Reaction Rules Research Articles

Expanding biochemical knowledge and illuminating metabolic dark matter with ATLASx

Metabolic “dark matter” describes currently unknown metabolic processes, which form a blind spot in our general understanding of metabolism and slow down the development of biosynthetic cell factories and naturally derived pharmaceuticals. Mapping the dark matter of metabolism remains an open challenge that can be addressed globally and systematically by existing computational solutions. In this work, we use 489 generalized enzymatic reaction rules to map both known and unknown metabolic processes around a biochemical database of 1.5 million biological compounds. We predict over 5 million reactions and integrate nearly 2 million naturally and synthetically-derived compounds into the global network of biochemical knowledge, named ATLASx. ATLASx is available to researchers as a powerful online platform that supports the prediction and analysis of biochemical pathways and evaluates the biochemical vicinity of molecule classes (https://lcsb-databases.epfl.ch/Atlas2).

Reaction network and molecular distribution of sulfides in gasoline and diesel of FCC process

In order to guide the accurate control of the sulfides in gasoline and diesel of Fluid Catalytic Cracking (FCC) process, a molecular-level model was established based on the Structure Oriented Lumping (SOL) method. According to the molecular composition characteristics of FCC feed oil, a molecular composition matrix containing 4,148 structural vectors was constructed with 24 structural increments. Using MATLAB software, the SOL reaction rules were compiled and a complex reaction network containing of about 110,000 reactions was established. According to the classification rules, the sulfides in gasoline and diesel represented by 32 and 136 structural vectors were divided into mercaptans, thioethers, monocyclic thiophenes, benzothiophenes and dibenzothiophenes, respectively. The conversion law of sulfides in gasoline and diesel was investigated by tracking their generation paths and reaction paths in the reaction network. The effects of the operation conditions on the sulfide content in gasoline and diesel were calculated quantitatively.

DFT Mechanistic Insights into Aldehyde Deformylations with Biomimetic Metal-Dioxygen Complexes: Distinct Mechanisms and Reaction Rules.

Aldehyde deformylations occurring in organisms are catalyzed by metalloenzymes through metal–dioxygen active cores, attracting great interest to study small-molecule metal–dioxygen complexes for understanding relevant biological processes and developing biomimetic catalysts for aerobic transformations. As the known deformylation mechanisms, including nucleophilic attack, aldehyde α-H-atom abstraction, and aldehyde hydrogen atom abstraction, undergo outer-sphere pathways, we herein report a distinct inner-sphere mechanism based on density functional theory (DFT) mechanistic studies of aldehyde deformylations with a copper (II)–superoxo complex. The inner-sphere mechanism proceeds via a sequence mainly including aldehyde end-on coordination, homolytic aldehyde C–C bond cleavage, and dioxygen O–O bond cleavage, among which the C–C bond cleavage is the rate-determining step with a barrier substantially lower than those of outer-sphere pathways. The aldehyde C–C bond cleavage, enabled through the activation of the dioxygen ligand radical in a second-order nucleophilic substitution (SN2)-like fashion, leads to an alkyl radical and facilitates the subsequent dioxygen O–O bond cleavage. Furthermore, we deduced the rules for the reactions of metal–dioxygen complexes with aldehydes and nitriles via the inner-sphere mechanism. Expectedly, our proposed inner-sphere mechanisms and the reaction rules offer another perspective to understand relevant biological processes involving metal–dioxygen cores and to discover metal–dioxygen catalysts for aerobic transformations.

Vacuum residue coking process simulation using molecular-level kinetic model coupled with vapor-liquid phase separation

In this work, a molecular-level kinetic model was built to simulate the vacuum residue (VR) coking process in a semi-batch laboratory-scale reaction kettle. A series of reaction rules for heavy oil coking were summarized and formulated based on the free radical reaction mechanism. Then, a large-scale molecular-level reaction network was automatically generated by applying the reaction rules on the vacuum residue molecules. In order to accurately describe the physical change of each molecule in the reactor, we coupled the molecular-level kinetic model with a vapor–liquid phase separation model. The vapor–liquid phase separation model adopted the Peng-Robinson equation of state to calculate vapor–liquid equilibrium. A separation efficiency coefficient was introduced to represent the mass transfer during the phase separation. We used six sets of experimental data under various reaction conditions to regress the model parameters. The tuned model showed that there was an excellent agreement between the calculated values and experimental data. Moreover, we investigated the effect of reaction temperature and reaction time on the product yields. After a comprehensive evaluation of the reaction temperature and reaction time, the optimal reaction condition for the vacuum residue coking was also obtained.

Computer generation of detailed reaction networks in hydrocracking of Fischer-Tropsch wax

Fischer-Tropsch synthesis (FTS) wax is a mixture of linear hydrocarbons with carbon number from C7 to C70+. Converting FTS wax into high-quality diesel (no sulfur and nitrogen contents) by hydrocracking technology is attractive in economy and practicability. Kinetic study of the hydrocracking of FTS wax in elementary step level is very challenging because of the huge amounts of reactions and species involved. Generation of reaction networks for hydrocracking of FTS wax in which the chain length goes up to C70 is described on the basis of Boolean adjacency matrixes. Each of the species (including paraffins, olefins and carbenium ions) involved in the elementary steps is represented digitally by using a ( N + 3) × N matrix, in which a group of standardized numbering rules are designed to guarantee the unique identity of the species. Subsequently, the elementary steps are expressed by computer-aided matrix transformations in terms of proposed reaction rules. Dynamic memory allocation is used in species storage and a characteristic vector with nine elements is designed to store the key information of a ( N + 3) × N matrix, which obviously reduces computer memory consumption and improves computing efficiency. The detailed reaction networks of FTS wax hydrocracking can be generated smoothly and accurately by the current method. The work is the basis of advanced elementary-step-level kinetic modeling.

Comparison of exact and approximate approaches to UAVs mission contingency planning in dynamic environments.

This paper presents a novel approach to the joint proactive and reactive planning of deliveries by an unmanned aerial vehicle (UAV) fleet. We develop a receding horizon-based approach to contingency planning for the UAV fleet's mission. We considered the delivery of goods to spatially dispersed customers, over an assumed time horizon. In order to take into account forecasted weather changes that affect the energy consumption of UAVs and limit their range, we propose a set of reaction rules that can be encountered during delivery in a highly dynamic and unpredictable environment. These rules are used in the course of designing the contingency plans related to the need to implement an emergency return of the UAV to the base or handling of ad hoc ordered deliveries. Due to the nonlinearity of the environment's characteristics, both constraint programming and genetic algorithm paradigms have been implemented. Because of the NP-difficult nature of the considered planning problem, conditions have been developed that allow for the acceleration of calculations. The multiple computer experiments carried out allow for comparison representatives of the approximate and exact methods so as to judge which approach is faster for which size of the selected instance of the UAV mission planning problem.

A unique monetary reaction rule: the case of Lebanon

A unique monetary reaction rule: the case of Lebanon

Chemical-damage MINE: A database of curated and predicted spontaneous metabolic reactions

Spontaneous reactions between metabolites are often neglected in favor of emphasizing enzyme-catalyzed chemistry because spontaneous reaction rates are assumed to be insignificant under physiological conditions. However, synthetic biology and engineering efforts can raise natural metabolites' levels or introduce unnatural ones, so that previously innocuous or nonexistent spontaneous reactions become an issue. Problems arise when spontaneous reaction rates exceed the capacity of a platform organism to dispose of toxic or chemically active reaction products. While various reliable sources list competing or toxic enzymatic pathways’ side-reactions, no corresponding compilation of spontaneous side-reactions exists, nor is it possible to predict their occurrence. We addressed this deficiency by creating the Chemical Damage (CD)-MINE resource. First, we used literature data to construct a comprehensive database of metabolite reactions that occur spontaneously in physiological conditions. We then leveraged this data to construct 148 reaction rules describing the known spontaneous chemistry in a substrate-generic way. We applied these rules to all compounds in the ModelSEED database, predicting 180,891 spontaneous reactions. The resulting (CD)-MINE is available at https://minedatabase.mcs.anl.gov/cdmine/#/home and through developer tools. We also demonstrate how damage-prone intermediates and end products are widely distributed among metabolic pathways, and how predicting spontaneous chemical damage helps rationalize toxicity and carbon loss using examples from published pathways to commercial products. We explain how analyzing damage-prone areas in metabolism helps design effective engineering strategies. Finally, we use the CD-MINE toolset to predict the formation of the novel damage product N-carbamoyl proline, and present mass spectrometric evidence for its presence in Escherichia coli.

Correspondence between meridian circuit and somato-segment arrangement

The "meridian theory" is the summary and sublimation of long-term medical practice of the Chinese ancient sages. Via reduction and reconstruction about the theoretical system, it has been put forward a doctrine of "binary structure" about the meridian and acupoints which, at the limbs, present a longitudinal arrangement, and those at the head-face and trunk present a horizontal distribution, being closely related to the "dematome" of the body. Centered on the ontogenesis of the embryonic "somite", a closely connected "structure-function unit" complex is formed with the development of the dermis-muscle-ogran-nerve within the homo-segment. This form constitutes the basic characteristics of pathological reaction rules and therapeutic effects of meridian acupoints.

EHreact: Extended Hasse Diagrams for the Extraction and Scoring of Enzymatic Reaction Templates.

Data-driven computer-aided synthesis planning utilizing organic or biocatalyzed reactions from large databases has gained increasing interest in the last decade, sparking the development of numerous tools to extract, apply, and score general reaction templates. The generation of reaction rules for enzymatic reactions is especially challenging since substrate promiscuity varies between enzymes, causing the optimal levels of rule specificity and optimal number of included atoms to differ between enzymes. This complicates an automated extraction from databases and has promoted the creation of manually curated reaction rule sets. Here, we present EHreact, a purely data-driven open-source software tool, to extract and score reaction rules from sets of reactions known to be catalyzed by an enzyme at appropriate levels of specificity without expert knowledge. EHreact extracts and groups reaction rules into tree-like structures, Hasse diagrams, based on common substructures in the imaginary transition structures. Each diagram can be utilized to output a single or a set of reaction rules, as well as calculate the probability of a new substrate to be processed by the given enzyme by inferring information about the reactive site of the enzyme from the known reactions and their grouping in the template tree. EHreact heuristically predicts the activity of a given enzyme on a new substrate, outperforming current approaches in accuracy and functionality.

A multi-layered bigraphical modelling approach for context-aware systems

There exist several approaches proposed for building Context-Aware Systems (CAS). However, due to the continually changing environment, the large number of interrelated components, complexity and diversity of application domains make the modelling of context-aware systems a particularly challenging task. To address the increasing complexity of the modelling: i) It is critical to take into account the importance of the environment (operational context); and ii) rely on software engineering concepts such as abstraction and modularity in order to reduce the level of complexity. Also, a context-aware system may require intelligence and autonomy. These naturally lead us to apply intelligent agent-based engineering. This work introduces a formal layered design approach that combines intelligent control of multi-agent systems and bigraph's rigor to model context-aware systems. Bigraphical reactive systems are particularly compelling for their capacity to specify, simultaneously, the physical and logical distribution of system components and their interconnections using two distinct structures; that is: place graph and link graph. While the behaviour and dynamic evolution are expressed using defined reaction rules, and as a last step, the bigraph specifications are coded in the Maude language to allow their execution and the verification of their validity.

Precise Introduction of the -CHnX3-n (X = F, Cl, Br, I) Moiety to Target Molecules by a Radical Strategy: A Theoretical and Experimental Study.

Addition of halomethyl radicals to form bioactive molecules has recently become an efficient strategy. The reaction has a bottleneck, however, which is the effective and selective generation of the proper halomethyl •CHnX3-n radical by combining CHnX4-n with a carbon radical. Understanding the reactivity and selectivity of carbon radicals in the hydrogen atom transfer (HAT) and halogen atom transfer (XAT) reactions of CHnX4-n is key to the development of such an attractive method. With the help of the emerging data-driven strategy, DFT calculations were used to explore various correlations. For selectivity, the relative energy barriers between HAT and XAT reactions (ΔG⧧H - ΔG⧧X) correlate reasonably well with the three parameters ΔGH, ΔGX, and IP, and the correlation studies reveal that the calculated IPinver and the experimental ΔBDE can be used to conveniently predict the selectivity. Predicted selectivities are consistent with experimental determinations. This work not only provides a possibility for selecting carbon radicals with the known or easily obtained physicochemical data but also demonstrates that the informatic workflow such as generating data and identifying correlations has potential applications in mining reaction rules.

Reaction Mechanisms of Ta-Substituted Cubic Li7La3Zr2O12 with Solvents During Storage.

The reactivity of garnet solid electrolytes toward humid air hinders their practical application despite their attractive, superior properties such as high Li+ conductivity and wide electrochemical window. Sealing garnets with organic solvents can not only prevent them from reacting with humid air but also render them compatible with other processing technologies. Therefore, the chemical and structural stability of garnets in organic solvents must be studied. In this study, we selected several commonly used organic solvents with different representative functional groups to investigate their stability with garnets and reaction mechanisms. The experiments and theoretical calculations revealed that all of the solvents reacted with garnets through Li-H exchange, and solvent acidity determined the reaction strength. Furthermore, the solvent acidity was closely correlated to the functional groups connected to H atoms, which can affect charge distribution. Solvents or the tautomer of the solvents with hydroxyl groups such as alcohol, acetone, and N-methyl pyrrolidone, which are relatively more acidic, can lead to a violent reaction with changes in the lattice parameters of garnets. Ether compounds and saturated aliphatic hydrocarbons with relatively low acidity are highly stable against garnets. The proposed reaction mechanisms and rules may help in selecting appropriate solvents for different applications of garnets.

Learning Chemistry of Complex Reaction Systems via a Python First-Principles Reaction Rule Stencil (pReSt) Generator.

Complex reaction networks can be generated with automated network generators from initial reactants and reaction rules. Reaction rule specification is central to network generation. These reaction rules are, at present, user-defined based on (intuitive) expert knowledge of chemistry and are often transferred from gas-phase to surface processes. The catalyst active site geometry is usually left out but is often responsible for selectivity. We propose a first-principles-based reaction mechanism generation framework using density functional theory (DFT) data of published reaction mechanisms. The framework "learns the chemistry" from published mechanisms. It can generate reaction networks not studied before, "flag" reactions not seen before for further DFT convergence tests, and easily reconcile differences between catalysts and reactants that may introduce new pathways never seen before. As such, it can be a diagnostic tool for data (mechanism) quality assessment and novel pathway discovery to new molecules. A software, the Python Reaction Stencil (pReSt), was developed for this purpose to wrap around automatic mechanism generation software. Multiple catalytic chemistries are considered to show the efficacy of the proposed framework.

Fischer-Tropsch wax catalytic cracking for the production of low olefin and high octane number gasoline: Experiment and molecular level kinetic modeling study

A molecular level kinetic model of Fischer–Tropsch wax catalytic cracking based on the structural unit and bond-electron matrix framework was developed. A molecular compositional model was built according to the detail molecular characterization data, containing 225 representative molecules. The reaction law was studied and then transformed to 17 reaction rules based on experimental data under different reaction conditions. All molecules traversed reaction rules, and a reaction network, including 700 molecules and 2029 reactions, was formed. The model parameters were reduced based on linear free energy relationship and tuned by experimental data. The predicted values of the model were in good agreement with the experimental data, with a maximum absolute error of 2.89 wt% and a minimum absolute error of 0.02 wt%. The model predicted that gasoline olefin content will achieve less than 25 wt% and RON > 90 under the reaction conditions of 510 °C, CTO 12 g/g and WHSV 6 h−1. The modelling also demonstrated that the feedstock was consumed rapidly, and multiple reactions could occur immediately. Thus, secondary reactions play an important role in the production of low olefin and high octane number gasoline.

Assessment of the impact of hydrolysis on bound sulfonamide residue determination in honey using stable isotope dilution ultrahigh performance liquid chromatography tandem mass spectrometry

In this study, an analytical method based on isotope dilution-liquid chromatography tandem mass spectrometry (ID-LC-MS/MS) was developed as a candidate reference method for the determination of sulfonamides (SAs) in honey. To guarantee the accuracy and authenticity, the impact of hydrolysis on bound SA residues was first investigated by enabling (i) identification of sugar-bound SAs, (ii) clarifying the binding reaction rule between the SAs and sugar, (iii) detection of free SAs and sugar-bound SAs, and (iv) preparation of SA-contaminated honey. Thus, the efficiency of different hydrolysis conditions was assessed by comparing the bound SA content before and after hydrolysis. In addition, optimization of the sample pretreatment procedures and LC conditions to minimize matrix effects by separation from significant matrix interferences was also performed. Satisfactory results in terms of hydrolysis efficiency (approximately 88.3%–99.2%), extraction efficiency (84.2%–105.3%), recovery (95.9%–103.1%), and limit of quantification (0.6–1.5 μg·kg−1) were obtained.

Reactive UAV Fleet’s Mission Planning in Highly Dynamic and Unpredictable Environments

Unmanned aerial vehicles (UAVs) create an interesting alternative for establishing more sustainable urban freight deliveries. The substitution of traditional trucks in the last-mile distribution by a UAV fleet can contribute to urban sustainability by reducing air pollution and increasing urban freight efficiency. This paper presents a novel approach to the joint proactive and reactive planning of deliveries by a UAV fleet. We develop a receding horizon-based approach to reactive, online planning for the UAV fleet’s mission. We considered the delivery of goods to spatially dispersed customers over an assumed time horizon. Forecasted weather changes affect the energy consumption of UAVs and limit their range. Therefore, consideration should be given to plans for follow-up tasks, previously unmet needs, and predictions of disturbances over a moving time horizon. We propose a set of reaction rules that can be encountered during delivery in a highly dynamic and unpredictable environment. We implement a constraint programming paradigm, which is well suited to cope with the nonlinearity of the system’s characteristics. The proposed approach to online reactive UAV routing is evaluated in several instances. The computational experiments have shown that the developed model is capable of providing feasible plans for a UAV fleet’s mission that are robust to changes in weather and customer’s orders.

Computationally Prospecting Potential Pathways from Lignin Monomers and Dimers toward Aromatic Compounds.

The heterogeneity of the aromatic products originating from lignin catalytic depolymerization remains one of the major challenges associated with lignin valorization. Microbes have evolved catabolic pathways that can funnel heterogeneous intermediates to a few central aromatic products. These aromatic compounds can subsequently undergo intra- or extradiol ring opening to produce value-added chemicals. However, such funneling pathways are only partially characterized for a few organisms such as Sphingobium sp. SYK-6 and Pseudomonas putida KT2440. Herein, we apply the de novo pathway design tool (novoStoic) to computationally prospect possible ways of funneling lignin-derived mono- and biaryls. novoStoic employs reaction rules between molecular moieties to hypothesize de novo conversions by flagging known enzymes that carry out the same biotransformation on the most similar substrate. Both reaction rules and known reactions are then deployed by novoStoic to identify a mass-balanced biochemical network that converts a source to a target metabolite while minimizing the number of de novo steps. We demonstrate the application of novoStoic for (i) designing alternative pathways of funneling S, G, and H lignin monomers, and (ii) exploring cleavage pathways of β-1 and β-β dimers. By exploring the uncharted chemical space afforded by enzyme promiscuity, novoStoic can help predict previously unknown native pathways leveraging enzyme promiscuity and propose new carbon/energy efficient lignin funneling pathways with few heterologous enzymes.

Molecular-level heavy petroleum hydrotreating modeling and comparison with high-resolution mass spectrometry

The establishment of a molecular-level process model is critical for heavy petroleum hydrotreating optimization. This paper focuses on constructing a heavy petroleum compositional model and hydrotreating process model with a more accurate molecular detail. Besides the bulk property data, the detail molecular characterization data from high-resolution mass spectrometry was used to guide the compositional and kinetic model development. Under the framework of structural unit and bond-electron matrix (SU-BEM), more than 12,000 representative molecules were constructed to form a heavy petroleum molecular structure library. The probability density functions (PDFs) were combined to constrain the molecular composition of the heavy petroleum. The optimal molecular composition was obtained by optimizing the PDFs parameters. 18 reaction rules were formulated to express the heavy petroleum molecular conversion pathways. The reaction network was generated automatically and transformed mathematically into a micro-kinetic model. The total numbers of involved reactions and molecules were ~ 25,000 and ~ 17,000, respectively. The model parameters were globally optimized according to experimental data. The model results show good agreement with the bulk property data. Moreover, the predicted molecular distribution and molecular conversion regulations are consistent with the high-resolution mass spectrometry data.

Revealing the pyrolysis behavior of 5-5′ biphenyl-type lignin fragment. Part I: A mechanistic study on fragmentation via experiments and theoretical calculation

Biphenyl structure plays an important role in the thermal degradation of woody lignin due to its non-negligible proportion, and its high binding energy of Caryl-Caryl bond leads the lignin fragments not easy to be break into small-molecule products. The in-depth study on the pyrolysis mechanism of biphenyl-containing structures is conducive to solve the shortcoming and providing technical support for lignin depolymerization. In this works, we report a mechanistic study on the pyrolysis of biphenyl structure. The pyrolytic pathways had been proposed based on the thermochemical characteristics, the functional groups evolutions and the products distributions during the pyrolysis process. DFT calculation were following carried out to explain the reaction rules at the microscopic (molecular) level. The results showed that both endothermic and exothermic procedures were coexistent during biphenyl dimer pyrolysis, along with the releasing of small molecular such as CH4, CO, H2O, etc.; there are two mutual-promotive and competitive fragmented pathways during pyrolysis, i.e. 5-5′ cleavage and substituent breaking. The demethylation of the methoxy group is the most prior initiation, followed by the dehydrogenation of edge groups, instead of the inaccessible CAr-Cx bonds homolysis. The 5-5′ cleavage pathway can partially be realized with the assistance of the hydrogen radical, which need only overcoming a 7.10 kcal/mol energy barrier. On the contrary, the fragmentation mostly involves the substituent breaking, and the biphenyl products formation through a series of radical-mediated reactions.