Combined simulation and mutagenesis analyses reveal the involvement of key residues for peroxisome proliferator-activated receptor alpha helix 12 dynamic behavior.

The dynamic properties of helix 12 in the ligand binding domain of nuclear receptors are a major determinant of AF-2 domain activity. We investigated the molecular and structural basis of helix 12 mobility, as well as the involvement of individual residues with regard to peroxisome proliferator-activated receptor alpha (PPARalpha) constitutive and ligand-dependent transcriptional activity. Functional assays of the activity of PPARalpha helix 12 mutants were combined with free energy molecular dynamics simulations. The agreement between the results from these approaches allows us to make robust claims concerning the mechanisms that govern helix 12 functions. Our data support a model in which PPARalpha helix 12 transiently adopts a relatively stable active conformation even in the absence of a ligand. This conformation provides the interface for the recruitment of a coactivator and results in constitutive activity. The receptor agonists stabilize this conformation and increase PPARalpha transcription activation potential. Finally, we disclose important functions of residues in PPARalpha AF-2, which determine the positioning of helix 12 in the active conformation in the absence of a ligand. Substitution of these residues suppresses PPARalpha constitutive activity, without changing PPARalpha ligand-dependent activation potential.

T-Cell Receptors Binding Orientation over Peptide/MHC Class I Is Driven by Long-Range Interactions.

Crystallographic data about T-Cell Receptor - peptide - major histocompatibility complex class I (TCRpMHC) interaction have revealed extremely diverse TCR binding modes triggering antigen recognition. Understanding the molecular basis that governs TCR orientation over pMHC is still a considerable challenge. We present a simplified rigid approach applied on all non-redundant TCRpMHC crystal structures available. The CHARMM force field in combination with the FACTS implicit solvation model is used to study the role of long-distance interactions between the TCR and pMHC. We demonstrate that the sum of the coulomb interactions and the electrostatic solvation energies is sufficient to identify two orientations corresponding to energetic minima at 0° and 180° from the native orientation. Interestingly, these results are shown to be robust upon small structural variations of the TCR such as changes induced by Molecular Dynamics simulations, suggesting that shape complementarity is not required to obtain a reliable signal. Accurate energy minima are also identified by confronting unbound TCR crystal structures to pMHC. Furthermore, we decompose the electrostatic energy into residue contributions to estimate their role in the overall orientation. Results show that most of the driving force leading to the formation of the complex is defined by CDR1,2/MHC interactions. This long-distance contribution appears to be independent from the binding process itself, since it is reliably identified without considering neither short-range energy terms nor CDR induced fit upon binding. Ultimately, we present an attempt to predict the TCR/pMHC binding mode for a TCR structure obtained by homology modeling. The simplicity of the approach and the absence of any fitted parameters make it also easily applicable to other types of macromolecular protein complexes.

The dynamics of the Swiss electricity market : three essays

Executive Summary Electricity is crucial for modern societies, thus it is important to understand the behaviour of electricity markets in order to be prepared to face the consequences of policy changes. The Swiss electricity market is now in a transition stage from a public monopoly to a liberalised market and it is undergoing an "emergent" liberalisation - i.e. liberalisation taking place without proper regulation. The withdrawal of nuclear capacity is also being debated. These two possible changes directly affect the mechanisms for capacity expansion. Thus, in this thesis we concentrate on understanding the dynamics of capacity expansion in the Swiss electricity market. A conceptual model to help understand the dynamics of capacity expansion in the Swiss electricity market is developed an explained in the first essay. We identify a potential risk of imports dependence. In the second essay a System Dynamics model, based on the conceptual model, is developed to evaluate the consequences of three scenarios: a nuclear phase-out, the implementation of a policy for avoiding imports dependence, and the combination of both. We conclude that the Swiss market is not well prepared to face unexpected changes of supply and demand, and we identify a risk of imports dependence, mainly in the case of a nuclear phase-out. The third essay focus on the opportunity cost of hydro-storage power generation, one of the main generation sources in Switzerland. We use and extended version of our model to test different policies for assigning an opportunity cost to hydro-storage power generation. We conclude that the preferred policies are different for different market participants and depend on market structure.

Constitutively active mutants of the alpha 1B-adrenergic receptor: role of highly conserved polar amino acids in receptor activation.

Site-directed mutagenesis and molecular dynamics simulations of the alpha 1B-adrenergic receptor (AR) were combined to explore the potential molecular changes correlated with the transition from R (inactive state) to R (active state). Using molecular dynamics analysis we compared the structural/dynamic features of constitutively active mutants with those of the wild type and of an inactive alpha 1B-AR to build a theoretical model which defines the essential features of R and R. The results of site-directed mutagenesis were in striking agreement with the predictions of the model supporting the following hypothesis. (i) The equilibrium between R and R depends on the equilibrium between the deprotonated and protonated forms, respectively, of D142 of the DRY motif. In fact, replacement of D142 with alanine confers high constitutive activity to the alpha 1B-AR. (ii) The shift of R143 of the DRY sequence out of a conserved 'polar pocket' formed by N63, D91, N344 and Y348 is a feature common to all the active structures, suggesting that the role of R143 is fundamental for mediating receptor activation. Disruption of these intramolecular interactions by replacing N63 with alanine constitutively activates the alpha 1B-AR. Our findings might provide interesting generalities about the activation process of G protein-coupled receptors.

Molecular determinants of desensitization in an ENaC/degenerin channel.

Epithelial Na(+) channel (ENaC)/degenerin family members are involved in mechanosensation, blood pressure control, pain sensation, and the expression of fear. Several of these channel types display a form of desensitization that allows the channel to limit Na(+) influx during prolonged stimulation. We used site-directed mutagenesis and chemical modification, functional analysis, and molecular dynamics simulations to investigate the role of the lower palm domain of the acid-sensing ion channel 1, a member of the ENaC/degenerin family. The lower palm domains of this trimeric channel are arranged around a central vestibule, at ∼20 Å above the plasma membrane and are covalently linked to the transmembrane channel parts. We show that the lower palm domains approach one another during desensitization. Residues in the palm co-determine the pH dependence of desensitization, its kinetics, and the stability of the desensitized state. Mutations of palm residues impair desensitization by preventing the closing movement of the palm. Overexpression of desensitization-impaired channel mutants in central neurons allowed--in contrast to overexpression of wild type--a sustained signaling response to rapid pH fluctuations. We identify and describe here the function of an important regulatory domain that most likely has a conserved role in ENaC/degenerin channels.

Molecular modeling of peptide-MHC class I complexes : applications to peptide based immunotherapy

Summary The specific CD8+ T cell immune response against tumors relies on the recognition by the T cell receptor (TCR) on cytotoxic T lymphocytes (CTL) of antigenic peptides bound to the class I major histocompatibility complex (MHC) molecule. Such tumor associated antigenic peptides are the focus of tumor immunotherapy with peptide vaccines. The strategy for obtaining an improved immune response often involves the design of modified tumor associated antigenic peptides. Such modifications aim at creating higher affinity and/or degradation resistant peptides and require precise structures of the peptide-MHC class I complex. In addition, the modified peptide must be cross-recognized by CTLs specific for the parental peptide, i.e. preserve the structure of the epitope. Detailed structural information on the modified peptide in complex with MHC is necessary for such predictions. In this thesis, the main focus is the development of theoretical in silico methods for prediction of both structure and cross-reactivity of peptide-MHC class I complexes. Applications of these methods in the context of immunotherapy are also presented. First, a theoretical method for structure prediction of peptide-MHC class I complexes is developed and validated. The approach is based on a molecular dynamics protocol to sample the conformational space of the peptide in its MHC environment. The sampled conformers are evaluated using conformational free energy calculations. The method, which is evaluated for its ability to reproduce 41 X-ray crystallographic structures of different peptide-MHC class I complexes, shows an overall prediction success of 83%. Importantly, in the clinically highly relevant subset of peptide-HLAA*0201 complexes, the prediction success is 100%. Based on these structure predictions, a theoretical approach for prediction of cross-reactivity is developed and validated. This method involves the generation of quantitative structure-activity relationships using three-dimensional molecular descriptors and a genetic neural network. The generated relationships are highly predictive as proved by high cross-validated correlation coefficients (0.78-0.79). Together, the here developed theoretical methods open the door for efficient rational design of improved peptides to be used in immunotherapy. Résumé La réponse immunitaire spécifique contre des tumeurs dépend de la reconnaissance par les récepteurs des cellules T CD8+ de peptides antigéniques présentés par les complexes majeurs d'histocompatibilité (CMH) de classe I. Ces peptides sont utilisés comme cible dans l'immunothérapie par vaccins peptidiques. Afin d'augmenter la réponse immunitaire, les peptides sont modifiés de façon à améliorer l'affinité et/ou la résistance à la dégradation. Ceci nécessite de connaître la structure tridimensionnelle des complexes peptide-CMH. De plus, les peptides modifiés doivent être reconnus par des cellules T spécifiques du peptide natif. La structure de l'épitope doit donc être préservée et des structures détaillées des complexes peptide-CMH sont nécessaires. Dans cette thèse, le thème central est le développement des méthodes computationnelles de prédiction des structures des complexes peptide-CMH classe I et de la reconnaissance croisée. Des applications de ces méthodes de prédiction à l'immunothérapie sont également présentées. Premièrement, une méthode théorique de prédiction des structures des complexes peptide-CMH classe I est développée et validée. Cette méthode est basée sur un échantillonnage de l'espace conformationnel du peptide dans le contexte du récepteur CMH classe I par dynamique moléculaire. Les conformations sont évaluées par leurs énergies libres conformationnelles. La méthode est validée par sa capacité à reproduire 41 structures des complexes peptide-CMH classe I obtenues par cristallographie aux rayons X. Le succès prédictif général est de 83%. Pour le sous-groupe HLA-A*0201 de complexes de grande importance pour l'immunothérapie, ce succès est de 100%. Deuxièmement, à partir de ces structures prédites in silico, une méthode théorique de prédiction de la reconnaissance croisée est développée et validée. Celle-ci consiste à générer des relations structure-activité quantitatives en utilisant des descripteurs moléculaires tridimensionnels et un réseau de neurones couplé à un algorithme génétique. Les relations générées montrent une capacité de prédiction remarquable avec des valeurs de coefficients de corrélation de validation croisée élevées (0.78-0.79). Les méthodes théoriques développées dans le cadre de cette thèse ouvrent la voie du design de vaccins peptidiques améliorés.

Lack of Enantioselectivity in the SULT1A3-catalyzed Sulfoconjugation of Normetanephrine Enantiomers: An In Vitro and Computational Study.

(1R)-Normetanephrine is the natural stereoisomeric substrate for sulfotransferase 1A3 (SULT1A3)-catalyzed sulfonation. Nothing appears known on the enantioselectivity of the reaction despite its potential significance in the metabolism of adrenergic amines and in clinical biochemistry. We confronted the kinetic parameters of the sulfoconjugation of synthetic (1R)-normetanephrine and (1S)-normetanephrine by recombinant human SULT1A3 to a docking model of each normetanephrine enantiomer with SULT1A3 and the 3'-phosphoadenosine-5'-phosphosulfate cofactor on the basis of molecular modeling and molecular dynamics simulations of the stability of the complexes. The K(M) , V(max) , and k(cat) values for the sulfonation of (1R)-normetanephrine, (1S)-normetanephrine, and racemic normetanephrine were similar. In silico models were consistent with these findings as they showed that the binding modes of the two enantiomers were almost identical. In conclusion, SULT1A3 is not substrate-enantioselective toward normetanephrine, an unexpected finding explainable by a mutual adaptability between the ligands and SULT1A3 through an "induced-fit model" in the catalytic pocket. Chirality, 00:000-000, 2012.© 2012 Wiley Periodicals, Inc.

Protein-ligand binding free energy estimation using molecular mechanics and continuum electrostatics. Application to HIV-1 protease inhibitors.

A method is proposed for the estimation of absolute binding free energy of interaction between proteins and ligands. Conformational sampling of the protein-ligand complex is performed by molecular dynamics (MD) in vacuo and the solvent effect is calculated a posteriori by solving the Poisson or the Poisson-Boltzmann equation for selected frames of the trajectory. The binding free energy is written as a linear combination of the buried surface upon complexation, SASbur, the electrostatic interaction energy between the ligand and the protein, Eelec, and the difference of the solvation free energies of the complex and the isolated ligand and protein, deltaGsolv. The method uses the buried surface upon complexation to account for the non-polar contribution to the binding free energy because it is less sensitive to the details of the structure than the van der Waals interaction energy. The parameters of the method are developed for a training set of 16 HIV-1 protease-inhibitor complexes of known 3D structure. A correlation coefficient of 0.91 was obtained with an unsigned mean error of 0.8 kcal/mol. When applied to a set of 25 HIV-1 protease-inhibitor complexes of unknown 3D structures, the method provides a satisfactory correlation between the calculated binding free energy and the experimental pIC5o without reparametrization.

Fourier transform convolution integrals applied to generalized Born molecular volume.

Generalized Born methods are currently among the solvation models most commonly used for biological applications. We reformulate the generalized Born molecular volume method initially described by (Lee et al, 2003, J Phys Chem, 116, 10606; Lee et al, 2003, J Comp Chem, 24, 1348) using fast Fourier transform convolution integrals. Changes in the initial method are discussed and analyzed. Finally, the method is extensively checked with snapshots from common molecular modeling applications: binding free energy computations and docking. Biologically relevant test systems are chosen, including 855-36091 atoms. It is clearly demonstrated that, precision-wise, the proposed method performs as good as the original, and could better benefit from hardware accelerated boards.

Structure-Based, Rational Design of T Cell Receptors.

Adoptive cell transfer using engineered T cells is emerging as a promising treatment for metastatic melanoma. Such an approach allows one to introduce T cell receptor (TCR) modifications that, while maintaining the specificity for the targeted antigen, can enhance the binding and kinetic parameters for the interaction with peptides (p) bound to major histocompatibility complexes (MHC). Using the well-characterized 2C TCR/SIYR/H-2K(b) structure as a model system, we demonstrated that a binding free energy decomposition based on the MM-GBSA approach provides a detailed and reliable description of the TCR/pMHC interactions at the structural and thermodynamic levels. Starting from this result, we developed a new structure-based approach, to rationally design new TCR sequences, and applied it to the BC1 TCR targeting the HLA-A2 restricted NY-ESO-1157-165 cancer-testis epitope. Fifty-four percent of the designed sequence replacements exhibited improved pMHC binding as compared to the native TCR, with up to 150-fold increase in affinity, while preserving specificity. Genetically engineered CD8(+) T cells expressing these modified TCRs showed an improved functional activity compared to those expressing BC1 TCR. We measured maximum levels of activities for TCRs within the upper limit of natural affinity, K D = ∼1 - 5 μM. Beyond the affinity threshold at K D < 1 μM we observed an attenuation in cellular function, in line with the "half-life" model of T cell activation. Our computer-aided protein-engineering approach requires the 3D-structure of the TCR-pMHC complex of interest, which can be obtained from X-ray crystallography. We have also developed a homology modeling-based approach, TCRep 3D, to obtain accurate structural models of any TCR-pMHC complexes when experimental data is not available. Since the accuracy of the models depends on the prediction of the TCR orientation over pMHC, we have complemented the approach with a simplified rigid method to predict this orientation and successfully assessed it using all non-redundant TCR-pMHC crystal structures available. These methods potentially extend the use of our TCR engineering method to entire TCR repertoires for which no X-ray structure is available. We have also performed a steered molecular dynamics study of the unbinding of the TCR-pMHC complex to get a better understanding of how TCRs interact with pMHCs. This entire rational TCR design pipeline is now being used to produce rationally optimized TCRs for adoptive cell therapies of stage IV melanoma.

Differential peptide binding to CD40 evokes counteractive responses.

The antigen-presenting cell-expressed CD40 is implied in the regulation of counteractive immune responses such as induction of pro-inflammatory and anti-inflammatory cytokines interleukin (IL)-12 and IL-10, respectively. The mechanism of this duality in CD40 function remains unknown. Here, we investigated whether such duality depends on ligand binding. Based on CD40 binding, we identifed two dodecameric peptides, peptide-7 and peptide-19, from the phage peptide library. Peptide-7 induces IL-10 and increases Leishmania donovani infection in macrophages, whereas peptide-19 induces IL-12 and reduces L. donovani infection. CD40-peptide interaction analyses by surface plasmon resonance and atomic force microscopy suggest that the functional differences are not associated with the studied interaction parameters. The molecular dynamic simulation of the CD40-peptides interaction suggests that these two peptides bind to two different places on CD40. Thus, we suggest for the first time that differential binding of the ligands imparts functional duality to CD40.

In silico prediction of human carboxylesterase-1 (hCES1) metabolism combining docking analyses and MD simulations.

Metabolic problems lead to numerous failures during clinical trials, and much effort is now devoted in developing in silico models predicting metabolic stability and metabolites. Such models are well known for cytochromes P450 and some transferases, whereas little has been done to predict the hydrolytic activity of human hydrolases. The present study was undertaken to develop a computational approach able to predict the hydrolysis of novel esters by human carboxylesterase hCES1. The study involves both docking analyses of known substrates to develop predictive models, and molecular dynamics (MD) simulations to reveal the in situ behavior of substrates and products, with particular attention being paid to the influence of their ionization state. The results emphasize some crucial properties of the hCES1 catalytic cavity, confirming that as a trend with several exceptions, hCES1 prefers substrates with relatively smaller and somewhat polar alkyl/aryl groups and larger hydrophobic acyl moieties. The docking results underline the usefulness of the hydrophobic interaction score proposed here, which allows a robust prediction of hCES1 catalysis, while the MD simulations show the different behavior of substrates and products in the enzyme cavity, suggesting in particular that basic substrates interact with the enzyme in their unprotonated form.

Structural prediction of peptides bound to MHC class I.

An ab initio structure prediction approach adapted to the peptide-major histocompatibility complex (MHC) class I system is presented. Based on structure comparisons of a large set of peptide-MHC class I complexes, a molecular dynamics protocol is proposed using simulated annealing (SA) cycles to sample the conformational space of the peptide in its fixed MHC environment. A set of 14 peptide-human leukocyte antigen (HLA) A0201 and 27 peptide-non-HLA A0201 complexes for which X-ray structures are available is used to test the accuracy of the prediction method. For each complex, 1000 peptide conformers are obtained from the SA sampling. A graph theory clustering algorithm based on heavy atom root-mean-square deviation (RMSD) values is applied to the sampled conformers. The clusters are ranked using cluster size, mean effective or conformational free energies, with solvation free energies computed using Generalized Born MV 2 (GB-MV2) and Poisson-Boltzmann (PB) continuum models. The final conformation is chosen as the center of the best-ranked cluster. With conformational free energies, the overall prediction success is 83% using a 1.00 Angstroms crystal RMSD criterion for main-chain atoms, and 76% using a 1.50 Angstroms RMSD criterion for heavy atoms. The prediction success is even higher for the set of 14 peptide-HLA A0201 complexes: 100% of the peptides have main-chain RMSD values &lt; or =1.00 Angstroms and 93% of the peptides have heavy atom RMSD values &lt; or =1.50 Angstroms. This structure prediction method can be applied to complexes of natural or modified antigenic peptides in their MHC environment with the aim to perform rational structure-based optimizations of tumor vaccines.

Three-dimensional models of 14α-sterol demethylase (Cyp51A) from Aspergillus lentulus and Aspergillus fumigatus: an insight into differences in voriconazole interaction.

Aspergillus lentulus, an Aspergillus fumigatus sibling species, is increasingly reported in corticosteroid-treated patients. Its clinical significance is unknown, but the fact that A. lentulus shows reduced antifungal susceptibility, mainly to voriconazole, is of serious concern. Heterologous expression of cyp51A from A. fumigatus and A. lentulus was performed in Saccharomyces cerevisiae to assess differences in the interaction of Cyp51A with the azole drugs. The absence of endogenous ERG11 was efficiently complemented in S. cerevisiae by the expression of either Aspergillus cyp51A allele. There was a marked difference between azole minimum inhibitory concentration (MIC) values of the clones expressing each Aspergillus spp. cyp51A. Saccharomyces cerevisiae clones expressing A. lentulus alleles showed higher MICs to all of the azoles tested, supporting the hypothesis that the intrinsic azole resistance of A. lentulus could be associated with Cyp51A. Homology models of A. fumigatus and A. lentulus Cyp51A protein based on the crystal structure of Cyp51p from Mycobacterium tuberculosis in complex with fluconazole were almost identical owing to their mutual high sequence identity. Molecular dynamics (MD) was applied to both three-dimensional protein models to refine the homology modelling and to explore possible differences in the Cyp51A-voriconazole interaction. After 20ns of MD modelling, some critical differences were observed in the putative closed form adopted by the protein upon voriconazole binding. A closer study of the A. fumigatus and A. lentulus voriconazole putative binding site in Cyp51A suggested that some major differences in the protein's BC loop could differentially affect the lock-up of voriconazole, which in turn could correlate with their different azole susceptibility profiles.

Localization of breakage points in knotted strings

It is a common macroscopic observation that knotted ropes or fishing lines under tension easily break at the knot. However, a more precise localization of the breakage point in knotted macroscopic strings is a difficult task. In the present work, the tightening of knots was numerically simulated, a comparison of strength of different knots was experimentally performed and a high velocity camera was used to precisely localize the site where knotted macroscopic strings break. In the case of knotted spaghetti, the breakage occurs at the position with high curvature at the entry to the knot. This localization results from joint contributions of loading, bending and friction forces into the complex process of knot breakage. The present simulations and experiments are in agreement with recent molecular dynamics simulations of a knotted polymer chain and with experiments performed on actin and DNA filaments. The strength of the knotted string is greatly reduced (down to 50%) by the presence of a knot, therefore reducing the resistance to tension of all materials containing chains of any sort. The present work with macroscopic strings revels some important aspects, which are not accessible by experiments with microscopic chains.