Ab initio modeling and molecular dynamics simulation of the alpha 1b-adrenergic receptor activation.

This work describes the ab initio procedure employed to build an activation model for the alpha 1b-adrenergic receptor (alpha 1b-AR). The first version of the model was progressively modified and complicated by means of a many-step iterative procedure characterized by the employment of experimental validations of the model in each upgrading step. A combined simulated (molecular dynamics) and experimental mutagenesis approach was used to determine the structural and dynamic features characterizing the inactive and active states of alpha 1b-AR. The latest version of the model has been successfully challenged with respect to its ability to interpret and predict the functional properties of a large number of mutants. The iterative approach employed to describe alpha 1b-AR activation in terms of molecular structure and dynamics allows further complications of the model to allow prediction and interpretation of an ever-increasing number of experimental data.

NO rebinding to myoglobin: a reactive molecular dynamics study.

The rebinding of NO to myoglobin after photolysis is studied using the 'reactive molecular dynamics' method. In this approach the energy of the system is evaluated on two potential energy surfaces that include the heme-ligand interactions which change between liganded and unliganded myoglobin. This makes it possible to take into account in a simple way, the high dimensionality of the transition seam connecting the reactant and product states. The dynamics of the dissociated NO molecules are examined, and the geometrical and energetic properties of the transition seam are studied. Analysis of the frequency of recrossing shows that the height of the effective rebinding barrier is dependent on the time after photodissociation. This effect is due mainly to protein relaxation and may contribute to the experimentally observed non-exponential rebinding rate of NO, as has been suggested previously.

How T cell receptors interact with peptide-MHCs: A multiple steered molecular dynamics study.

The T-cell receptor (TCR) interaction with antigenic peptides (p) presented by the major histocompatibility complex (MHC) molecule is a key determinant of immune response. In addition, TCR-pMHC interactions offer examples of features more generally pertaining to protein-protein recognition: subtle specificity and cross-reactivity. Despite their importance, molecular details determining the TCR-pMHC binding remain unsolved. However, molecular simulation provides the opportunity to investigate some of these aspects. In this study, we perform extensive equilibrium and steered molecular dynamics simulations to study the unbinding of three TCR-pMHC complexes. As a function of the dissociation reaction coordinate, we are able to obtain converged H-bond counts and energy decompositions at different levels of detail, ranging from the full proteins, to separate residues and water molecules, down to single atoms at the interface. Many observed features do not support a previously proposed two-step model for TCR recognition. Our results also provide keys to interpret experimental point-mutation results. We highlight the role of water both in terms of interface resolvation and of water molecules trapped in the bound complex. Importantly, we illustrate how two TCRs with similar reactivity and structures can have essentially different binding strategies. Proteins 2011; © 2011 Wiley-Liss, Inc.

NMR chemical shifts of the rhodopsin chromophore in the dark state and in bathorhodopsin: a hybrid QM/MM molecular dynamics study.

We investigate nuclear magnetic resonance (NMR) parameters of the rhodopsin chromophore in the dark state of the protein and in the early photointermediate bathorhodopsin via first-principles molecular dynamics simulations and NMR chemical shift calculations in a hybrid quantum/classical (QM/MM) framework. NMR parameters are particularly sensitive to structural properties and to the chemical environment, which allows us to address different questions about the retinal chromophore in situ. Our calculations show that both the 13C and the 1H NMR chemical shifts are rather insensitive to the protonation state of Glu181, an ionizable amino acid side chain located in the vicinity of the isomerizing 11-cis bond. Thus, other techniques should be better suited to establish its protonation state. The calculated chemical shifts for bathorhodopsin further support our previously published theoretical structure, which is in very good agreement with more recent X-ray data.

Understanding the low-temperature limitations to forest growth through calibration of a forest dynamics model with tree-ring data

The sensitivity of altitudinal and latitudinal tree-line ecotones to climate change, particularly that of temperature, has received much attention. To improve our understanding of the factors affecting tree-line position, we used the spatially explicit dynamic forest model TreeMig. Although well-suited because of its landscape dynamics functions, TreeMig features a parabolic temperature growth response curve, which has recently been questioned. and the species parameters are not specifically calibrated for cold temperatures. Our main goals were to improve the theoretical basis of the temperature growth response curve in the model and develop a method for deriving that curve's parameters from tree-ring data. We replaced the parabola with an asymptotic curve, calibrated for the main species at the subalpine (Swiss Alps: Pinus cembra, Larix decidua, Picea abies) and boreal (Fennoscandia: Pinus sylvestris, Betula pubescens, P. abies) tree-lines. After fitting new parameters, the growth curve matched observed tree-ring widths better. For the subalpine species, the minimum degree-day sum allowing, growth (kDDMin) was lowered by around 100 degree-days; in the case of Larix, the maximum potential ring-width was increased to 5.19 mm. At the boreal tree-line, the kDDMin for P. sylvestris was lowered by 210 degree-days and its maximum ring-width increased to 2.943 mm; for Betula (new in the model) kDDMin was set to 325 degree-days and the maximum ring-width to 2.51 mm; the values from the only boreal sample site for Picea were similar to the subalpine ones, so the same parameters were used. However, adjusting the growth response alone did not improve the model's output concerning species' distributions and their relative importance at tree-line. Minimum winter temperature (MinWiT, mean of the coldest winter month), which controls seedling establishment in TreeMig, proved more important for determining distribution. Picea, P. sylvestris and Betula did not previously have minimum winter temperature limits, so these values were set to the 95th percentile of each species' coldest MinWiT site (respectively -7, -11, -13). In a case study for the Alps, the original and newly calibrated versions of TreeMig were compared with biomass data from the National Forest Inventor), (NFI). Both models gave similar, reasonably realistic results. In conclusion, this method of deriving temperature responses from tree-rings works well. However, regeneration and its underlying factors seem more important for controlling species' distributions than previously thought. More research on regeneration ecology, especially at the upper limit of forests. is needed to improve predictions of tree-line responses to climate change further.

Protein-protein interaction investigated by steered molecular dynamics: the TCR-pMHC complex.

We present a novel steered molecular dynamics scheme to induce the dissociation of large protein-protein complexes. We apply this scheme to study the interaction of a T cell receptor (TCR) with a major histocompatibility complex (MHC) presenting a peptide (p). Two TCR-pMHC complexes are considered, which only differ by the mutation of a single amino acid on the peptide; one is a strong agonist that produces T cell activation in vivo, while the other is an antagonist. We investigate the interaction mechanism from a large number of unbinding trajectories by analyzing van der Waals and electrostatic interactions and by computing energy changes in proteins and solvent. In addition, dissociation potentials of mean force are calculated with the Jarzynski identity, using an averaging method developed for our steering scheme. We analyze the convergence of the Jarzynski exponential average, which is hampered by the large amount of dissipative work involved and the complexity of the system. The resulting dissociation free energies largely underestimate experimental values, but the simulations are able to clearly differentiate between wild-type and mutated TCR-pMHC and give insights into the dissociation mechanism.

Influence of ionization state on the activation of temocapril by hCES1: a molecular-dynamics study.

Temocapril is a prodrug whose hydrolysis by carboxylesterase 1 (CES1) yields the active ACE inhibitor temocaprilat. This molecular-dynamics (MD) study uses a resolved structure of the human CES1 (hCES1) to investigate some mechanistic details of temocapril hydrolysis. The ionization constants of temocapril (pK1 and pK3) and temocaprilat (pK1, pK2, and pK3) were determined experimentally and computationally using commercial algorithms. The constants so obtained were in good agreement and revealed that temocapril exists mainly in three ionic forms (a cation, a zwitterion, and an anion), whereas temocaprilat exists in four major ionic forms (a cation, a zwitterion, an anion, and a dianion). All these ionic forms were used as ligands in 5-ns MS simulations. While the cationic and zwitterionic forms of temocapril were involved in an ion-pair bond with Glu255 suggestive of an inhibitor behavior, the anionic form remained in a productive interaction with the catalytic center. As for temocaprilat, its cation appeared trapped by Glu255, while its zwitterion and anion made a slow departure from the catalytic site and a partial egress from the protein. Only its dianion was effectively removed from the catalytic site and attracted to the protein surface by Lys residues. A detailed mechanism of product egress emerges from the simulations.

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.

Molecular mechanisms involved in the activation and regulation of the alpha 1-adrenergic receptor subtypes.

The adrenergic receptors (ARs) belong to the superfamily of membrane-bound G protein coupled receptors (GPCRs). Our investigation has focused on the structure-function relationship of the alpha 1b-AR subtype used as the model system for other GPCRs. Site-directed mutagenesis studies have elucidated the structural domains of the alpha 1b-AR involved in ligand binding, G protein coupling or desensitization. In addition, a combined approach using site-directed mutagenesis and molecular dynamics analysis of the alpha 1b-AR has provided information about the potential mechanisms underlying the activation process of the receptor, i.e. its transition from the 'inactive' to the 'active' conformation.

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.

Relation between sequence and structure of HIV-1 protease inhibitor complexes: a model system for the analysis of protein flexibility.

The flexibility of different regions of HIV-1 protease was examined by using a database consisting of 73 X-ray structures that differ in terms of sequence, ligands or both. The root-mean-square differences of the backbone for the set of structures were shown to have the same variation with residue number as those obtained from molecular dynamics simulations, normal mode analyses and X-ray B-factors. This supports the idea that observed structural changes provide a measure of the inherent flexibility of the protein, although specific interactions between the protease and the ligand play a secondary role. The results suggest that the potential energy surface of the HIV-1 protease is characterized by many local minima with small energetic differences, some of which are sampled by the different X-ray structures of the HIV-1 protease complexes. Interdomain correlated motions were calculated from the structural fluctuations and the results were also in agreement with molecular dynamics simulations and normal mode analyses. Implications of the results for the drug-resistance engendered by mutations are discussed briefly.

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.

Mutational analysis of the highly conserved arginine within the Glu/Asp-Arg-Tyr motif of the alpha(1b)-adrenergic receptor: effects on receptor isomerization and activation.

We have suggested previously that both the negatively and positively charged residues of the highly conserved Glu/Asp-Arg-Tyr (E/DRY) motif play an important role in the activation process of the alpha(1b)-adreneric receptor (AR). In this study, R143 of the E/DRY sequence in the alpha(1b)-AR was mutated into several amino acids (Lys, His, Glu, Asp, Ala, Asn, and Ile). The charge-conserving mutation of R143 into lysine not only preserved the maximal agonist-induced response of the alpha(1b)-AR, but it also conferred high degree of constitutive activity to the receptor. Both basal and agonist-induced phosphorylation levels were significantly increased for the R143K mutant compared with those of the wild-type receptor. Other substitutions of R143 resulted in receptor mutants with either a small increase in constitutive activity (R143H and R143D), impairment (R143H, R143D), or complete loss of receptor-mediated response (R143E, R143A, R143N, R143I). The R413E mutant displayed a small, but significant increase in basal phosphorylation despite being severely impaired in receptor-mediated response. Interestingly, all the arginine mutants displayed increased affinity for agonist binding compared with the wild-type alpha(1b)-AR. A correlation was found between the extent of the affinity shift and the intrinsic activity of the agonists. The analysis of the receptor mutants using the allosteric ternary complex model in conjunction with the results of molecular dynamics simulations on the receptor models support the hypothesis that mutations of R143 can drive the isomerization of the alpha(1b)-AR into different states, highlighting the crucial role of this residue in the activation process of the receptor.

Theoretical study on receptor-G protein recognition: new insights into the mechanisms of the alpha1b-adrenergic recptor activation

This work compares the structural/dynamics features of the wild-type alb-adrenergic receptor (AR) with those of the D142A active mutant and the agonist-bound state. The two active receptor forms were compared in their isolated states as well as in their ability to form homodimers and to recognize the G alpha q beta 1 gamma 2 heterotrimer. The analysis of the isolated structures revealed that, although the mutation- and agonist-induced active states of the alpha 1b-AR are different, they, however, share several structural peculiarities including (a) the release of some constraining interactions found in the wild-type receptor and (b) the opening of a cytosolic crevice formed by the second and third intracellular loops and the cytosolic extensions of helices 5 and 6. Accordingly, also their tendency to form homodimers shows commonalties and differences. In fact, in both the active receptor forms, helix 6 plays a crucial role in mediating homodimerization. However, the homodimeric models result from different interhelical assemblies. On the same line of evidence, in both of the active receptor forms, the cytosolic opened crevice recognizes similar domains on the G protein. However, the docking solutions are differently populated and the receptor-G protein preorientation models suggest that the final complexes should be characterized by different interaction patterns.

Combining probabilistic land-use change and tree population dynamics modelling to simulate responses in mountain forests

Altitudinal tree lines are mainly constrained by temperature, but can also be influenced by factors such as human activity, particularly in the European Alps, where centuries of agricultural use have affected the tree-line. Over the last decades this trend has been reversed due to changing agricultural practices and land-abandonment. We aimed to combine a statistical land-abandonment model with a forest dynamics model, to take into account the combined effects of climate and human land-use on the Alpine tree-line in Switzerland. Land-abandonment probability was expressed by a logistic regression function of degree-day sum, distance from forest edge, soil stoniness, slope, proportion of employees in the secondary and tertiary sectors, proportion of commuters and proportion of full-time farms. This was implemented in the TreeMig spatio-temporal forest model. Distance from forest edge and degree-day sum vary through feed-back from the dynamics part of TreeMig and climate change scenarios, while the other variables remain constant for each grid cell over time. The new model, TreeMig-LAb, was tested on theoretical landscapes, where the variables in the land-abandonment model were varied one by one. This confirmed the strong influence of distance from forest and slope on the abandonment probability. Degree-day sum has a more complex role, with opposite influences on land-abandonment and forest growth. TreeMig-LAb was also applied to a case study area in the Upper Engadine (Swiss Alps), along with a model where abandonment probability was a constant. Two scenarios were used: natural succession only (100% probability) and a probability of abandonment based on past transition proportions in that area (2.1% per decade). The former showed new forest growing in all but the highest-altitude locations. The latter was more realistic as to numbers of newly forested cells, but their location was random and the resulting landscape heterogeneous. Using the logistic regression model gave results consistent with observed patterns of land-abandonment: existing forests expanded and gaps closed, leading to an increasingly homogeneous landscape.