Computer-aided protein–ligand binding predictions are a valuable help in drug discovery. Protein–ligand docking programs generally consist of two main components: a scoring function and a search ...algorithm. It is of interest to evaluate the intrinsic performance of scoring functions, independently of conformational exploration, to understand their strengths and weaknesses and suggest improvements. The comparative assessment of scoring functions (CASF) provides such an evaluation. Here we add the AutoDock and Vina scoring functions to the CASF-2013 benchmark. We find that these popular, free software docking programs are generally in the first half (AutoDock) and first quarter (Vina) among all methods tested in CASF-2013. Vina is the best of all methods in terms of docking power. We also find that ligand minimization has an important impact, reducing the performance difference between AutoDock and Vina.
Designed enzymes are of fundamental and technological interest. Experimental directed evolution still has significant limitations, and computational approaches are a complementary route. A designed ...enzyme should satisfy multiple criteria: stability, substrate binding, transition state binding. Such multi-objective design is computationally challenging. Two recent studies used adaptive importance sampling Monte Carlo to redesign proteins for ligand binding. By first flattening the energy landscape of the apo protein, they obtained positive design for the bound state and negative design for the unbound. We have now extended the method to design an enzyme for specific transition state binding, i.e., for its catalytic power. We considered methionyl-tRNA synthetase (MetRS), which attaches methionine (Met) to its cognate tRNA, establishing codon identity. Previously, MetRS and other synthetases have been redesigned by experimental directed evolution to accept noncanonical amino acids as substrates, leading to genetic code expansion. Here, we have redesigned MetRS computationally to bind several ligands: the Met analog azidonorleucine, methionyl-adenylate (MetAMP), and the activated ligands that form the transition state for MetAMP production. Enzyme mutants known to have azidonorleucine activity were recovered by the design calculations, and 17 mutants predicted to bind MetAMP were characterized experimentally and all found to be active. Mutants predicted to have low activation free energies for MetAMP production were found to be active and the predicted reaction rates agreed well with the experimental values. We suggest the present method should become the paradigm for computational enzyme design.
Barbiturates are proposed as a second/third line treatment for intracranial hypertension in traumatic brain injury (TBI) patients, but the literature remains uncertain regarding their benefit/risk ...balance. We aimed to evaluate the impact of barbiturates therapy in TBI patients with early intracranial hypertension on the intensive care unit (ICU) survival, the occurrence of ventilator-associated pneumonia (VAP), and the patient's functional status at three months. We used the French AtlanREA prospective cohort of trauma patients. Using a propensity score-based methodology (inverse probability of treatment weighting), we compared patients having received barbiturates within the first 24 hours of admission (barbiturates group) and those who did not (control group). We used cause-specific Cox models for ICU survival and risk of VAP, and logistic regression for the 3-month Glasgow Outcome Scale (GOS) evaluation. Among the 1396 patients with severe trauma, 383 had intracranial hypertension on admission and were analyzed. Among them, 96 (25.1%) received barbiturates. The early use of barbiturates was significantly associated with increased ICU mortality (HR = 1.85, 95%CI 1.03-3.33). However, barbiturates treatment was not significantly associated with VAP (HR = 1.02, 95%CI 0.75-1.41) or 3-month GOS (OR = 1.67, 95%CI 0.84-3.33). Regarding the absence of relevant clinical trials, our results suggest that each early prescription of barbiturates requires a careful assessment of the benefit/risk ratio.
Since the validation of the sentinel node technique (SLN) for vulvar cancer 20 years ago, this technique has been introduced in the management of operable cervical cancer and endometrial cancer. For ...cervical cancer a "one fits all" attitude has mainly been presented. However, this approach, consisting of a frozen section during the operation, can be discussed in some stages. We present and discuss the main option for each stage, as well as some secondary possibilities. For endometrial cancer, SLN is now the technique of choice for the nodal staging of low- and intermediate-risk groups. Some discussion exists for the high-risk group. We also discuss the impacts of using preoperatively the molecular classification of endometrial cancer. Patients with POLE or TP53 mutations could have different nodal staging. The story of SLN in uterine cancers is not finished. We propose a comprehensive algorithm of SLN in early cervical and endometrial cancers. However, several ongoing trials will give us important data in the coming years. They could substantially change these propositions.
Propulsion systems based on the constant-pressure combustion process have reached maturity in terms of performance, which is close to its theoretical limit. Technological breakthroughs are needed to ...develop more efficient transportation systems that meet today’s demands for reduced environmental impact and increased performance. The Rotating Detonation Engine (RDE), a specific implementation of the detonation process, appears today as a promising candidate due to its high thermal efficiency, wide operating Mach range, short combustion time and, thus, high compactness. Following the first proofs of concept presented in the 1960s, the last decade has seen a significant increase in laboratory demonstrators with different fuels, injection techniques, operating conditions, dimensions and geometric configurations. Recently, two flight tests of rocket-type RDEs have been reported in Japan and Poland, supervized by Professors Kasahara (Nagoya University) and Wolanski (Warsaw University), respectively. Engineering approaches are now required to design industrial systems whose missions impose efficiency and reliability constraints. The latter may render ineffective the simplified solutions and configurations developed under laboratory conditions. This requires understanding the fundamentals of detonation dynamics relevant to the RDE and the interrelated optimizations of the device components. This article summarizes some of the authors’ experimental and numerical work on fundamental and applied issues now considered to affect, individually or in combination, the efficiency and reliability of the RDE. These are the structure of the detonation reaction zone, the detonation dynamics for rotating regimes, the injection configurations, the chamber geometry, and the integration constraints.
Objective The aim of this study was to develop a new diagnostic tool to predict lymph node metastasis (LNM) in patients with advanced epithelial ovarian cancer undergoing primary cytoreductive ...surgery. Materials and method The FRANCOGYN group's multicenter retrospective ovarian cancer cohort furnished the patient population on which we developed a logistic regression model. The prediction model equation enabled us to create LNM risk groups with simple lymphadenectomy decision rules associated with a user-friendly free interactive web application called shinyLNM. Results 277 patients from the FRANCOGYN cohort were included; 115 with no LNM and 162 with LNM. Three variables were independently and significantly (p<0.05) associated with LNM in multivariate analysis: pelvic and/or para-aortic LNM on CT and/or PET/CT (p<0.00), initial PCI greater than or equal to 10 and/or diaphragmatic carcinosis (p = 0.02), and initial CA125 greater than or equal to 500 (p = 0.02). The ROC-AUC of this prediction model after leave-one-out cross-validation was 0.72. There was no difference between the predicted and the observed probabilities of LNM (p = 0.09). Specificity for the group at high risk of LNM was 83.5%, the LR+ was 2.73, and the observed probability of LNM was 79.3%; sensitivity for the group at low-risk of LNM was 92.0%, the LR- was 0.24, and the observed probability of LNM was 25.0%. Conclusion This new tool may prove useful for improving surgical planning and provide useful information for patients.
Therapeutic strategies for epithelial ovarian cancers are evolving with the advent of immunotherapy, such as PD-L1 inhibitors, with encouraging results. However, little data are available on PDL-1 ...expression in ovarian cancers. Thus, we set out to determine the PD-L1 expression according to histological subtype. We evaluated the expression of two PD-L1 clones - QR1 and E1L3N - with two scores, one based on the percentage of labeled tumor cells (tumor proportion score, TPS) and the other on labeled immune cells (combined proportion score, CPS) in a consecutive retrospective series of 232 ovarian cancers. PD-L1 expression was more frequent in high grade serous carcinoma (27.5% with E1L3N clone and 41.5% with QR1 clone), grade 3 endometrioid carcinoma (25% with E1L3N clone and 50% with QR1 clone), and clear-cell carcinomas (27.3% with E1L3N clone and 29.6% with QR1 clone) than other histological subtypes with CPS score. Using the CPS score, 17% of cases were labeled with E1L3N vs 28% with QR1. Using the TPS score, 14% of cases were positive to E1L3N vs 17% for QR1. For TPS and CPS, respectively, 77% and 78% of the QR1 cases were concordant with E1L3N for the thresholds of 1%. Overall and progression-free survival between PD-L1 positive and PD-L1 negative patients were not different across all histological types, and each subtype in particular for serous carcinomas expressing PD-L1. Expression of PD-L1 is relatively uncommon in epithelium ovarian tumors. When positive, usually <10% of tumor cells are labeled. QR1 clone and CPS appear the best tools to evaluate PD-L1 expression.
Lymph node status is a major prognostic factor in early-stage cervical cancer. Predicting the risk of lymph node metastasis is essential for optimal therapeutic management. The aim of the study was ...to develop a web-based application to predict the risk of lymph node metastasis in patients with early-stage (IA1 with positive lymph vascular space invasion, IA2 and IB1) cervical cancer.
We performed a secondary analysis of data from two prospective multicenter trials, Senticol 1 and 2 pooled together in the training dataset. The histological risk factors were included in a multivariate logistic regression model in order to determine the most suitable prediction model. An internal validation of the chosen prediction model was then carried out by a cross validation of the 'leave one out cross validation' type. The prediction model was implemented in an interactive online application of the 'Shinyapp' type. Finally, an external validation was performed with a retrospective cohort from L'Hôtel-Dieu de Québec in Canada.
Three hundred twenty-one patients participating in Senticol 1 and 2 were included in our training analysis. Among these patients, 280 did not present lymph node invasion (87.2%), 13 presented isolated tumor cells (4%), 11 presented micrometastases (3.4%) and 17 macrometastases (5.3%). Tumor size, presence of lymph-vascular space invasion and stromal invasion were included in the prediction model. The Receiver Operating Characteristic (ROC) Curve from this model had an area under the curve (AUC) of 0.79 (95% CI 0.69- 0.90). The AUC from the cross validation was 0.65. The external validation on the Canadian cohort confirmed a good discrimination of the model with an AUC of 0.83.
This is the first study of a prediction score for lymph node involvement in early-stage cervical cancer that includes internal and external validation. The web application is a simple, practical, and modern method of using this prediction score to assist in clinical management.
Survival disparities persist in ovarian cancer and may be linked to the environments in which patients live. The main objective of this study was to analyze the global impact of the area of residence ...of ovarian cancer patients on overall survival. The data were obtained from the Surveillance, Epidemiology and End Results (SEER) database. We included all the patients with epithelial ovarian cancers diagnosed between 2010 and 2016. The areas of residence were analyzed by the hierarchical clustering of the principal components to group similar counties. A multivariable Cox proportional hazards model was then fitted to evaluate the independent effect of each predictor on overall survival. We included a total of 16,806 patients. The clustering algorithm assigned the 607 counties to four clusters, with cluster 1 being the most disadvantaged and cluster 4 having the highest socioeconomic status and best access to care. The area of residence cluster remained a statistically significant independent predictor of overall survival in the multivariable analysis. The patients living in cluster 1 had a risk of death more than 25% higher than that of the patients living in cluster 4. This study highlights the importance of considering the sociodemographic factors within the patient's area of residence when developing a care plan and follow-up.
Computational protein design aims to create proteins with novel properties. A key element is the energy or scoring function used to select the sequences and conformations. We study the performance of ...an “MMGBSA” energy function, which combines molecular mechanics terms, a generalized Born and surface area (GBSA) solvent model, with approximations that make the model pairwise additive. Our approach is implemented in the Proteus software. The use of a physics-based energy function ensures a certain model transferability and explanatory power. As a first test, we redesign the sequence of nine proteins, one position at a time, with the rest of the protein having its native sequence and crystallographic conformation. As a second test, all positions are designed together. The contributions of individual energy terms are evaluated, and various parametrizations are compared. We find that the GB term significantly improves the results compared to simple Coulomb electrostatics but is affected by pairwise decomposition errors when all positions are designed together. The SA term, with distinct energy coefficients for nonpolar and polar atoms, makes a decisive contribution to obtain realistic protein sequences and can partially compensate for the absence of a GB term. With the best GBSA protocol, we obtain nativelike protein cores and Superfamily recognition of almost all of our sequences.
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