Structure–reactivity modeling using mixture-based representation of chemical reactions

© 2017, Springer International Publishing AG. We describe a novel approach of reaction representation as a combination of two mixtures: a mixture of reactants and a mixture of products. In turn, each mixture can be encoded using an earlier reported approach involving simplex descriptors (SiRMS). The feature vector representing these two mixtures results from either concatenated product and reactant descriptors or the difference between descriptors of products and reactants. This reaction representation doesn’t need an explicit labeling of a reaction center. The rigorous “product-out” cross-validation (CV) strategy has been suggested. Unlike the naïve “reaction-out” CV approach based on a random selection of items, the proposed one provides with more realistic estimation of prediction accuracy for reactions resulting in novel products. The new methodology has been applied to model rate constants of E2 reactions. It has been demonstrated that the use of the fragment control domain applicability approach significantly increases prediction accuracy of the models. The models obtained with new “mixture” approach performed better than those required either explicit (Condensed Graph of Reaction) or implicit (reaction fingerprints) reaction center labeling

QSPR MODELING OF TAUTOMERIC EQUILIBRIA USING LOCAL DESCRIPTORS

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Structure–reactivity relationship in Diels–Alder reactions obtained using the condensed reaction graph approach

© 2017, Pleiades Publishing, Ltd. By the structural representation of a chemical reaction in the form of a condensed graph a model allowing the prediction of rate constants (logk) of Diels–Alder reactions performed in different solvents and at different temperatures is constructed for the first time. The model demonstrates good agreement between the predicted and experimental logk values: the mean squared error is less than 0.75 log units. Erroneous predictions correspond to reactions in which reagents contain rarely occurring structural fragments. The model is available for users at https://cimm.kpfu.ru/predictor/

Visualization and Analysis of Complex Reaction Data: The Case of Tautomeric Equilibria

© 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim Generative Topographic Mapping (GTM) approach was successfully used to visualize, analyze and model the equilibrium constants (KT) of tautomeric transformations as a function of both structure and experimental conditions. The modeling set contained 695 entries corresponding to 350 unique transformations of 10 tautomeric types, for which KT values were measured in different solvents and at different temperatures. Two types of GTM-based classification models were trained: first, a “structural” approach focused on separating tautomeric classes, irrespective of reaction conditions, then a “general” approach accounting for both structure and conditions. In both cases, the cross-validated Balanced Accuracy was close to 1 and the clusters, assembling equilibria of particular classes, were well separated in 2-dimentional GTM latent space. Data points corresponding to similar transformations measured under different experimental conditions, are well separated on the maps. Additionally, GTM-driven regression models were found to have their predictive performance dependent on different scenarios of the selection of local fragment descriptors involving special marked atoms (proton donors or acceptors). The application of local descriptors significantly improves the model performance in 5-fold cross-validation: RMSE=0.63 and 0.82 logKT units with and without local descriptors, respectively. This trend was as well observed for SVR calculations, performed for the comparison purposes

Использование электроприводов агрегатов кустовых насосных станций в качестве потребителей-регуляторов активной и реактивной энергии и мощности

The paper presents results of the experiments conducted at/on a number of pump units with synchronous electric engines which are used at group pump stations in the process of oil production. Purpose of the experiments is to determine actual possibilities of group pump station units while using them as regulating loads of active and reactive energy. The experimental results have made it possible to construct power and economic characteristics. Taking into account these characteristics a method of load distribution for each unit at specified total load is proposed in the paper.Представлены результаты экспериментов, проведенных на ряде насосных агрегатов с синхронными электродвигателями, применяемыми на кустовых насосных станциях (КНС) при нефтедобыче. Целью экспериментов являлось определение реальных возможностей агрегатов КНС при использовании их в качестве потребителей-регуляторов активной и реактивной энергии. По результатам экспериментов построены энергоэкономические характеристики агрегатов и с их учетом предложен метод распределения долей нагрузок по каждому агрегату при заданной суммарной нагрузке.

Usage of Electric Drives of Units at Group Pump Stations as Regulating Loads of Active and Reactive Energy and Power

The paper presents results of the experiments conducted at/on a number of pump units with synchronous electric engines which are used at group pump stations in the process of oil production. Purpose of the experiments is to determine actual possibilities of group pump station units while using them as regulating loads of active and reactive energy. The experimental results have made it possible to construct power and economic characteristics. Taking into account these characteristics a method of load distribution for each unit at specified total load is proposed in the paper

Sydnone-alkyne cycloaddition: Which factors are responsible for reaction rate ?

© 2019 Elsevier B.V. In this work we report extensive DFT study of sydnone-alkyne cyclization which included investigation of the reaction mechanism, analysis of different factors affecting sydnone and alkyne reactivity as well as attempt to reproduce quantitatively experimental activation free energy. The calculations were performed for a set of 18 sydnone-alkyne reactions with a help of a semi-automatized workflow involving reagent preparation and generation of starting structures for a plausible transition state. Reconstructed reaction path supported two-step mechanism: cycloaddition followed by retro-Diels-Alder reaction. Since the latter had a tiny barrier, the cycloaddition step was predicted to be the rate-limiting. For the ensemble of reactions, calculations reproduce activation free energies extracted from experimental reaction rates (k) with the accuracy of 2 kcal/mol. Accounting for solvation effects didn't change the overall trend of activation free energies as a function of substituents. A series of statistical model linking logk and sydnones structure was built using Support Vector Regression and Multiple Linear Regression machine-learning methods coupled with different types of molecular descriptors; none of them demonstrated a good performance at cross-validation stage. Detailed analysis of different factors affecting reaction rate variation as a function of substituents revealed particular role of the charge on C3 atom in the sydnone moiety as well as of the size of the substituent at C3

Sydnone-alkyne cycloaddition: Which factors are responsible for reaction rate ?

© 2019 Elsevier B.V. In this work we report extensive DFT study of sydnone-alkyne cyclization which included investigation of the reaction mechanism, analysis of different factors affecting sydnone and alkyne reactivity as well as attempt to reproduce quantitatively experimental activation free energy. The calculations were performed for a set of 18 sydnone-alkyne reactions with a help of a semi-automatized workflow involving reagent preparation and generation of starting structures for a plausible transition state. Reconstructed reaction path supported two-step mechanism: cycloaddition followed by retro-Diels-Alder reaction. Since the latter had a tiny barrier, the cycloaddition step was predicted to be the rate-limiting. For the ensemble of reactions, calculations reproduce activation free energies extracted from experimental reaction rates (k) with the accuracy of 2 kcal/mol. Accounting for solvation effects didn't change the overall trend of activation free energies as a function of substituents. A series of statistical model linking logk and sydnones structure was built using Support Vector Regression and Multiple Linear Regression machine-learning methods coupled with different types of molecular descriptors; none of them demonstrated a good performance at cross-validation stage. Detailed analysis of different factors affecting reaction rate variation as a function of substituents revealed particular role of the charge on C3 atom in the sydnone moiety as well as of the size of the substituent at C3

Structure–reactivity modeling using mixture-based representation of chemical reactions

© 2017, Springer International Publishing AG. We describe a novel approach of reaction representation as a combination of two mixtures: a mixture of reactants and a mixture of products. In turn, each mixture can be encoded using an earlier reported approach involving simplex descriptors (SiRMS). The feature vector representing these two mixtures results from either concatenated product and reactant descriptors or the difference between descriptors of products and reactants. This reaction representation doesn’t need an explicit labeling of a reaction center. The rigorous “product-out” cross-validation (CV) strategy has been suggested. Unlike the naïve “reaction-out” CV approach based on a random selection of items, the proposed one provides with more realistic estimation of prediction accuracy for reactions resulting in novel products. The new methodology has been applied to model rate constants of E2 reactions. It has been demonstrated that the use of the fragment control domain applicability approach significantly increases prediction accuracy of the models. The models obtained with new “mixture” approach performed better than those required either explicit (Condensed Graph of Reaction) or implicit (reaction fingerprints) reaction center labeling