One of the primary tasks in vaccine design and development of immunotherapeutic drugs is to predict conformational B-cell epitopes corresponding to primary antibody binding sites within the antigen tertiary structure. To date, multiple approaches have been developed to address this issue. However, for a wide range of antigens their accuracy is limited. In this paper, we applied the transfer learning approach using pretrained deep learning models to develop a model that predicts conformational B-cell epitopes based on the primary antigen sequence and tertiary structure. A pretrained protein language model, ESM-1v, and an inverse folding model, ESM-IF1, were fine-tuned to quantitatively predict antibody-antigen interaction features and distinguish between epitope and non-epitope residues. The resulting model called SEMA demonstrated the best performance on an independent test set with ROC AUC of 0.76 compared to peer-reviewed tools. We show that SEMA can quantitatively rank the immunodominant regions within the SARS-CoV-2 RBD domain. SEMA is available at https:// github.com/AIRI-Institute/SEMAi and the web-interface http://sema.airi.net.
The results of the predictive analytical studies on Covid-19 incidence dynamics in Moscow, taking into account different changes in epidemic prevention measures, including vaccination coverage of the population, are presented.Research Objective. Using the new epidemiological model for analysis and prediction of the Covid-19 incidence dynamics in Moscow and outlining main strategies in implementing epidemic prevention measures (EPMs), including vaccination in 2020/2021.Materials and methods. The epidemiological model is based on the Russian approach to mathematical modeling of epidemics, known as Epiddynamics. The medium-term forecasting incorporated probable scenarios of epidemic development with different EPMs (isolation of the infected and contacts, breaking the transmission chains), including different rates of vaccination coverage in Moscow.Results and discussion. The computational simulations demonstrated that the incidence rate is likely to increase with scaling down EPMs and zero vaccination coverage. At the same time, the daily incidence rate depends on the degree of EPMs reduction and basically does not depend on the time when the reduction begins. With scaled-down EPMs, vaccination can decrease the incidence, though its effectiveness will depend on the time of its commencement, coverage and rate.Conclusion. The computational simulations showed that the vaccination will be efficient for prevention of new surges in COVID-19 cases only if the other EPMs (isolation of the infected and contacts, breaking the transmission chains) are still in place until the vaccination coverage reaches about 2 million people. Ideally, the measures aimed at isolation and breaking of transmission chains should be continued until the total vaccination coverage reaches 4 million people, after which the restrictive measures can be scaled down significantly. With vaccination coverage of 50% of the population of Moscow, the restrictive measures can be completely discontinued.
Background: The significant reduction of measles and rubella morbidity and child mortality, which allowed WHO to set a target for their elimination by 2010, is one of the finest examples of the vaccine prevention effectiveness in the fight against infectious diseases. However, in the period from 2010 to 2019 there was a controversial situation with respect to measles, characterized by the presence of high vaccination coverage of the population on the one hand, and an increase in the incidence on the other. Obviously, the key point in resolving these contradictions is to analyze the susceptibility of the population. Aim: Of the study was to assess the susceptibility of Moscow population to measles in the context of factors affecting its formationю. Methods: Epidemiological, serological, statistical methods and GIS technologies were used in the work. The serological study (using the solid-phase ELISA method) included 2410 blood serum samples collected between 2013 and 2017 from healthy residents of Moscow aged from birth to 60 years. On the basis of documents on sanitary and epidemic investigation of measles cases in Moscow (20132015) a relational database under the management of MySQL Database Management System was formed, based on the analysis of which the coverage of the population with preventive vaccinations was estimated. Results: Оn average, the proportion of seronegative persons to measles in 20162017, compared with 20132014 (20.5%) increased and amounted to 29.0% mainly due to the group over 36 years. The most vulnerable were children aged 12 years and 36 years, where the share of the immune persons amounted to 51,5% and 37.9%, respectively, at low coverage in a planned manner (55,9% [95% CI, 52.2 per cent; of 59.5%] and 75,3% [95% CI, 73.3 per cent; for 77.2%]). The proportion of vaccinated persons who lost post-vaccination immunity under the influence of factors preventing its formation (from 3.6% to 21.6% in the group of 714 years; from 11.8% to 26.4% in the group of 1517 years) was calculated. The possibility of visualizing the spread of measles on electronic maps for the territorial and temporal analysis of the epidemic situation is shown. Conclusions: It is reasonable to assume that over the time, the proportion of people who have suffered measles will decrease, and the proportion of people not covered by vaccination or lost post-vaccination immunity - increase, that can lead to a decrease in herd immunity and requires correction of vaccination work. The proposed information and analytical system for monitoring the epidemiological situation allows to work quickly with heterogeneous resources and choose on electronic maps the area of interest from the global level (country) to the local (house), which is necessary for the adoption of scientifically based preventive and epidemiological measures.
Measles is one of the preventable infections that does not lose its relevance to this day. In Russia, as well as throughout the world, waves of an increase in the incidence of measles are still being recorded, so in 2019 the maximum incidence rate over the past 20 years (3.05 %ооо) was noted. According to the current Measles Elimination Program of the Russian Federation, each case of this infection is subject to investigation, based on the results of which the epidemiologist organizes measures to prevent its spread in the outbreak. The main anti-epidemic measures in this case are isolation of the patient (at home or in a hospital according to clinical indications) and vaccination of persons in contact with him who need it. Thus, in order to prevent the occurrence of secondary cases, it is necessary to determine the vaccination and infectious history of all persons in contact with the sick person and vaccinate them no later than the seventh day from the moment the outbreak was registered. To date, it is difficult to generalize data from investigations of measles cases, despite their value for epidemiological diagnosis and the development of epidemiological surveillance (ES) tactics. The aim of the work was to improve the information support for the investigation of measles cases by creating and analyzing a database. The authors proposed a method for summarizing and analyzing the results of the investigation of measles cases using the formation of a database. For this purpose, about 1000 acts and reports on the results of the investigation of measles foci (on paper) registered in Moscow in the period from 2013 to 2015 were analyzed. The data contained in these documents is entered into the database, systematized in separate blocks and processed by the appropriate software for the purpose of their subsequent accumulation, storage and analysis. Based on the results of the work, the age composition of measles patients was analyzed. It was found that children under 18 years of age were more likely to have this infection, while the largest share among them was in persons aged 3–6 (32.4 %) and 7–14 years (25.0 %). The use of the database made it possible to confirm the high epidemiological effectiveness of the measles vaccine — the protection factor (E) was 86 %. Using the database, it was found that adults aged 20–35 years old were most actively vaccinated in measles foci (vaccination coverage was 57.7 %). With the threat of this infection, only 25.9 % of children (under 17 years old) who needed vaccination agreed to be vaccinated, and the percentage of refusals varied from 69.8 % in the age group up to two years old to 42.3 % in the group 20–35 years old.
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