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.

Comparison between computational alanine scanning and per-residue binding free energy decomposition for protein-protein association using MM-GBSA: application to the TCR-p-MHC complex.

Recognition by the T-cell receptor (TCR) of immunogenic peptides (p) presented by Class I major histocompatibility complexes (MHC) is the key event in the immune response against virus-infected cells or tumor cells. A study of the 2C TCR/SIYR/H-2K(b) system using a computational alanine scanning and a much faster binding free energy decomposition based on the Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) method is presented. The results show that the TCR-p-MHC binding free energy decomposition using this approach and including entropic terms provides a detailed and reliable description of the interactions between the molecules at an atomistic level. Comparison of the decomposition results with experimentally determined activity differences for alanine mutants yields a correlation of 0.67 when the entropy is neglected and 0.72 when the entropy is taken into account. Similarly, comparison of experimental activities with variations in binding free energies determined by computational alanine scanning yields correlations of 0.72 and 0.74 when the entropy is neglected or taken into account, respectively. Some key interactions for the TCR-p-MHC binding are analyzed and some possible side chains replacements are proposed in the context of TCR protein engineering. In addition, a comparison of the two theoretical approaches for estimating the role of each side chain in the complexation is given, and a new ad hoc approach to decompose the vibrational entropy term into atomic contributions, the linear decomposition of the vibrational entropy (LDVE), is introduced. The latter allows the rapid calculation of the entropic contribution of interesting side chains to the binding. This new method is based on the idea that the most important contributions to the vibrational entropy of a molecule originate from residues that contribute most to the vibrational amplitude of the normal modes. The LDVE approach is shown to provide results very similar to those of the exact but highly computationally demanding method.

MM-GBSA binding free energy decomposition and T cell receptor engineering.

Recognition by the T-cell receptor (TCR) of immunogenic peptides (p) presented by class I major histocompatibility complexes (MHC) is the key event in the immune response against virus infected cells or tumor cells. The major determinant of T cell activation is the affinity of the TCR for the peptide-MHC complex, though kinetic parameters are also important. A study of the 2C TCR/SIYR/H-2Kb system using a binding free energy decomposition (BFED) based on the MM-GBSA approach had been performed to assess the performance of the approach on this system. The results showed that the TCR-p-MHC BFED including entropic terms provides a detailed and reliable description of the energetics of the interaction (Zoete and Michielin, 2007). Based on these results, we have developed a new approach to design sequence modifications for a TCR recognizing the human leukocyte antigen (HLA)-A2 restricted tumor epitope NY-ESO-1. NY-ESO-1 is a cancer testis antigen expressed not only in melanoma, but also on several other types of cancers. It has been observed at high frequencies in melanoma patients with unusually positive clinical outcome and, therefore, represents an interesting target for adoptive transfer with modified TCR. Sequence modifications of TCR potentially increasing the affinity for this epitope have been proposed and tested in vitro. T cells expressing some of the proposed TCR mutants showed better T cell functionality, with improved killing of peptide-loaded T2 cells and better proliferative capacity compared to the wild type TCR expressing cells. These results open the door of rational TCR design for adoptive transfer cancer therapy.

Binding free energy differences in a TCR-peptide-MHC complex induced by a peptide mutation: a simulation analysis.

Recognition by the T-cell receptor (TCR) of immunogenic peptides presented by class I major histocompatibility complexes (MHCs) is the determining event in the specific cellular immune response against virus-infected cells or tumor cells. It is of great interest, therefore, to elucidate the molecular principles upon which the selectivity of a TCR is based. These principles can in turn be used to design therapeutic approaches, such as peptide-based immunotherapies of cancer. In this study, free energy simulation methods are used to analyze the binding free energy difference of a particular TCR (A6) for a wild-type peptide (Tax) and a mutant peptide (Tax P6A), both presented in HLA A2. The computed free energy difference is 2.9 kcal/mol, in good agreement with the experimental value. This makes possible the use of the simulation results for obtaining an understanding of the origin of the free energy difference which was not available from the experimental results. A free energy component analysis makes possible the decomposition of the free energy difference between the binding of the wild-type and mutant peptide into its components. Of particular interest is the fact that better solvation of the mutant peptide when bound to the MHC molecule is an important contribution to the greater affinity of the TCR for the latter. The results make possible identification of the residues of the TCR which are important for the selectivity. This provides an understanding of the molecular principles that govern the recognition. The possibility of using free energy simulations in designing peptide derivatives for cancer immunotherapy is briefly discussed.

Cell-free reconstitution of vacuole membrane fragmentation reveals regulation of vacuole size and number by TORC1.

Size and copy number of organelles are influenced by an equilibrium of membrane fusion and fission. We studied this equilibrium on vacuoles-the lysosomes of yeast. Vacuole fusion can readily be reconstituted and quantified in vitro, but it had not been possible to study fission of the organelle in a similar way. Here we present a cell-free system that reconstitutes fragmentation of purified yeast vacuoles (lysosomes) into smaller vesicles. Fragmentation in vitro reproduces physiological aspects. It requires the dynamin-like GTPase Vps1p, V-ATPase pump activity, cytosolic proteins, and ATP and GTP hydrolysis. We used the in vitro system to show that the vacuole-associated TOR complex 1 (TORC1) stimulates vacuole fragmentation but not the opposing reaction of vacuole fusion. Under nutrient restriction, TORC1 is inactivated, and the continuing fusion activity then dominates the fusion/fission equilibrium, decreasing the copy number and increasing the volume of the vacuolar compartment. This result can explain why nutrient restriction not only induces autophagy and a massive buildup of vacuolar/lysosomal hydrolases, but also leads to a concomitant increase in volume of the vacuolar compartment by coalescence of the organelles into a single large compartment.

Mutations inducing divergent shifts of constitutive activity reveal different modes of binding among catecholamine analogues to the beta(2)-adrenergic receptor.

1. We compared the changes in binding energy generated by two mutations that shift in divergent directions the constitutive activity of the human beta(2) adrenergic receptor (beta(2)AR). 2. A constitutively activating mutant (CAM) and the double alanine replacement (AA mutant) of catechol-binding serines (S204A, S207A) in helix 5 were stably expressed in CHO cell lines, and used to measure the binding affinities of more than 40 adrenergic ligands. Moreover, the efficacy of the same group of compounds was determined as intrinsic activity for maximal adenylyl cyclase stimulation in wild-type beta(2)AR. 3. Although the two mutations had opposite effects on ligand affinity, the extents of change were in both cases largely correlated with the degree of ligand efficacy. This was particularly evident if the extra loss of binding energy due to hydrogen bond deletion in the AA mutant was taken into account. Thus the data demonstrate that there is an overall linkage between the configuration of the binding pocket and the intrinsic equilibrium between active and inactive receptor forms. 4. We also found that AA mutation-induced affinity changes for catecholamine congeners gradually lacking ethanolamine substituents were linearly correlated to the loss of affinity that such modifications of the ligand cause for wild-type receptor. This indicates that the strength of bonds between catechol ring and helix 5 is critically dependent on the rest of interactions of the beta-ethanolamine tail with other residues of the beta(2)-AR binding pocket.

EADock: docking of small molecules into protein active sites with a multiobjective evolutionary optimization.

In recent years, protein-ligand docking has become a powerful tool for drug development. Although several approaches suitable for high throughput screening are available, there is a need for methods able to identify binding modes with high accuracy. This accuracy is essential to reliably compute the binding free energy of the ligand. Such methods are needed when the binding mode of lead compounds is not determined experimentally but is needed for structure-based lead optimization. We present here a new docking software, called EADock, that aims at this goal. It uses an hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 A around the center of mass of the ligand position in the crystal structure, and on the contrary to other benchmarks, our algorithm was fed with optimized ligand positions up to 10 A root mean square deviation (RMSD) from the crystal structure, excluding the latter. This validation illustrates the efficiency of our sampling strategy, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures could be explained by the presence of crystal contacts in the experimental structure. Finally, the ability of EADock to accurately predict binding modes on a real application was illustrated by the successful docking of the RGD cyclic pentapeptide on the alphaVbeta3 integrin, starting far away from the binding pocket.

EADock : design of a new molecular docking algorithm and some of its applications

3 Summary 3. 1 English The pharmaceutical industry has been facing several challenges during the last years, and the optimization of their drug discovery pipeline is believed to be the only viable solution. High-throughput techniques do participate actively to this optimization, especially when complemented by computational approaches aiming at rationalizing the enormous amount of information that they can produce. In siiico techniques, such as virtual screening or rational drug design, are now routinely used to guide drug discovery. Both heavily rely on the prediction of the molecular interaction (docking) occurring between drug-like molecules and a therapeutically relevant target. Several softwares are available to this end, but despite the very promising picture drawn in most benchmarks, they still hold several hidden weaknesses. As pointed out in several recent reviews, the docking problem is far from being solved, and there is now a need for methods able to identify binding modes with a high accuracy, which is essential to reliably compute the binding free energy of the ligand. This quantity is directly linked to its affinity and can be related to its biological activity. Accurate docking algorithms are thus critical for both the discovery and the rational optimization of new drugs. In this thesis, a new docking software aiming at this goal is presented, EADock. It uses a hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with .the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 R around the center of mass of the ligand position in the crystal structure, and conversely to other benchmarks, our algorithms was fed with optimized ligand positions up to 10 A root mean square deviation 2MSD) from the crystal structure. This validation illustrates the efficiency of our sampling heuristic, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best-ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures in this benchmark could be explained by the presence of crystal contacts in the experimental structure. EADock has been used to understand molecular interactions involved in the regulation of the Na,K ATPase, and in the activation of the nuclear hormone peroxisome proliferatoractivated receptors a (PPARa). It also helped to understand the action of common pollutants (phthalates) on PPARy, and the impact of biotransformations of the anticancer drug Imatinib (Gleevec®) on its binding mode to the Bcr-Abl tyrosine kinase. Finally, a fragment-based rational drug design approach using EADock was developed, and led to the successful design of new peptidic ligands for the a5ß1 integrin, and for the human PPARa. In both cases, the designed peptides presented activities comparable to that of well-established ligands such as the anticancer drug Cilengitide and Wy14,643, respectively. 3.2 French Les récentes difficultés de l'industrie pharmaceutique ne semblent pouvoir se résoudre que par l'optimisation de leur processus de développement de médicaments. Cette dernière implique de plus en plus. de techniques dites "haut-débit", particulièrement efficaces lorsqu'elles sont couplées aux outils informatiques permettant de gérer la masse de données produite. Désormais, les approches in silico telles que le criblage virtuel ou la conception rationnelle de nouvelles molécules sont utilisées couramment. Toutes deux reposent sur la capacité à prédire les détails de l'interaction moléculaire entre une molécule ressemblant à un principe actif (PA) et une protéine cible ayant un intérêt thérapeutique. Les comparatifs de logiciels s'attaquant à cette prédiction sont flatteurs, mais plusieurs problèmes subsistent. La littérature récente tend à remettre en cause leur fiabilité, affirmant l'émergence .d'un besoin pour des approches plus précises du mode d'interaction. Cette précision est essentielle au calcul de l'énergie libre de liaison, qui est directement liée à l'affinité du PA potentiel pour la protéine cible, et indirectement liée à son activité biologique. Une prédiction précise est d'une importance toute particulière pour la découverte et l'optimisation de nouvelles molécules actives. Cette thèse présente un nouveau logiciel, EADock, mettant en avant une telle précision. Cet algorithme évolutionnaire hybride utilise deux pressions de sélections, combinées à une gestion de la diversité sophistiquée. EADock repose sur CHARMM pour les calculs d'énergie et la gestion des coordonnées atomiques. Sa validation a été effectuée sur 37 complexes protéine-ligand cristallisés, incluant 11 protéines différentes. L'espace de recherche a été étendu à une sphère de 151 de rayon autour du centre de masse du ligand cristallisé, et contrairement aux comparatifs habituels, l'algorithme est parti de solutions optimisées présentant un RMSD jusqu'à 10 R par rapport à la structure cristalline. Cette validation a permis de mettre en évidence l'efficacité de notre heuristique de recherche car des modes d'interactions présentant un RMSD inférieur à 2 R par rapport à la structure cristalline ont été classés premier pour 68% des complexes. Lorsque les cinq meilleures solutions sont prises en compte, le taux de succès grimpe à 78%, et 92% lorsque la totalité de la dernière génération est prise en compte. La plupart des erreurs de prédiction sont imputables à la présence de contacts cristallins. Depuis, EADock a été utilisé pour comprendre les mécanismes moléculaires impliqués dans la régulation de la Na,K ATPase et dans l'activation du peroxisome proliferatoractivated receptor a (PPARa). Il a également permis de décrire l'interaction de polluants couramment rencontrés sur PPARy, ainsi que l'influence de la métabolisation de l'Imatinib (PA anticancéreux) sur la fixation à la kinase Bcr-Abl. Une approche basée sur la prédiction des interactions de fragments moléculaires avec protéine cible est également proposée. Elle a permis la découverte de nouveaux ligands peptidiques de PPARa et de l'intégrine a5ß1. Dans les deux cas, l'activité de ces nouveaux peptides est comparable à celles de ligands bien établis, comme le Wy14,643 pour le premier, et le Cilengitide (PA anticancéreux) pour la seconde.

Label-free detection of tobramycin in serum by transmission-localized surface plasmon resonance.

In order to improve the efficacy and safety of treatments, drug dosage needs to be adjusted to the actual needs of each patient in a truly personalized medicine approach. Key for widespread dosage adjustment is the availability of point-of-care devices able to measure plasma drug concentration in a simple, automated, and cost-effective fashion. In the present work, we introduce and test a portable, palm-sized transmission-localized surface plasmon resonance (T-LSPR) setup, comprised of off-the-shelf components and coupled with DNA-based aptamers specific to the antibiotic tobramycin (467 Da). The core of the T-LSPR setup are aptamer-functionalized gold nanoislands (NIs) deposited on a glass slide covered with fluorine-doped tin oxide (FTO), which acts as a biosensor. The gold NIs exhibit localized plasmon resonance in the visible range matching the sensitivity of the complementary metal oxide semiconductor (CMOS) image sensor employed as a light detector. The combination of gold NIs on the FTO substrate, causing NIs size and pattern irregularity, might reduce the overall sensitivity but confers extremely high stability in high-ionic solutions, allowing it to withstand numerous regeneration cycles without sensing losses. With this rather simple T-LSPR setup, we show real-time label-free detection of tobramycin in buffer, measuring concentrations down to 0.5 μM. We determined an affinity constant of the aptamer-tobramycin pair consistent with the value obtained using a commercial propagating-wave based SPR. Moreover, our label-free system can detect tobramycin in filtered undiluted blood serum, measuring concentrations down to 10 μM with a theoretical detection limit of 3.4 μM. While the association signal of tobramycin onto the aptamer is masked by the serum injection, the quantification of the captured tobramycin is possible during the dissociation phase and leads to a linear calibration curve for the concentrations over the tested range (10-80 μM). The plasmon shift following surface binding is calculated in terms of both plasmon peak location and hue, with the latter allowing faster data elaboration and real-time display of the results. The presented T-LSPR system shows for the first time label-free direct detection and quantification of a small molecule in the complex matrix of filtered undiluted blood serum. Its uncomplicated construction and compact size, together with the remarkable performances, represent a leap forward toward effective point-of-care devices for therapeutic drug concentration monitoring.

Cell-free reconstitution of microautophagy in yeast.

Microautophagy is the direct uptake of soluble or particulate cellular constituents into lysosomes. Here, I describe methods to reconstitute and study this process in vitro, using vacuoles (lysosomes) from the yeast Saccharomyces cerevisiae as model organelles. Protocols to grow the cells, isolate vacuoles from them, and to induce microautophagy of soluble tracers are presented.

A rapid assay for the coupled cell free generation of oxylipins

We developed a rapid and simple assay for the coupled in vitro synthesis of oxylipins using free unsaturated fatty acids as substrates. Reactions were catalysed with extracts expressed from living plant tissues. Preliminary experiments involving the cell free transformation of fatty acid hydroperoxides revealed that storage or pretreatment of the plant extract rapidly altered its capacity to catalyse the generation of oxidised fatty acid derivatives. This could reflect changes in oxylipin generation that might take place in situ in damaged plant cells during herbivory. All subsequent experiments were performed without dilution, titration or any other modification of the plant extract prior to its addition to the assay system. The assays were used to study, for the first time, tissue-specific differences in fatty acid transformation to divinyl ethers. Root tissues from tomato efficiently catalysed the formation of corneleic and colnelenic acids from linoleic acid and linolenic acids, respectively, whereas leaf, hypocotyl and cotyledon extracts did not promote the formation of these compounds. We observed the efficient generation of 9-oxo-nonanoic acid from the substrate linolenic acid and speculate that this aldehyde could arise either from the action of hydroperoxide lyase on 9-hydroperoxylinolenic acid or by a novel route involving cleavage of colnelenic acid which was also present among the products of the reaction. A potential role of divinyl ethers as substrates for the generation of toxic aldehydes is discussed

SwissParam: a fast force field generation tool for small organic molecules.

The drug discovery process has been deeply transformed recently by the use of computational ligand-based or structure-based methods, helping the lead compounds identification and optimization, and finally the delivery of new drug candidates more quickly and at lower cost. Structure-based computational methods for drug discovery mainly involve ligand-protein docking and rapid binding free energy estimation, both of which require force field parameterization for many drug candidates. Here, we present a fast force field generation tool, called SwissParam, able to generate, for arbitrary small organic molecule, topologies, and parameters based on the Merck molecular force field, but in a functional form that is compatible with the CHARMM force field. Output files can be used with CHARMM or GROMACS. The topologies and parameters generated by SwissParam are used by the docking software EADock2 and EADock DSS to describe the small molecules to be docked, whereas the protein is described by the CHARMM force field, and allow them to reach success rates ranging from 56 to 78%. We have also developed a rapid binding free energy estimation approach, using SwissParam for ligands and CHARMM22/27 for proteins, which requires only a short minimization to reproduce the experimental binding free energy of 214 ligand-protein complexes involving 62 different proteins, with a standard error of 2.0 kcal mol(-1), and a correlation coefficient of 0.74. Together, these results demonstrate the relevance of using SwissParam topologies and parameters to describe small organic molecules in computer-aided drug design applications, together with a CHARMM22/27 description of the target protein. SwissParam is available free of charge for academic users at www.swissparam.ch.

Monoclonal antibodies against idiotypic determinant(s) of the T cell receptor from HPB-ALL cells induce IL2 production in Jurkat cells without apparent evidence of binding.

Two monoclonal antibodies (mAb) directed against idiotypic determinants of the T cell receptor (anti-Ti) from HPB-ALL cells induce interleukin 2 (IL2) production in Jurkat T cells without evidence of binding to these cells as judged by fluorescence-activated cell sorter (FACS) analysis, indirect antibody-binding radioimmunoassay and direct binding studies with 125I-labeled mAb. The IL2 response induced by these mAb observed both in the presence and absence of phorbol myristate acetate was in the range of that obtained when Jurkat cells were stimulated with phytohemagglutinin or anti-T3 mAb (Leu 4). The idiotypic specificity of the two anti-HPB-ALL Ti mAb was demonstrated by several criteria. Both mAb bound specifically to HPB-ALL cells as determined by radioimmunoassay or FACS analysis but not with 8 other T cell lines. The anti-HPB-ALL Ti mAb precipitated a disulfide-linked heterodimer of 85 kDa only from 125I-labeled HPB-ALL cells and not from other cell lines tested. Incubation of HPB-ALL cells with anti-T3 abrogated the expression of T3 and induced co-modulation of the idiotypic structures detected by the two anti-HPB-ALL Ti mAb. Conversely, incubation of HPB-ALL cells with either one of the anti-Ti mAb abrogated the expression of T3 and of the idiotypic structures. Our results suggest that mAb with an apparent unique specificity for the receptor of the immunizing T cell line HPB-ALL can activate Jurkat cells by a very weak cross-reaction with these cells, which is not detectable by conventional binding tests.

Corne cutanée du bord libre palpébral. A propos d'une observation anatomo-clinique [A cutaneous horn of the free margin of the eyelid: an anatomical and clinical observation].

A cutaneous horn was observed close to the free margin of the inferior right eyelid in a 26-year-old-male patient. A minimal resection was primarily performed. Histopathologic study disclosed a precancerous keratosis. As the tumor had not been entirely excised, a complementary resection was performed secondarily to obtain the entire resection of the tumor.