Molecular glue degraders: exciting opportunities for novel drug discovery.

INTRODUCTION: Molecular Glue Degraders (MGDs) is a concept that refers to a class of compounds that facilitate the interaction between two proteins or molecules within a cell. These compounds act as bridge that enhances specific Protein-Protein Interactions (PPIs). Over the past decade, this technology has gained attention as a potential strategy to target proteins that were traditionally considered undruggable using small molecules. AREAS COVERED: This review presents the concept of cellular homeostasis and the balance between protein synthesis and protein degradation. The concept of protein degradation is concerned with molecular glues, which form part of the broader field of Targeted Protein Degradation (TPD). Next, pharmacochemical strategies for the rational design of MGDs are detailed and illustrated by examples of Ligand-Based (LBDD), Structure-Based (SBDD) and Fragment-Based Drug Design (FBDD). EXPERT OPINION: Expanding the scope of what can be effectively targeted in the development of treatments for diseases that are incurable or resistant to conventional therapies offers new therapeutic options. The treatment of microbial infections and neurodegenerative diseases is a major societal challenge, and the discovery of MGDs appears to be a promising avenue. Combining different approaches to discover and exploit a variety of innovative therapeutic agents will create opportunities to treat diseases that are still incurable.

Seafood dose parameters: Updating 210Po retention factors for cooking, decay loss and mariculture.

210Po has been identified as one of the main contributors to ingestion doses to humans, particularly from the consumption of seafood. The amount of 210Po activity concentration data for various types of seafood has increased greatly in recent times. However, to provide realistic seafood dose assessments, most 210Po data requires correction to account for losses that can occur before the seafood is actually consumed. Here we develop generic correction factors for the main processes associated with reduction of 210Po in seafood - leaching during cooking, radioactive decay between harvest and consumption, and sourcing from mariculture versus wild-caught. When seafood is cooked, the overall mean fraction of 210Po retained is 0.74 for all cooking and seafood types, with the means for various seafood types and cooking categories ranging from 0.56 to 1.03. When considering radioactive decay during the period between harvest and consumption, the overall mean fraction remaining is 0.81 across all seafood preservation/packaging types, with estimates ranging from 0.50 (canned seafood) to 0.98 (fresh seafood). Regarding mariculture influence, the available limited data suggest marine fish and crustaceans raised with processed feed have about one order of magnitude lower (×0.10) 210Po muscle content than wild-caught seafood of the same or similar species, although this ratio varies. Overall, this study concludes that 210Po activity concentrations in seafood at the time of ingestion may be reduced to only about 55% compared to when it was harvested. Therefore, correction factors must be applied to any data derived from environmental monitoring in order to achieve realistic dose estimates. The data also suggest lower 210Po ingestion doses for consumers who routinely favour cooked, long shelf-life and farmed fish/crustaceans. However, more data is needed in some categories, especially for cooking of molluscs and seaweed, and for the 210Po content in all farmed seafood.

Strengths of ecosystem services concept for radiation protection.

The successful ecosystem services concept, defined as the benefits people obtain from ecosystems is still not really reflected in the current approaches for protecting public and environment against radiation promoted by the International Commission on Radiological Protection or other similar approaches. Yet some recent thoughts from international organizations lead us to believe that an eco-based approach could be more promoted in the coming years in environmental radiation protection field. The French Institute for Radiation Protection and Nuclear Safety has identified different fields of application of this concept into radiation protection, in line with its integrated approach of radiological risks management. As the ecosystem services approach makes it possible to highlight biophysical and socio-economic approaches of the impacts of ionizing radiation on ecosystems, it represents a subject of primary importance for future works conducted by IRSN. However, the operationality of the ecosystem services concept is the subject of many debates. In many situations, scientists have not yet fully understood how radioactive contamination could affect ecosystem services, and how to articulate with certainty cause and effect relationships between state of an ecosystem and provision of services. In addition, the concept is also accompanied by contradictory perceptions of the status of humans in ecosystems. To solve these knowledge gaps and uncertainties, it is necessary to acquire robust data on the impacts of radiation on ecosystems both under experimental and realistic conditions, and to integrate all potential consequences (direct and indirect, ecotoxicological but also economic and cultural).

PROTAC technology: A new drug design for chemical biology with many challenges in drug discovery.

Target Protein Degradation TPD is a new avenue and revolutionary for therapeutics because redefining the principles of classical drug discovery and guided by event-based target activity rather than the occupancy-driven activity. Since the discovery of the first PROTAC in 2001, TPD represents a rapidly growing technology, with applications in both drug discovery and chemical biology. Over the last decade, many questions have been raised and today the knowledge gained by each team has elucidated a number of them, although there is still a long way to go. The objective of this work is to present the challenges that the PROTAC strategy has very recently addressed in drug design and discovery by presenting extremely recent results from the literature and to provide guidelines in the drug design of new PROTACs as successful therapeutic modality for medicinal chemists.

Foliar interception of radionuclides in dry conditions: a meta-analysis using a Bayesian modeling approach.

Uncertainty on the parameters that describe the transfer of radioactive materials into the (terrestrial) environment may be characterized thanks to datasets such as those compiled within International Atomic Energy Agency (IAEA) documents. Nevertheless, the information included in these documents is too poor to derive a relevant and informative uncertainty distribution regarding dry interception of radionuclides by the pasture grass and the leaves of vegetables. In this paper, 145 sets of dry interception measurements by the aboveground biomass of specific plants were collected from published scientific papers. A Bayesian meta-analysis was performed to derive the posterior probability distributions of the parameters that reflect their uncertainty given the collected data. Four competing models were compared in terms of both fitting performances and predictive abilities to reproduce plausible dry interception data. The asymptotic interception factor, applicable whatever the species and radionuclide to the highest aboveground biomass values (e.g. mature leafy vegetables), was estimated with the best model, to be 0.87 with a 95% credible interval (0.85, 0.89).

Assessment of dry and wet atmospheric deposits of radioactive aerosols: application to Fukushima radiocaesium fallout.

The Fukushima Dai-ichi nuclear accident led to massive atmospheric deposition of radioactive substances onto the land surfaces. The spatial distribution of deposits has been estimated by Japanese authorities for gamma-emitting radionuclides through either airborne monitoring surveys (since April 2011) or in situ gamma-ray spectrometry of bare soil areas (since summer 2011). We demonstrate that significant differences exist between the two surveys for radiocaesium isotopes and that these differences can be related to dry deposits through the use of physically based relationships involving aerosol deposition velocities. The methodology, which has been applied to cesium-134 and cesium-137 deposits within 80-km of the nuclear site, provides reasonable spatial estimations of dry and wet deposits that are discussed and compared to atmospheric numerical simulations from the Japanese Atomic Energy Agency and the French Institute of Radioprotection and Nuclear Safety. As a complementary approach to numerical simulations, this field-based analysis has the possibility to contribute information that can be applied to the understanding and assessment of dose impacts to human populations and the environment around Fukushima.

Fitting a lognormal distribution to enumeration and absence/presence data.

To fit a lognormal distribution to a complex set of microbial data, including detection data (e.g. presence or absence in 25g) and enumeration data (e.g. 30cfu/g), we compared two models: a model called M(CLD) based on data expressed as concentrations (in cfu/g) or censored concentrations (e.g. <10cfu/g, or >1cfu/25g) versus a model called M(RD) that directly uses raw data (presence/absence in test portions, and plate colony counts). We used these two models to simulated data sets, under standard conditions (limit of detection (LOD)=1cfu/25g; limit of quantification (LOQ)=10cfu/g) and used a maximum likelihood estimation method (directly for the model M(CLD) and via the Expectation-Maximisation (EM) algorithm for the model M(RD). The comparison suggests that in most cases estimates provided by the proposed model M(RD) are similar to those obtained by model M(CLD) accounting for censorship. Nevertheless, in some cases, the proposed model M(RD) leads to less biased and more precise estimates than model M(CLD).

Hierarchical Bayesian models to assess between- and within-batch variability of pathogen contamination in food.

Assessing within-batch and between-batch variability is of major interest for risk assessors and risk managers in the context of microbiological contamination of food. For example, the ratio between the within-batch variability and the between-batch variability has a large impact on the results of a sampling plan. Here, we designed hierarchical Bayesian models to represent such variability. Compatible priors were built mathematically to obtain sound model comparisons. A numeric criterion is proposed to assess the contamination structure comparing the ability of the models to replicate grouped data at the batch level using a posterior predictive loss approach. Models were applied to two case studies: contamination by Listeria monocytogenes of pork breast used to produce diced bacon and contamination by the same microorganism on cold smoked salmon at the end of the process. In the first case study, a contamination structure clearly exists and is located at the batch level, that is, between batches variability is relatively strong, whereas in the second a structure also exists but is less marked.

Design of challenge testing experiments to assess the variability of Listeria monocytogenes growth in foods.

The assessment of the evolution of micro-organisms naturally contaminating food must take into account the variability of biological factors, food characteristics and storage conditions. A research project involving eight French laboratories was conducted to quantify the variability of growth parameters of Listeria monocytogenes obtained by challenge testing in five food products. The residual variability corresponded to a coefficient of variation (CV) of approximately 20% for the growth rate (µ(max)) and 130% for the parameter K = µ(max) × lag. The between-batch and between-manufacturer variability of µ(max) was very dependent on the food tested and mean CV of approximately 20 and 35% were observed for these two sources of variability, respectively. The initial physiological state variability led to a CV of 100% for the parameter K. It appeared that repeating a limited number of three challenge tests with three different batches (or manufacturers) and with different initial physiological states seems often necessary and adequate to accurately assess the variability of the behavior of L. monocytogenes in a specific food produced by a given manufacturer (or for a more general food designation).

Probabilistic modeling of the fate of Listeria monocytogenes in diced bacon during the manufacturing process.

To assess the impact of the manufacturing process on the fate of Listeria monocytogenes, we built a generic probabilistic model intended to simulate the successive steps in the process. Contamination evolution was modeled in the appropriate units (breasts, dice, and then packaging units through the successive steps in the process). To calibrate the model, parameter values were estimated from industrial data, from the literature, and based on expert opinion. By means of simulations, the model was explored using a baseline calibration and alternative scenarios, in order to assess the impact of changes in the process and of accidental events. The results are reported as contamination distributions and as the probability that the product will be acceptable with regards to the European regulatory safety criterion. Our results are consistent with data provided by industrial partners and highlight that tumbling is a key step for the distribution of the contamination at the end of the process. Process chain models could provide an important added value for risk assessment models that basically consider only the outputs of the process in their risk mitigation strategies. Moreover, a model calibrated to correspond to a specific plant could be used to optimize surveillance.

Validation of a stochastic modelling approach for Listeria monocytogenes growth in refrigerated foods.

A stochastic modelling approach was developed to describe the distribution of Listeria monocytogenes contamination in foods throughout their shelf life. This model was designed to include the main sources of variability leading to a scattering of natural contaminations observed in food portions: the variability of the initial contamination, the variability of the biological parameters such as cardinal values and growth parameters, the variability of individual cell behaviours, the variability of pH and water activity of food as well as portion size, and the variability of storage temperatures. Simulated distributions of contamination were compared to observed distributions obtained on 5 day-old and 11 day-old cheese curd surfaces artificially contaminated with between 10 and 80 stressed cells and stored at 14°C, to a distribution observed in cold smoked salmon artificially contaminated with approximately 13 stressed cells and stored at 8°C, and to contaminations observed in naturally contaminated batches of smoked salmon processed by 10 manufacturers and stored for 10 days a 4°C and then for 20 days at 8°C. The variability of simulated contaminations was close to that observed for artificially and naturally contaminated foods leading to simulated statistical distributions properly describing the observed distributions. This model seems relevant to take into consideration the natural variability of processes governing the microbial behaviour in foods and is an effective approach to assess, for instance, the probability to exceed a critical threshold during the storage of foods like the limit of 100 CFU/g in the case of L. monocytogenes.

Quantitative risk assessment of Listeria monocytogenes in French cold-smoked salmon: II. Risk characterization.

A model for the assessment of exposure to Listeria monocytogenes from cold-smoked salmon consumption in France was presented in the first of this pair of articles (Pouillot et al., 2007, Risk Analysis, 27:683-700). In the present study, the exposure model output was combined with an internationally accepted hazard characterization model, adapted to the French situation, to assess the risk of invasive listeriosis from cold-smoked salmon consumption in France in a second-order Monte Carlo simulation framework. The annual number of cases of invasive listeriosis due to cold-smoked salmon consumption in France is estimated to be 307, with a very large credible interval ([10; 12,453]), reflecting data uncertainty. This uncertainty is mainly associated with the dose-response model. Despite the significant uncertainty associated with the predictions, this model provides a scientific base for risk managers and food business operators to manage the risk linked to cold-smoked salmon contaminated with L. monocytogenes. Under the modeling assumptions, risk would be efficiently reduced through a decrease in the prevalence of L. monocytogenes or better control of the last steps of the cold chain (shorter and/or colder storage during the consumer step), whereas reduction of the initial contamination levels of the contaminated products and improvement in the first steps of the cold chain do not seem to be promising strategies. An attempt to apply the recent risk-based concept of FSO (food safety objective) on this example underlines the ambiguity in practical implementation of the risk management metrics and the need for further elaboration on these concepts.

Quantitative risk assessment of Listeria monocytogenes in French cold-smoked salmon: I. Quantitative exposure assessment.

A quantitative assessment of the exposure to Listeria monocytogenes from cold-smoked salmon (CSS) consumption in France is developed. The general framework is a second-order (or two-dimensional) Monte Carlo simulation, which characterizes the uncertainty and variability of the exposure estimate. The model takes into account the competitive bacterial growth between L. monocytogenes and the background competitive flora from the end of the production line to the consumer phase. An original algorithm is proposed to integrate this growth in conditions of varying temperature. As part of a more general project led by the French Food Safety Agency (Afssa), specific data were acquired and modeled for this quantitative exposure assessment model, particularly time-temperature profiles, prevalence data, and contamination-level data. The sensitivity analysis points out the main influence of the mean temperature in household refrigerators and the prevalence of contaminated CSS on the exposure level. The outputs of this model can be used as inputs for further risk assessment.

Effect of the inoculum size on Listeria monocytogenes growth in structured media.

Obtaining quantitative data concerning the relative impact of various factors that may influence bacterial growth is of great importance for microbial risk assessment and predictive microbiology. The objective of this work was to investigate the effect of the initial Listeria monocytogenes density on all the growth parameters of this pathogen (lag phase duration, growth rate and maximum population density attained) on a sterile solid model system mimicking smoked fishery products, and in real cold-smoked salmon, a product likely to be contaminated with L. monocytogenes. Growth of the pathogen was monitored using a sensitive enumeration method, recently developed, based on membrane filtration followed by the transfer of the filter on a selective media [Gnanou Besse, N., Audinet, N., Beaufort, A., Colin, P., Cornu, M. and Lombard, B., 2004. A contribution to the improvement of Listeria monocytogenes enumeration in smoked salmon. International Journal of Food Microbiology, 91, 119-127.]. Depending on the experimental conditions, we found a significant effect of the inoculum size, both on lag phase duration, and on the maximal population attained. Moreover, the effect of the inoculum size on the growth of L. monocytogenes was dependent on a complex set of interactions. Factors which have appeared to impact on this effect include the cells physiological state, the background microflora, the texture of the media and the packaging system. It is important to understand how these interactions affect the growth of Listeria in order to predict and control its development in food.

Experimental evaluation of different precision criteria applicable to microbiological counting methods.

The dispersion of microbiological counting measurements, when repeating the analysis on the same material both within a laboratory (repeatability) and between laboratories (reproducibility) can be characterized by the organization of interlaboratory studies, where several sets of identical test materials are sent to several laboratories. Using the example of data generated by an interlaboratory study on enumeration of Listeria monocytogenes in foods by the standardized reference method (colony-count technique), 2 types of robust estimators of reproducibility standard deviations, based on the median, were examined, in comparison with the classical estimators, based on the mean. Experimental evaluation indicated that the 3 approaches gave consistent results for most of the combinations. The usual log10 transformation of the enumeration results was also questioned before these calculations were conducted.

Uncertainty distribution associated with estimating a proportion in microbial risk assessment.

The uncertainty associated with estimates should be taken into account in quantitative risk assessment. Each input's uncertainty can be characterized through a probabilistic distribution for use under Monte Carlo simulations. In this study, the sampling uncertainty associated with estimating a low proportion on the basis of a small sample size was considered. A common application in microbial risk assessment is the estimation of a prevalence, proportion of contaminated food products, on the basis of few tested units. Three Bayesian approaches (based on beta(0, 0), beta(1/2, 1/2), and beta(l, 1)) and one frequentist approach (based on the frequentist confidence distribution) were compared and evaluated on the basis of simulations. For small samples, we demonstrated some differences between the four tested methods. We concluded that the better method depends on the true proportion of contaminated products, which is by definition unknown in common practice. When no prior information is available, we recommend the beta (1/2, 1/2) prior or the confidence distribution. To illustrate the importance of these differences, the four methods were used in an applied example. We performed two-dimensional Monte Carlo simulations to estimate the proportion of cold smoked salmon packs contaminated by Listeria monocytogenes, one dimension representing within-factory uncertainty, modeled by each of the four studied methods, and the other dimension representing variability between companies.

Time-temperature profiles of chilled ready-to-eat foods in school catering and probabilistic analysis of Listeria monocytogenes growth.

The purpose of this study was to evaluate the chill chain in school catering by monitoring time-temperature profiles. Chilled ready-to-eat foods have been chosen as subject of this study because of their high risk due to their production, storage and distribution steps, separated in time, followed by consumption without any further thermal treatment. In order to integrate the effects of storage duration and storage temperature, a quantitative criterion, namely "TTE" or "Time-Temperature Equivalent", was proposed. To illustrate the sanitary consequences of the recorded thermal history, Listeria monocytogenes growth was predicted based on reference growth curves in chilled ready-to-eat food products. The study of five centralised kitchens and 11 school-lunch canteens demonstrated in general a satisfactory maintenance of the chill chain. However, the coincidence of extended storage duration (due to weekends) and temperature abuse was observed and could lead to a significant microbial development.

A contribution to the improvement of Listeria monocytogenes enumeration in cold-smoked salmon.

For the enumeration of Listeria monocytogenes in food, a sensitive enumeration method based on membrane filtration followed by transfer of the filter to a selective medium has been developed. This study was carried out with cold-smoked salmon, a product likely to be contaminated with L. monocytogenes. The operating protocol utilizes three filtration runs in parallel (5, 15 and 30 ml) of a 1 in 10 dilution of the salmon suspension through 0.45-microm pore-size cellulose ester membranes, and then culture of the filters on Aloa agar (AES Laboratoires, Combourg, France). The results obtained with the technique were compared with those from the reference EN ISO 11290-2 method and found to provide more precise results in the enumeration of L. monocytogenes from both artificially and naturally contaminated cold-smoked salmon. Moreover, for several samples contaminated at low levels, L. monocytogenes could be recovered only by the filtration method. The examination of increasing volumes of salmon suspension enabled readable results to be obtained for all levels of L. monocytogenes and competitive microflora investigated. In most cases, the optimised operating protocol enabled 5.1 g of salmon to be examined, instead of 0.01-0.1 g with the reference EN ISO 11290-2 method, thus improving the sensitivity of the method.

Estimation of uncertainty and variability in bacterial growth using Bayesian inference. Application to Listeria monocytogenes.

The usefulness of risk assessment is limited by its ability or inability to model and evaluate risk uncertainty and variability separately. A key factor of variability and uncertainty in microbial risk assessment could be growth variability between strains and growth model parameter uncertainty. In this paper, we propose a Bayesian procedure for growth parameter estimation which makes it possible to separate these two components by means of hyperparameters. This model incorporates in a single step the logistic equation with delay as a primary growth model and the cardinal temperature equation as a secondary growth model. The estimation of Listeria monocytogenes growth parameters in milk using literature data is proposed as a detailed application. While this model should be applied on genuine data, it is highlighted that the proposed approach may be convenient for estimating the variability and uncertainty of growth parameters separately, using a complete predictive microbiology model.

Modelling the competitive growth of Listeria monocytogenes and Listeria innocua in enrichment broths.

The overgrowth of Listeria innocua in enrichment broths designed for the isolation of Listeria monocytogenes is believed to result from two factors: a selective growth advantage of L. innocua, and/or an inhibitory interspecies interaction. The generation times of 13 isolates of L. innocua and L. monocytogenes were determined in Brain Heart Infusion (BHI) and a variety of enrichment media. No significant differences were found in growth characteristics between either species in the various media, suggesting that the growth advantage of L. innocua in enrichment media was not as significant as previously described. Kinetic analysis of mixed cultures of L. monocytogenes and isolates of L. innocua producing a variety of inhibitory activities demonstrated the possibility of an inhibitory interaction between these two species resulting in the overgrowth of the enrichment culture with L. innocua. Modelling the evolution of the ratio between two populations in an enrichment process was used to analyze the impact of a selective growth advantage in L. innocua in an enrichment process for growth of L. monocytogenes. These findings support the widely held view that an overgrowth of L. innocua in the enrichment process can result from both a selective growth advantage as well as the production of inhibitory compounds. From a practical perspective, these interactions can result in an increase in false negatives.