Structural assessment of single amino acid mutations: application to TP53 function.

Single amino acid substitution is the type of protein alteration most related to human diseases. Current studies seek primarily to distinguish neutral mutations from harmful ones. Very few methods offer an explanation of the final prediction result in terms of the probable structural or functional effect on the protein. In this study, we describe the use of three novel parameters to identify experimentally-verified critical residues of the TP53 protein (p53). The first two parameters make use of a surface clustering method to calculate the protein surface area of highly conserved regions or regions with high nonlocal atomic interaction energy (ANOLEA) score. These parameters help identify important functional regions on the surface of a protein. The last parameter involves the use of a new method for pseudobinding free-energy estimation to specifically probe the importance of residue side-chains to the stability of protein fold. A decision tree was designed to optimally combine these three parameters. The result was compared to the functional data stored in the International Agency for Research on Cancer (IARC) TP53 mutation database. The final prediction achieved a prediction accuracy of 70% and a Matthews correlation coefficient of 0.45. It also showed a high specificity of 91.8%. Mutations in the 85 correctly identified important residues represented 81.7% of the total mutations recorded in the database. In addition, the method was able to correctly assign a probable functional or structural role to the residues. Such information could be critical for the interpretation and prediction of the effect of missense mutations, as it not only provided the fundamental explanation of the observed effect, but also helped design the most appropriate laboratory experiment to verify the prediction results.

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.

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.

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.

Assessment of total energy expenditure in free-living patients with cystic fibrosis.

The increase in resting energy expenditure (REE) reported in patients with cystic fibrosis (CF) does not necessarily imply an increase in total energy expenditure (TEE). In this study REE was assessed with open-circuit indirect calorimetry, and free-living 24-hour TEE with the heart rate method. Thirteen patients with CF, aged 8 to 24 years, with adequate nutritional status and moderately decreased pulmonary function, were studied. They were compared with 13 healthy control subjects matched for gender, age, height, and nutritional status. Resting energy expenditure was higher in patients with CF (1512 +/- 88 kcal/day) than in control subjects (1339 +/- 76 kcal/day; p less than 0.01), whereas free-living 24-hour TEE (2345 +/- 127 kcal/day and 2358 +/- 256 kcal/day, respectively) and net mechanical work efficiency of walking on a treadmill (20.4 +/- 0.7% and 19.8 +/- 0.6%, respectively) were similar. Respiratory quotient was higher in patients with CF than in control subjects at rest (0.834 +/- 0.009 vs 0.797 +/- 0.008; p less than 0.05), and tended to remain so during physical exercise, indicating a higher contribution of carbohydrate oxidation to energy expenditure. We conclude that in free living conditions, patients with CF can compensate for their increase in REE by a reduction in spontaneous physical activities or other yet undefined mechanisms.

Free-living energy expenditure assessed by two different methods in rural Gambian men.

OBJECTIVE: To assess total free-living energy expenditure (EE) in Gambian farmers with two independent methods, and to determine the most realistic free-living EE and physical activity in order to establish energy requirements for rural populations in developing countries. DESIGN: In this cross-sectional study two methods were applied at the same time. SETTING: Three rural villages and Dunn Nutrition Centre Keneba, MRC, The Gambia. SUBJECTS: Eight healthy, male subjects were recruited from three rural Gambian villages in the sub-Sahelian area (age: 25 +/- 4y; weight: 61.2 +/- 10.1 kg; height: 169.5 +/- 6.5 cm, body mass index: 21.2 +/- 2.5 kg/m2). INTERVENTION: We assessed free-living EE with two inconspicuous and independent methods: the first one used doubly labeled water (DLW) (2H2 18O) over a period of 12 days, whereas the second one was based on continuous heart rate (HR) measurements on two to three days using individual regression lines (HR vs EE) established by indirect calorimetry in a respiration chamber. Isotopic dilution of deuterium (2H2O) was also used to assess total body water and hence fat-free mass (FFM). RESULTS: EE assessed by DLW was found to be 3880 +/- 994 kcal/day (16.2 +/- 4.2 MJ/day). Expressed per unit body weight the EE averaged 64.2 +/- 9.3 kcal/kg/d (269 +/- 38 kJ/kg/d). These results were consistent with the EE results assessed by HR: 3847 +/- 605 kcal/d (16.1 +/- 2.5 MJ/d) or 63.4 +/- 8.2 kcal/kg/d (265 +/- 34kJ/kg/d). Physical activity index, expressed as a multiple of basal metabolic rate (BMR), averaged 2.40 +/- 0.41 (DLW) or 2.40 +/- 0.28 (HR). CONCLUSIONS: These findings suggest an extremely high level of physical activity in Gambian men during intense agricultural work (wet season). This contrasts with the relative food shortage, previously reported during the harvesting period. We conclude that the assessment of EE during the agricultural season in non-industrialized countries needs further investigations in order to obtain information on the energy requirement of these populations. For this purpose the use of the DLW and HR methods have been shown to be useful and complementary.

Free-living energy expenditure measured by two independent techniques in pregnant and nonpregnant Gambian women.

Free-living energy expenditure (EE) was assessed in 37 young pregnant Gambian women at the 12th (n = 11, 53.5 +/- 1.7 kg), 24th (n = 14, 54.7 +/- 2.1 kg), and 36th (n = 12, 65.0 +/- 2.6 kg) wk of pregnancy and was compared with nonpregnant nonlactating (NPNL) control women (n = 12, 50.3 +/- 1.6 kg). The following two methods were used to assess EE: 1) the heart rate (HR) method using individual regression lines (HR vs EE) established at different activity levels in a respiration chamber and 2) the doubly labeled water (2H2(18)O) method in a subgroup of 25 pregnant and 7 control women. With the HR method the EE during the agricultural rainy season was found to be 2,408 +/- 87, 2,293 +/- 122, and 2,782 +/- 130 kcal/day at 12, 24, and 36 wk of gestation and were not significantly different from the control group (2,502 +/- 133 kcal/day). These findings were confirmed by the 2H2(18)O measurements, which failed to show any effect of pregnancy on EE. Expressed per unit body weight, the free-living EE was found to be lower (P less than 0.01 with 2H2(18)O method) at 36 wk of gestation than in the NPNL group. It is concluded that, in these Gambian women, energy-sparing mechanisms that contribute to meet the additional energy stress of gestation are operating during pregnancy (e.g., diminished spontaneous physical activity).

Prediction of resting energy expenditure from fat-free mass and fat mass.

On the basis of literature values, the relationship between fat-free mass (FFM), fat mass (FM), and resting energy expenditure [REE (kJ/24 h)] was determined for 213 adults (86 males, 127 females). The objectives were to develop a mathematical model to predict REE based on body composition and to evaluate the contribution of FFM and FM to REE. The following regression equations were derived: 1) REE = 1265 + (93.3 x FFM) (r2 = 0.727, P < 0.001); 2) REE = 1114 + (90.4 x FFM) + (13.2 x FM) (R2 = 0.743, P < 0.001); and 3) REE = (108 x FFM) + (16.9 x FM) (R2 = 0.986, P < 0.001). FM explained only a small part of the variation remaining after FFM was accounted for. The models that include both FFM and FM are useful in examination of the changes in REE that occur with a change in both the FFM and FM. To account for more of the variability in REE, FFM will have to be divided into organ mass and skeletal muscle mass in future analyses.

Daily energy expenditure in free-living conditions in obese and non-obese children: comparison of doubly labelled water (2H2(18)O) method and heart-rate monitoring.

OBJECTIVE: To compare the heart-rate monitoring with the doubly labelled water (2H2(18)O) method to estimate total daily energy expenditure in obese and non-obese children. DESIGN: Cross sectional study of obese and normal weight children. SUBJECTS: 13 prepubertal children: six obese (4M, 2F, 9.1 +/- 1.5 years, 47.3 +/- 9.7 kg) and seven non-obese (3M, 4F, 9.3 +/- 0.6 years, 31.8 +/- 3.2 kg). MEASUREMENTS: Total daily energy expenditure was assessed by means of the doubly labelled water method (TEEDLW) and of heart-rate monitoring (TEEHR). RESULTS: TEEHR was significantly (P < 0.05) higher than TEEDLW in obese children (9.47 +/- 0.84 MJ/d vs 8.99 +/- 0.63 MJ/d) whereas it was not different in non-obese children (8.43 +/- 2.02 MJ/d vs 8.42 +/- 2.30 MJ/d, P = NS). The difference of TEE assessed by HR monitoring in the obese group averaged 6.2 +/- 4.7%. At the individual level, the degree of agreement (difference between TEEHR and TEEDLW +/- 2s.d.) was low both in obese (-0.36, 1.32 MJ/d) and in non-obese children (-1.30, 1.34 MJ/d). At the group level, the agreement between the two methods was good in nonobese children (95% c.i. for the bias:-0.59, 0.63 MJ/d) but not in obese children (0.04, 0.92 MJ/d). Duration of sleep and energy expenditure during resting and physical activity were not significantly different in the two groups. Patterns of heart-rate (or derived energy expenditure) during the day-time were similar in obese and non-obese children. CONCLUSION: The HR monitoring technique provides an estimation of TEE close to that assessed by the DLW method in non-obese prepubertal children. In comparison with DLW, the HR monitoring method yields a greater TEE value in obese children.

Total energy expenditure and patterns of activity in 8-10-year-old obese and nonobese children.

Total energy expenditure (TEE) and patterns of activity were measured by means of a heart rate (HR)-monitoring method in a group of 8-10-year-old children including 13 obese children (weight, 46 +/- 10 kg; fat mass: 32 +/- 9%) and 16 nonobese children (weight, 31 +/- 5 kg; fat mass, 18 +/- 5%). Time for sleeping was not statistically different in the two groups of children (596 +/- 33 vs. 582 +/- 43 min; p = NS). Obese children spent more time doing sedentary activities (400 +/- 129 vs. 295 +/- 127 min; p < 0.05) and less time in nonsedentary activities (449 +/- 126 vs. 563 +/- 135 min; p < 0.05) than nonobese children. Time spent in moderate or vigorous activity-i.e., time spent at a HR between 50% of the maximal O2 uptake (peak VO2) and 70% peak VO2 (moderate) and at a HR > or = 70% peak VO2 (vigorous)-was not statistically different in obese and nonobese children (88 +/- 69 vs. 52 +/- 35 min and 20 +/- 21 vs. 16 +/- 13 min, respectively; p = NS). TEE was significantly higher in the obese group than in the nonobese group (9.46 +/- 1.40 vs. 7.51 +/- 1.67 MJ/day; p < 0.01). The energy expenditure for physical activity (plus thermogenesis) was significantly higher in the obese children (3.98 +/- 1.30 vs. 2.94 +/- 1.39 MJ/day; p < 0.05). The proportion of TEE daily devoted to physical activity (plus thermogenesis) was not significantly different in the two groups, as shown by the ratio between TEE and the postabsorptive metabolic rate (PMR): 1.72 +/- 0.25 obese vs 1.61 +/- 0.28 non-obese. In conclusion, in free-living conditions obese children have a higher TEE than do nonobese children, despite the greater time devoted to sedentary activities. The higher energy cost to perform weight-bearing activities as well as the higher absolute PMR of obese children help explain this apparent paradox.

Assessment of free-living physical activity in humans: an overview of currently available and proposed new measures.

The number of physical activity measures and indexes used in the human literature is large and may result in some difficulty for the average investigator to choose the most appropriate measure. Accordingly, this review is intended to provide information on the utility and limitations of the various measures. Its primary focus is the objective assessment of free-living physical activity in humans based on physiological and biomechanical methods. The physical activity measures have been classified into three categories: Measures based on energy expenditure or oxygen uptake, such as activity energy expenditure, activity-related time equivalent, physical activity level, physical activity ratio, metabolic equivalent, and a new index of potential interest, daytime physical activity level. Measures based on heart rate monitoring, such as net heart rate, physical activity ratio heart rate, physical activity level heart rate, activity-related time equivalent, and daytime physical activity level heart rate. Measures based on whole-body accelerometry (counts/U time). Quantification of the velocity and duration of displacement in outdoor conditions by satellites using the Differential Global Positioning System may constitute a surrogate for physical activity, because walking is the primary activity of man in free-living conditions. A general outline of the measures and indexes described above is presented in tabular form, along with their respective definition, usual applications, advantages, and shortcomings. A practical example is given with typical values in obese and non-obese subjects. The various factors to be considered in the selection of physical activity methods include experimental goals, sample size, budget, cultural and social/environmental factors, physical burden for the subject, and statistical factors, such as accuracy and precision. It is concluded that no single current technique is able to quantify all aspects of physical activity under free-living conditions, requiring the use of complementary methods. In the future, physical activity sensors, which are of low-cost, small-sized, and convenient for subjects, investigators, and clinicians, are needed to reliably monitor, during extended periods in free-living situations, small changes in movements and grade as well as duration and intensity of typical physical activities.