this work we refine existing literature parameters for octahedrally coordinated Mn(2+), Zn(2+), Mg(2+), and Ca(2+), as well as providing new parameters for Ni(2+), Co(2+), and Fe(2+). In all the cases, we are able to reproduce both M(2+)-O distances and experimental solvation free energies, which has not been achieved to date for transition metals using any other model. The parameters have also been tested using two different water models and show consistent performance. Therefore, our parameters are easily transferable to any force field that describes nonbonded interactions using Coulomb and Lennard-Jones potentials. Finally, we demonstrate the stability of our parameters in both the human and Escherichia coli variants of the enzyme glyoxalase I as showcase systems, as both enzymes are active with a range of transition metals. The parameters presented in this work provide a valuable resource for the molecular simulation community, as they extend the range of metal ions that can be studied using classical approaches, while also providing a starting point for subsequent parametrization of new metal centers.

Site-directed mutagenesis combined with binding affinity measurements is widely used to probe the nature of ligand interactions with GPCRs. Such experiments, as well as structure-activity relationships for series of ligands, are usually interpreted with computationally derived models of ligand binding modes. However, systematic approaches for accurate calculations of the corresponding binding free energies are still lacking. Here, we report a computational strategy to quantitatively predict the effects of alanine scanning and ligand modifications based on molecular dynamics free energy simulations. A smooth stepwise scheme for free energy perturbation calculations is derived and applied to a series of thirteen alanine mutations of the human neuropeptide Y1 receptor and series of eight analogous antagonists. The robustness and accuracy of the method enables univocal interpretation of existing mutagenesis and binding data. We show how these calculations can be used to validate structural models and demonstrate their ability to discriminate against suboptimal ones.

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.

Neuropeptide Y and peptide YY receptor type 2 (Y2) is involved in appetite regulation and several other physiological processes. We have investigated the structure of the human Y2 receptor. Computational modeling of receptor-agonist interactions was used as a guide to design a series of receptor mutants, followed by binding assays using full-length and truncated peptide agonists and the Y2-specific antagonist BIIE0246. Our model suggested a hydrogen bond network among highly conserved residues Thr2.61, Gln3.32, and His7.39, which could play roles in ligand binding and/or receptor structure. In addition, the C-terminus of the peptide could make contact with residues Tyr5.38 and Leu6.51. Mutagenesis of all these positions, followed by binding assays, provides experimental support for our computational model: most of the mutants for the residues forming the proposed hydrogen bond network displayed reduced peptide agonist affinities as well as reduced hPYY3-36 potency in a functional assay. The Ala and Leu mutants of Gln3.32 and His7.39 disrupted membrane expression of the receptor. Combined with the modeling, the experimental results support roles for these hydrogen bond network residues in peptide binding as well as receptor architecture. The reduced agonist affinity for mutants of Tyr5.38 and Leu6.51 supports their role in a binding pocket surrounding the invariant tyrosine at position 36 of the peptide ligands. The results for antagonist BIIE0246 suggest several differences in interactions compared to those of the peptides. Our results lead to a new structural model for NPY family receptors and peptide binding.

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 three-dimensional 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.

Several of the steps in protein synthesis on the ribosome utilize hydrolysis of guanosine triphosphate (GTP) as the driving force. This reaction is catalyzed by translation factors that become activated upon binding to the ribosome. The recently determined crystal structure of an elongation factor-Tu ternary complex bound to the ribosome allows the energetics of GTP activation to be explored by computer simulations. A central problem regards the role of the universally conserved histidine, which has been proposed to act as a general base for guanosine triphosphate hydrolysis. Here we report a detailed energetic and structural analysis of different possible protonation states that could be involved in activation of the reaction. We show that the histidine cannot act as a general base, but must be protonated and in its active conformation to promote GTP hydrolysis. We further show that the sarcin-ricin loop of the ribosome spontaneously drives the histidine into the correct conformation for GTP activation.

The wealth of structural and biochemical data now available for protein synthesis on the ribosome presents major new challenges for computational biochemistry. Apart from technical difficulties in modeling ribosome systems, the complexity of the overall translation cycle with a multitude of different kinetic steps presents a formidable problem for computational efforts where we have only seen the beginning. However, a range of methodologies including molecular dynamics simulations, free energy calculations, molecular docking and quantum chemical approaches have already been put to work with promising results. In particular, the combined efforts of structural biology, biochemistry, kinetics and computational modeling can lead towards a quantitative structure-based description of translation., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

A broad range of computational methods exist for the estimation of ligand-protein binding affinities. In this chapter we will provide a guide to the linear interaction energy (LIE) method for binding free energy calculations, focusing on the drug design problem. The method is implemented in combination with molecular dynamics (MD) sampling of relevant conformations of the ligands and complexes under consideration. The detailed procedure for MD sampling is followed by key notes in order to properly analyze such sampling and obtain sufficiently accurate estimations of ligand-binding affinities.

The hERG potassium channel is of major pharmaceutical importance, and its blockade by various compounds, potentially causing serious cardiac side effects, is a major problem in drug development. Despite the large amounts of existing biochemical data on blockade of hERG by drugs and druglike compounds, relatively little is known regarding the structural basis of binding of blockers to the channel. Here, we have used a recently developed homology model of hERG to conduct molecular docking experiments with a series of channel blockers, followed by molecular dynamics simulations of the complexes and evaluation of binding free energies with the linear interaction energy method. The calculations yield a remarkably good agreement with experimental binding affinities and allow for a rationalization of three-dimensional structure-activity relationships in terms of a number of key interactions. Two main interaction regions of the channel are thus identified with implications for further mutagenesis experiments and design of new compounds.

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.

Malfunction of hERG potassium channels, due to inherited mutations or inhibition by drugs, can cause long QT syndrome, which can lead to life-threatening arrhythmias. A three-dimensional structure of hERG is a prerequisite to understand the molecular basis of hERG malfunction. To achieve a consensus model, we carried out an extensive analysis of hERG models based on various alignments of helix S5. We analyzed seven models using a combination of conventional geometry/packing/normality validation methods as well as molecular dynamics simulations and molecular docking. A synthetic test set with the X-ray crystal structure of K(v)1.2 with artificially shifted S5 sequences modeled into the structure served as a reference case. We docked the known hERG inhibitors (+)-cisapride, (S)-terfenadine, and MK-499 into the hERG models and simulation snapshots. None of the single analyses unambiguously identified a preferred model, but the combination of all three revealed that there is only one model that fulfils all quality criteria. This model is confirmed by a recent mutation scanning experiment (P. Ju, G. Pages, R. P. Riek, P. C. Chen, A. M. Torres, P. S. Bansal, S. Kuyucak, P. W. Kuchel, J. I. Vandenberg, J. Biol. Chem. 2009, 284, 1000-1008). We expect the modeled structure to be useful as a basis both for computational studies of channel function and kinetics as well as the design of experiments.

Background and Purpose: Human and rat 5-HT(7) receptors were studied with a particular emphasis on the molecular interactions involved in ligand binding, searching for an explanation to the interspecies selectivity observed for a set of compounds. We performed affinity studies, molecular modelling and site-directed mutagenesis, with special focus on residue Phe(7.38) of the human 5-HT(7) receptor [Cys(7.38) in rat]., Experimental Approach: Competition binding studies were performed for seven 5-HT(7) receptor ligands at three different 5-HT(7) receptors. The functional behaviour was evaluated by measuring 5-carboxytryptamine-stimulated cAMP production. Computational simulations were carried out to explore the structural bases in ligand binding observed for these compounds., Key Results: Competition experiments showed a remarkable selectivity for the human receptor when compared with the rat receptor. These results indicate that mutating Cys to Phe at position 7.38 profoundly affects the binding affinities at the 5-HT(7) receptor. Computational simulations provide a structural interpretation for this key finding. Pharmacological characterization of compounds mr25020, mr25040 and mr25053 revealed a competitive antagonistic behaviour. Compounds mr22423, mr22433, mr23284 and mr25052 behaved as partial agonists., Conclusions and Implications: We propose that the interspecies difference in binding affinities observed for the compounds at human and rat 5-HT(7) receptors is due to the nature of the residue at position 7.38. Our molecular modelling simulations suggest that Phe(7.38) in the human receptor is integrated in the hydrophobic pocket in the central part of the binding site [Phe(6.51)-Phe(6.52)] and allows a tighter binding of the ligands when compared with the rat receptor.

Recent progress in elucidating the peptide bond formation process on the ribosome has led to notion of a proton shuttle mechanism where the 2'-hydroxyl group of the P-site tRNA plays a key role in mediating proton transfer between the nucleophile and leaving group, whereas ribosomal groups do not actively participate in the reaction. Despite these advances, the detailed nature of the transition state for peptidyl transfer and the role of several trapped water molecules in the peptidyl transferase center remain major open questions. Here, we employ high-level quantum chemical ab initio calculations to locate and characterize global transition states for the reaction, described by a molecular model encompassing all the key elements of the reaction center. The calculated activation enthalpy as well as structures are in excellent agreement with experimental data and point to feasibility of an eight-membered "double proton shuttle" mechanism in which an auxiliary water molecule, observed both in computer simulations and crystal structures, actively participates. A second conserved water molecule is found to be of key importance for stabilizing developing negative charge on the substrate oxyanion and its presence is catalytically favorable both in terms of activation enthalpy and entropy. Transition states calculated both for six- and eight-membered mechanisms are invariably late and do not involve significant charge development on the attacking amino group. Predicted kinetic isotope effects consistent with this picture are similar to those observed for uncatalyzed ester aminolysis reactions in solution.