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.

Design of new tools to improve the efficacy of DNA-damaging drugs used in cancer therapy

Résumé Les tumeurs sont diverses et hétérogènes, mais toutes partagent la capacité de proliférer sans contrôle. Une prolifération dérégulée de cellules couplée à une insensibilité à une réponse apoptotique constitue une condition minimale pour que l'évolution d'une tumeur se produise. Un des traitements les plus utilisés pour traité le cancer à l'heure actuelle sont les chimiothérapies, qui sont fréquemment des composés chimiques qui induisent des dommages dans l'ADN. Les agents anticancéreux sont efficaces seulement quand les cellules tumorales sont plus aisément tuées que le tissu normal environnant. L'efficacité de ces agents est en partie déterminée par leur capacité à induire l'apoptose. Nous avons récemment démontré que la protéine RasGAP est un substrat non conventionnel des caspases parce elle peut induire à la fois des signaux anti et pro-apoptotiques, selon l'ampleur de son clivage par les caspases. A un faible niveau d'activité des caspases, RasGAP est clivé, générant deux fragments (le fragment N et le fragment C). Le fragment N semble être un inhibiteur général de l'apoptose en aval de l'activation des caspases. À des niveaux plus élevés d'activité des caspases, la capacité du fragment N de contrecarrer l'apoptose est supprimée quand il est clivé à nouveau par les caspases. Ce dernier clivage produit deux nouveaux fragments, N 1 et N2, qui contrairement au fragment N sensibilisent efficacement des cellules cancéreuses envers des agents chimiothérapeutiques. Dans cette étude nous avons prouvé qu'un peptide, appelé par la suite TAT-RasGAP317-326, qui est dérivé du fragment N2 de RasGAP et est rendu perméable aux cellules, sensibilise spécifiquement des cellules cancéreuses à trois génotoxines différentes utilisées couramment dans des traitements anticancéreux, et cela dans des modèles in vitro et in vivo. Il est important de noté que ce peptide semble ne pas avoir d'effet sur des cellules non cancéreuses. Nous avons également commencé à caractériser les mécanismes moléculaires expliquant les fonctions de sensibilisation de TAT-RasGAP317-326. Nous avons démontré que le facteur de transcription p53 et une protéine sous son activité transcriptionelle, nommée Puma, sont indispensables pour l'activité de TAT-RasGAP317-326. Nous avons également prouvé que TAT-RasGAP317-326 exige la présence d'une protéine appelée G3BP1, une protéine se liant a RasGAP, pour potentialisé les effets d'agents anticancéreux. Les données obtenues dans cette étude montrent qu'il pourrait être possible d'augmenter l'efficacité des chimiothérapies à l'aide d'un composé capable d'augmenter la sensibilité des tumeurs aux génotoxines et ainsi pourrait permettre de traiter de manière plus efficace des patients sous traitement chimiothérapeutiques. Summary Tumors are diverse and heterogeneous, but all share the ability to proliferate without control. Deregulated cell proliferation coupled with suppressed apoptotic sensitivity constitutes a minimal requirement upon which tumor evolution occurs. One of the most commonly used treatments is chemotherapy, which frequently uses chemical compounds that induce DNA damages. Anticancer agents are effective only when tumors cells are more readily killed than the surrounding normal tissue. The efficacy of these agents is partly determined by their ability to induce apoptosis. We have recently demonstrated that the protein RasGAP is an unconventional caspase substrate because it can induce both anti- and pro-apoptotic signals, depending on the extent of its cleavage by caspases. At low levels of caspase activity, RasGAP is cleaved, generating an N-terminal fragment (fragment N) and a C-terminal fragment (fragment C). Fragment N appears to be a general Mocker of apoptosis downstream of caspase activation. At higher levels of caspase activity, the ability of fragment N to counteract apoptosis is suppressed when it is further cleaved. This latter cleavage event generates two fragments, N1 and N2, which in contrast to fragment N potently sensitizes cancer cells toward DNA-damaging agents induced apoptosis. In the present study we show that a cell permeable peptide derived from the N2 fragment of RasGAP, thereafter called TAT-RasGAP317-326, specifically sensitizes cancer cells to three different genotoxins commonly used in chemotherapy in vitro and in vivo models. Importantly this peptide seems not to have any effect on non cancer cells. We have also started to characterize the molecular mechanisms underlying the sensitizing functions of TAT-RasGAP317-326. We have demonstrated that the p53 transcription factor and a protein under its transcriptional activity, called Puma, are required for the activity of TATRasGAP317-326. We have also showed that TAT-RasGAP317-326 requires the presence of a protein called G3BP1, which have been shown to interact with RasGAP, to increase the effect of the DNA-damaging drug cisplatin. The data obtained in this study showed that it is possible to increase the efficacy of current used chemotherapies with a compound able to increase the efficacy of genotoxins which could be beneficial for patients subjected to chemotherapy.

Blind docking of 260 protein-ligand complexes with EADock 2.0.

Molecular docking softwares are one of the important tools of modern drug development pipelines. The promising achievements of the last 10 years emphasize the need for further improvement, as reflected by several recent publications (Leach et al., J Med Chem 2006, 49, 5851; Warren et al., J Med Chem 2006, 49, 5912). Our initial approach, EADock, showed a good performance in reproducing the experimental binding modes for a set of 37 different ligand-protein complexes (Grosdidier et al., Proteins 2007, 67, 1010). This article presents recent improvements regarding the scoring and sampling aspects over the initial implementation, as well as a new seeding procedure based on the detection of cavities, opening the door to blind docking with EADock. These enhancements were validated on 260 complexes taken from the high quality Ligand Protein Database [LPDB, (Roche et al., J Med Chem 2001, 44, 3592)]. Two issues were identified: first, the quality of the initial structures cannot be assumed and a manual inspection and/or a search in the literature are likely to be required to achieve the best performance. Second the description of interactions involving metal ions still has to be improved. Nonetheless, a remarkable success rate of 65% was achieved for a large scale blind docking assay, when considering only the top ranked binding mode and a success threshold of 2 A RMSD to the crystal structure. When looking at the five-top ranked binding modes, the success rate increases up to 76%. In a standard local docking assay, success rates of 75 and 83% were obtained, considering only the top ranked binding mode, or the five top binding modes, respectively.

Multigenic lentiviral vectors for combined and tissue-specific expression of miRNA- and protein-based antiangiogenic factors.

Lentivirus-based gene delivery vectors carrying multiple gene cassettes are powerful tools in gene transfer studies and gene therapy, allowing coexpression of multiple therapeutic factors and, if desired, fluorescent reporters. Current strategies to express transgenes and microRNA (miRNA) clusters from a single vector have certain limitations that affect transgene expression levels and/or vector titers. In this study, we describe a novel vector design that facilitates combined expression of therapeutic RNA- and protein-based antiangiogenic factors as well as a fluorescent reporter from back-to-back RNApolII-driven expression cassettes. This configuration allows effective production of intron-embedded miRNAs that are released upon transduction of target cells. Exploiting such multigenic lentiviral vectors, we demonstrate robust miRNA-directed downregulation of vascular endothelial growth factor (VEGF) expression, leading to reduced angiogenesis, and parallel impairment of angiogenic pathways by codelivering the gene encoding pigment epithelium-derived factor (PEDF). Notably, subretinal injections of lentiviral vectors reveal efficient retinal pigment epithelium-specific gene expression driven by the VMD2 promoter, verifying that multigenic lentiviral vectors can be produced with high titers sufficient for in vivo applications. Altogether, our results suggest the potential applicability of combined miRNA- and protein-encoding lentiviral vectors in antiangiogenic gene therapy, including new combination therapies for amelioration of age-related macular degeneration.

1D.03: Inactive matrix GLA protein is associated with renal resistive index in a population-based study

OBJECTIVE: Renal resistive index (RRI) varies directly with renal vascular stiffness and pulse pressure. RRI correlates positively with arteriolosclerosis in damaged kidneys and predicts progressive renal dysfunction. Matrix Gla-protein (MGP) is a vascular calcification inhibitor that needs vitamin K to be activated. Inactive MGP, known as desphospho-uncarboxylated MGP (dp-ucMGP), can be measured in plasma and has been associated with various cardiovascular (CV) markers, CV outcomes and mortality. In this study we hypothesize that increased RRI is associated with high levels of dp-ucMGP. DESIGN AND METHOD: We recruited participants via a multi-center family-based cross-sectional study in Switzerland exploring the role of genes and kidney hemodynamics in blood pressure regulation. Dp-ucMGP was quantified in plasma samples by sandwich ELISA. Renal doppler sonography was performed using a standardized protocol to measure RRIs on 3 segmental arteries in each kidney. The mean of the 6 measures was reported. Multiple regression analysis was performed to estimate associations between RRI and dp-ucMGP adjusting for sex, age, pulse pressure, mean pressure, renal function and other CV risk factors. RESULTS: We included 1035 participants in our analyses. Mean values were 0.64 ± 0.06 for RRI and 0.44 ± 0.21 (nmol/L) for dp-ucMGP. RRI was positively associated with dp-ucMGP both before and after adjustment for sex, age, body mass index, pulse pressure, mean pressure, heart rate, renal function, low and high density lipoprotein, smoking status, diabetes, blood pressure and cholesterol lowering drugs, and history of CV disease (P < 0.001). CONCLUSIONS: RRI is independently and positively associated with high levels of dp-ucMGP after adjustment for pulse pressure and common CV risk factors. Further studies are needed to determine if vitamin K supplementation can have a positive effect on renal vascular stiffness and kidney function.

In vivo imaging of the central and peripheral effects of sleep deprivation and suprachiasmatic nuclei lesion on PERIOD-2 protein in mice.

STUDY OBJECTIVES: That sleep deprivation increases the brain expression of various clock genes has been well documented. Based on these and other findings we hypothesized that clock genes not only underlie circadian rhythm generation but are also implicated in sleep homeostasis. However, long time lags have been reported between the changes in the clock gene messenger RNA levels and their encoded proteins. It is therefore crucial to establish whether also protein levels increase within the time frame known to activate a homeostatic sleep response. We report on the central and peripheral effects of sleep deprivation on PERIOD-2 (PER2) protein both in intact and suprachiasmatic nuclei-lesioned mice. DESIGN: In vivo and in situ PER2 imaging during baseline, sleep deprivation, and recovery. SETTINGS: Mouse sleep-recording facility. PARTICIPANTS: Per2::Luciferase knock-in mice. INTERVENTIONS: N/A. MEASUREMENTS AND RESULTS: Six-hour sleep deprivation increased PER2 not only in the brain but also in liver and kidney. Remarkably, the effects in the liver outlasted those observed in the brain. Within the brain the increase in PER2 concerned the cerebral cortex mainly, while leaving suprachiasmatic nuclei (SCN) levels unaffected. Against expectation, sleep deprivation did not increase PER2 in the brain of arrhythmic SCN-lesioned mice because of higher PER2 levels in baseline. In contrast, liver PER2 levels did increase in these mice similar to the sham and partially lesioned controls. CONCLUSIONS: Our results stress the importance of considering both sleep-wake dependent and circadian processes when quantifying clock-gene levels. Because sleep deprivation alters PERIOD-2 in the brain as well as in the periphery, it is tempting to speculate that clock genes constitute a common pathway mediating the shared and well-known adverse effects of both chronic sleep loss and disrupted circadian rhythmicity on metabolic health.

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.

Protein pocket and ligand shape comparison and its application in virtual screening.

Understanding molecular recognition is one major requirement for drug discovery and design. Physicochemical and shape complementarity between two binding partners is the driving force during complex formation. In this study, the impact of shape within this process is analyzed. Protein binding pockets and co-crystallized ligands are represented by normalized principal moments of inertia ratios (NPRs). The corresponding descriptor space is triangular, with its corners occupied by spherical, discoid, and elongated shapes. An analysis of a selected set of sc-PDB complexes suggests that pockets and bound ligands avoid spherical shapes, which are, however, prevalent in small unoccupied pockets. Furthermore, a direct shape comparison confirms previous studies that on average only one third of a pocket is filled by its bound ligand, supplemented by a 50 % subpocket coverage. In this study, we found that shape complementary is expressed by low pairwise shape distances in NPR space, short distances between the centers-of-mass, and small deviations in the angle between the first principal ellipsoid axes. Furthermore, it is assessed how different binding pocket parameters are related to bioactivity and binding efficiency of the co-crystallized ligand. In addition, the performance of different shape and size parameters of pockets and ligands is evaluated in a virtual screening scenario performed on four representative targets.

Attracting cavities for docking. Replacing the rough energy landscape of the protein by a smooth attracting landscape.

Molecular docking is a computational approach for predicting the most probable position of ligands in the binding sites of macromolecules and constitutes the cornerstone of structure-based computer-aided drug design. Here, we present a new algorithm called Attracting Cavities that allows molecular docking to be performed by simple energy minimizations only. The approach consists in transiently replacing the rough potential energy hypersurface of the protein by a smooth attracting potential driving the ligands into protein cavities. The actual protein energy landscape is reintroduced in a second step to refine the ligand position. The scoring function of Attracting Cavities is based on the CHARMM force field and the FACTS solvation model. The approach was tested on the 85 experimental ligand-protein structures included in the Astex diverse set and achieved a success rate of 80% in reproducing the experimental binding mode starting from a completely randomized ligand conformer. The algorithm thus compares favorably with current state-of-the-art docking programs. © 2015 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

Mechanisms of protein homeostasis in health, aging and disease.

When emerging from the ribosomes, new polypeptides need to fold properly, eventually translocate, and then assemble into stable, yet functionally flexible complexes. During their lifetime, native proteins are often exposed to stresses that can partially unfold and convert them into stably misfolded and aggregated species, which can in turn cause cellular damage and propagate to other cells. In animal cells, especially in aged neurons, toxic aggregates may accumulate, induce cell death and lead to tissue degeneration via different mechanisms, such as apoptosis as in Parkinson's and Alzheimer's diseases and aging in general. The main cellular mechanisms effectively controlling protein homeostasis in youth and healthy adulthood are: (1) the molecular chaperones, acting as aggregate unfolding and refolding enzymes, (2) the chaperone-gated proteases, acting as aggregate unfolding and degrading enzymes, (3) the aggresomes, acting as aggregate compacting machineries, and (4) the autophagosomes, acting as aggregate degrading organelles. For unclear reasons, these cellular defences become gradually incapacitated with age, leading to the onset of degenerative diseases. Understanding these mechanisms and the reasons for their incapacitation in late adulthood is key to the design of new therapies against the progression of aging, degenerative diseases and cancers.