An automated method for graph-based chemical space exploration and transition state finding

Algorithms that automatically explore the chemical space have been limited to chemical systems with a low number of atoms due to expensive involved quantum calculations and the large amount of possible reaction pathways. The method described here presents a novel solution to the problem of chemical exploration by generating reaction networks with heuristics based on chemical theory. First, a second version of the reaction network is determined through molecular graph transformations acting upon functional groups of the reacting. Only transformations that break two chemical bonds and form two new ones are considered, leading to a significant performance enhancement compared to previously presented algorithm. Second, energy barriers for this reaction network are estimated through quantum chemical calculations by a growing string method, which can also identify non-octet species missed during the previous step and further define the reaction network. The proposed algorithm has been successfully applied to five different chemical reactions, in all cases identifying the most important reaction pathways.     

Ensembling machine learning models to boost molecular affinity prediction

This study unites six popular machine learning approaches to enhance the prediction of a molecular binding affinity between receptors (large protein molecules) and ligands (small organic molecules). Here we examine a scheme where affinity of ligands is predicted against a single receptor – human thrombin, thus, the models consider ligand features only. However, the suggested approach can be repurposed for other receptors. The methods include Support Vector Machine, Random Forest, CatBoost, feed-forward neural network, graph neural network, and Bidirectional Encoder Representations from Transformers. The first five methods use input features based on physico-chemical properties of molecules, while the last one is based on textual molecular representations. All approaches do not rely on atomic spatial coordinates, avoiding a potential bias from known structures, and are capable of generalizing for compounds with unknown conformations. Within each of the methods, we have trained two models that solve classification and regression tasks. Then, all models are grouped into a pipeline of two subsequent ensembles. The first ensemble aggregates six classification models which vote whether a ligand binds to a receptor or not. If a ligand is classified as active (i.e., binds), the second ensemble predicts its binding affinity in terms of the inhibition constant K_i.     

Identifiability of chemical reaction networks

We consider the dynamics of chemical reaction networks under the assumption of mass-action kinetics. We show that there exist reaction networks for which the reaction rate constants are not uniquely identifiable, even if we are given complete information on the dynamics of concentrations for all chemical species of . Also, we show that there exist reaction networks such that their dynamics are identical under appropriate choices of reaction rate constants, and present theorems that characterize the properties of , , that make this possible. We use these facts to show how we can determine dynamical properties of some chemical networks by analyzing other chemical networks.     

Quantum chemical reaction networks,reaction graphs and the structure of potential energy hypersurfaces

Global properties of the Born-Oppenheimer energy expectation value functional, defined over the nuclear configuration space R, are analyzed. Quantum chemical reaction graphs and reaction networks are defined in terms of intersection graphs of connected sets of nuclear geometries, representing various chemical structures. The set of all possible reaction mechanisms on the given energy hypersurface and the associated activation energy conditions are analyzed using reachability matrices defined over digraphs D ^s() and D ^s(, E).     

茚三酮对B-Z振荡反应的影响

研究了茚三酮对B Z振荡体系的影响,考察了振幅和周期的改变值与茚三酮浓度的关系。结果表明,在6.9×10-7～4.2×10-2mol/L范围内,第一振幅改变值与茚三酮浓度有良好的线性关系,相关系数为0.9977。依据FKN模型,对此反应机理进行了初步探讨。     

Automatic knowledge extraction from chemical structures: the case of mutagenicity prediction

This work proposes a new structure–activity relationship (SAR) approach to mine molecular fragments that act as structural alerts for biological activity. The entire process is designed to fit with human reasoning, not only to make the predictions more reliable but also to permit clear control by the user in order to meet customized requirements. This approach has been tested on the mutagenicity endpoint, showing marked prediction skills and, more interestingly, bringing to the surface much of the knowledge already collected in the literature as well as new evidence.     

On the study of nonlinear dynamics of complex chemical reaction systems

When driven far from equilibrium,nonlinear chemical reactions often show a variety of self-organization behavior,including chemical oscillations,waves,chaos and patterns[1].Recently,the study of such nonlinear phenomena in‘complex’systems,such as the li…     

超临界CO_2在化学反应中的应用进展

本文详细地综述了最近几年来有关超临界CO2流体中的化学反应的研究成果，展望了超临界CO2化学反应的开发应用前景，试图让这一崭新的研究领域受到更加广泛的关注。     

Graph Neural Networks with Multiple Feature Extraction Paths for Chemical Property Estimation

Feature extraction is essential for chemical property estimation of molecules using machine learning. Recently, graph neural networks have attracted attention for feature extraction from molecules. However, existing methods focus only on specific structural information, such as node relationship. In this paper, we propose a novel graph convolutional neural network that performs feature extraction with simultaneously considering multiple structures. Specifically, we propose feature extraction paths specialized in node, edge, and three-dimensional structures. Moreover, we propose an attention mechanism to aggregate the features extracted by the paths. The attention aggregation enables us to select useful features dynamically. The experimental results showed that the proposed method outperformed previous methods.     

致癌性胺离子反应过程中电荷和化学位移的计算

应用原子-键电负性均衡方法中的σπ模型(ABEEMσπ)计算了由致癌性胺离子所参与的反应过程中的电荷分布,所计算出的电荷分布可以和从头算很好的相关联,并且所需要的时间也大大的缩短;同时应用从头计算程序计算致癌性胺离子反应过程中的NMR化学位移.结果表明,在反应过程中电荷的变化和NMR化学位移的变化有很好的对应关系.     

A dimensionless reaction coordinate for quantifying the lateness of transition states

The Hammond‐Leffler postulate asserts that transition states of exothermic reactions are reactant‐like (early), whereas transition states of endothermic reactions are product‐like (late). Related postulates have been proposed to describe the sensitivity of activation barriers for reactions occurring on catalytic surfaces to the catalyst structure. To evaluate the validity of these postulates for different chemical reactions, a general method for classifying transition states as either early or late is needed. One can envision a dimensionless reaction coordinate that changes continuously and monotonically from 0 to 1 along a minimum energy reaction pathway. The value of the dimensionless reaction coordinate for the transition state (W_TS) classifies transition states as (a) early when W_TS < 0.5, (b) late when W_TS > 0.5, and (c) equidistant between reactants and products when W_TS = 0.5. In this article, we derive such a dimensionless reaction coordinate and illustrate its usefulness for several different chemical reactions. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010     

Metric properties of the functions of distances between molecular graphs

The metric properties of several functions of distances between the molecular (marked) graphs, depending on the size of the largest common subgraphs, are discussed. Recommendations are given on how to use these functions in investigations of samples of chemical compounds.     

Fluctuation theorem for entropy production in a chemical reaction channel

Fluctuation theorem for entropy production in a mesoscopic chemical reaction network is discussed. When the system size is sufficiently large, it is found that, by defining a kind of coarse-grained dissipation function, the entropy production in a reversible reaction channel can be approximately described by a type of detailed fluctuation theorem. Such a fluctuation relation has been successfully tested by direct simulations in a linear reaction model consisting of two reversible channels and in an oscillat...     

化学反应过渡态的结构和动力学

化学反应过渡态决定了包括反应速率和微观反应动力学在内的化学反应的基本特性,而无论是从理论还是实验上研究和观测化学反应过渡态都是极具挑战性的课题.近年来,我国科学家们利用交叉分子束-里德堡氢原子飞行时间谱仪,结合高精度的量子动力学计算,对H＋H2和F＋H2这两个教科书式的典型反应体系进行了全量子态分辨的反应动力学研究,从中得出了关于这两个反应体系的过渡态的结构和动力学性质的结论性的研究成果.     

On the chemical reaction of matter with antimatter.

A chemical reaction between the building block antiatomic nucleus, the antiproton (p or H- in chemical notation), and the hydrogen molecular ion (H2+) has been observed by the ATHENA collaboration at CERN. The charged pair interact via the long-range Coulomb force in the environment of a Penning trap which is purpose-built to observe antiproton interactions. The net result of the very low energy collision of the pair is the creation of an antiproton-proton bound state, known as protonium (Pn), together with the liberation of a hydrogen atom. The Pn is formed in a highly excited, metastable, state with a lifetime against annihilation of around 1 micros. Effects are observed related to the temperature of the H2+ prior to the interaction, and this is discussed herein.     

A study of heat and mass transfer of Non-Newtonian fluid with surface chemical reaction

Considering the significance of non-Newtonian fluid usage in manufacturing such as molten plastics, polymeric materials, pulps, and so on, significant efforts have been made to investigate the phenomenon of non-Newtonian fluids. In this article the influences of heat and mass transfer on non-Newtonian Walter's B fluid flow over uppermost catalytic surface of a paraboloid is encountered. An elasticity of the fluid layer is considered in the freestream together with heat source/sink and has the tendency to cause heat flow in the fluid saturated domain. The flow problem of two-dimensional Walter's B fluid is represented using Law of conservation of mass, momentum, heat, and concentration along with thermal and solutal chemical reactive boundary conditions. The governing equations are non-linear partial differential equation and are non-dimensionalized by employing stream function and similarity transformation. The final dimensionless equations yielded are coupled non-linear ordinary differential equations. Furthermore, shooting technique along with RK-4th order method is used to get the numerical results. Graphs and tables are modeled by using MATLAB software to check the effects of Walter's B parameter, Chemical reaction parameter and Thickness parameter on temperature, velocity, and concentration profiles. Tabular analysis shows the results of some physical parameters like skin friction coefficient, Nusselt number and Sherwood number due to the variation of Walter's B parameter, thickness parameter and chemical reactive parameter.     

Quantum chemical study of the reaction of trichloroethylene with O(3P)

The adiabatic mechanism of the reaction of trichloroethylene with O(³P), exploring the various O-atom addition and H-atom abstraction channels, is theoretically studied at the MP2/6-311++G(2d, 2p), MP2/aug-cc-pVTZ, CCSD/6-31G(d), G3, and CBS-QB3 levels of theory. From a kinetic point of view, the addition to the less substituted carbon atom of the double bond is more favorable than the addition to the more substituted carbon. Such O-atom addition reactions are favored over the one possible hydrogen-abstraction reaction. Calculations of the present study showed that five products are obtained: HCCl + C(O)Cl₂ (P1), Cl + ClC(O)CHCl (P2), H + ClC(O)CCl₂ (P3), Cl + HC(O)CCl₂ (P4), and CH(O)Cl + CCl₂ (P5). The products P2 and P4 are found to be the most favored ones. The kinetic calculations of rate constant in the range of 285–395 K are performed at the CBS-QB3 level of theory and are in conformity with the experimental outcomes.     

On the centrality of vertices of molecular graphs

For acyclic systems the center of a graph has been known to be either a single vertex of two adjacent vertices, that is, an edge. It has not been quite clear how to extend the concept of graph center to polycyclic systems. Several approaches to the graph center of molecular graphs of polycyclic graphs have been proposed in the literature. In most cases alternative approaches, however, while being apparently equally plausible, gave the same results for many molecules, but occasionally they differ in their characterization of molecular center. In order to reduce the number of vertices that would qualify as forming the center of the graph, a hierarchy of rules have been considered in the search for graph centers. We reconsidered the problem of “the center of a graph” by using a novel concept of graph theory, the vertex “weights,” defined by counting the number of pairs of vertices at the same distance from the vertex considered. This approach gives often the same results for graph centers of acyclic graphs as the standard definition of graph center based on vertex eccentricities. However, in some cases when two nonequivalent vertices have been found as graph center, the novel approach can discriminate between the two. The same approach applies to cyclic graphs without additional rules to locate the vertex or vertices forming the center of polycyclic graphs, vertices referred to as central vertices of a graph. In addition, the novel vertex “weights,” in the case of acyclic, cyclic, and polycyclic graphs can be interpreted as vertex centralities, a measure for how close or distant vertices are from the center or central vertices of the graph. Besides illustrating the centralities of a number of smaller polycyclic graphs, we also report on several acyclic graphs showing the same centrality values of their vertices. © 2013 Wiley Periodicals, Inc.