Data Formats for Elementary Gas‐Phase Kinetics: Part 2. Unique Representations of Reactions

A method of extending the IUPAC International Chemical Identifier (InChI) to describe and identify elementary reactions in a standard computer‐readable notation is developed. Denoted InChI‐ER, the method is based on the existing InChI formalism, with certain refinements for the better identification of molecular entities as proposed in Part 1 published previously in this journal. Using this base notation, an identifier for elementary reactions on a molecular level is created by adding additional layers in a conceptually similar and extensible manner. Two of the layers describe the atoms involved in the transition state and the connectivity changes that occur during the reaction. Additional layers classify the reactions on the basis of the connectivity changes, providing chemical information useful in organizing and searching kinetic data sets found in databases or used in detailed kinetic modeling. Important aspects of the method are that the proposed layers are optional, that they do not interfere with existing InChI specifications, and that they retain extensibility should further refinements be desired in the future.     

Data Formats for Elementary Gas Phase Kinetics,Part 1: Unique Representations of Species at the Molecular Level

Standardized electronic formats for data are needed to efficiently and transparently communicate the results of scientific studies. A format for the unique identification of chemical species is a requirement in the field of chemistry, and the IUPAC International Chemical Identifier (InChI) has been widely adopted for this purpose. The InChI identifier has proved to be very useful. The InChI identifier, however, is currently insufficient to uniquely specify some types of molecular entities at a detailed molecular level needed to fully characterize their chemical nature, to differentiate between chemically distinct conformers, to uniquely identify structures used in quantum chemical calculations, and to completely describe elementary chemical reactions. To address this limitation, we propose an augmented form of InChI, denoted as InChI–ER, which contains additional optional layers that allow the unique and unambiguous identification of molecules at a detailed molecular level. The new layers proposed herein are optional extensions of the existing InChI formalism and, like all other InChI layers, would not interfere with InChI identifiers currently in use. The focus of the present work is the better specification of required molecular entities such as rotational conformations, ring conformations, and electronic states. In companion articles, we propose additional reaction layers using an extended InChI format that will enable the unique identification of elementary chemical reactions, including specification of associated transition states, specification of the changes in bonds that occur during reaction, and classification of reaction types.     

Two-dimensional wavelet analysis based classification of gas chromatogram differential mobility spectrometry signals

This study introduces two-dimensional (2-D) wavelet analysis to the classification of gas chromatogram differential mobility spectrometry (GC/DMS) data which are composed of retention time, compensation voltage, and corresponding intensities. One reported method to process such large data sets is to convert 2-D signals to 1-D signals by summing intensities either across retention time or compensation voltage, but it can lose important signal information in one data dimension. A 2-D wavelet analysis approach keeps the 2-D structure of original signals, while significantly reducing data size. We applied this feature extraction method to 2-D GC/DMS signals measured from control and disordered fruit and then employed two typical classification algorithms to testify the effects of the resultant features on chemical pattern recognition. Yielding a 93.3% accuracy of separating data from control and disordered fruit samples, 2-D wavelet analysis not only proves its feasibility to extract feature from original 2-D signals but also shows its superiority over the conventional feature extraction methods including converting 2-D to 1-D and selecting distinguishable pixels from training set. Furthermore, this process does not require coupling with specific pattern recognition methods, which may help ensure wide applications of this method to 2-D spectrometry data.     

Systemic approach in the physical and structural chemistry of enzyme catalysis: From primary structure to elementary event

The state of the art in enzyme catalysis is considered in terms of physical and structural chemistry. The main chemical kinetic and structural approaches are presented that can provide detailed information concerning the elementary processes making up the multistep catalytic cycle of molecular conversion at the active site of an enzyme. It is demonstrated that knowledge of the sequence of amino acids in a protein is sufficient to reconstruct the tertiary structure of this protein, to identify the catalytic groups, and to elucidate the molecular mechanism of catalysis. This approach is based on highly efficient information and computational technologies. The architecture of the active sites of enzymes is analyzed, including geometric invariants and the characteristic bond distances and angles of catalytic groups. The template method for identifying catalytic sites in the protein 4D structure is considered. The potential of molecular mechanics in the study of active sites is illustrated by the example of computer-simulated mutagenesis. Quantum chemical calculations applied to elementary events of the catalytic cycle are considered as a physical basis for understanding the catalytic mechanism and the origin of the efficiency and specificity of enzymes.     

The Royal Society of Chemistry and the delivery of chemistry data repositories for the community

Since 2009 the Royal Society of Chemistry (RSC) has been delivering access to chemistry data and cheminformatics tools via the ChemSpider database and has garnered a significant community following in terms of usage and contribution to the platform. ChemSpider has focused only on those chemical entities that can be represented as molecular connection tables or, to be more specific, the ability to generate an InChI from the input structure. As a structure centric hub ChemSpider is built around the molecular structure with other data and links being associated with this structure. As a result the platform has been limited in terms of the types of data that can be managed, and the flexibility of its searches, and it is constrained by the data model. New technologies and approaches, specifically taking into account a shift from relational to NoSQL databases, and the growing importance of the semantic web, has motivated RSC to rearchitect and create a more generic data repository utilizing these new technologies. This article will provide an overview of our activities in delivering data sharing platforms for the chemistry community including the development of the new data repository expanding into more extensive domains of chemistry data.     

Structure determination of protein-protein complexes using NMR chemical shifts: case of an endonuclease colicin-immunity protein complex

Nuclear magnetic resonance (NMR) spectroscopy provides a range of powerful techniques for determining the structures and the dynamics of proteins. The high-resolution determination of the structures of protein-protein complexes, however, is still a challenging problem for this approach, since it can normally provide only a limited amount of structural information at protein-protein interfaces. We present here the determination using NMR chemical shifts of the structure (PDB code 2K5X) of the cytotoxic endonuclease domain from bacterial toxin colicin (E9) in complex with its cognate immunity protein (Im9). In order to achieve this result, we introduce the CamDock method, which combines a flexible docking procedure with a refinement that exploits the structural information provided by chemical shifts. The results that we report thus indicate that chemical shifts can be used as structural restraints for the determination of the conformations of protein complexes that are difficult to obtain by more standard NMR approaches.     

Density-functional geometry optimization of the 150,000-atom photosystem-I trimer

We present a linear-scaling method based on the use of density-functional theory (DFT) for the system-wide optimization of x-ray structural coordinates and apply it to optimize the 150,000 atoms of the photosystem-I (PS-I) trimer. The method is based on repetitive applications of a multilevel ONIOM procedure using the PW916-31G(d) DFT calculations for the high level and PM3 for the lower level; this method treats all atoms in the structure equivalently, a structure in which the majority of the atoms can be considered as part of some internal "active site." To obtain a realistic single structure, some changes to the original protein model were necessary but these are kept to a minimum in order that the optimized structure most closely resembles the original x-ray one. Optimization has profound effects on the perceived electronic properties of the cofactors, with, e.g., optimization lowering the internal energy of the chlorophylls by on average 53 kcal mol(-1) and eliminates the enormous 115 kcal mol(-1) energy spread depicted by the original x-ray heavy-atom coordinates. A highly precise structure for PS-I results that is suitable for analysis of device function. Significant qualitative features of the structure are also improved such as correction of an error in the stereochemistry of one of the chlorophylls in the "special pair" of the reaction center, as well as the replacement of a water molecule with a metal cation in a critical region on the C3 axis. The method also reveals other unusual features of the structure, leading both to suggestions concerning device functionality and possible mutations between gene sequencing and x-ray structure determination. The optimization scheme is thus shown to augment the molecular modeling schemes that are currently used to add medium-resolution structural information to the raw scattering data in order to obtain atomically resolved structures. System-wide optimization is now a feasible process and its use within protein x-ray data refinement should be considered.     

Evaluation and comparison of layered titanate nanosheets using TOF‐SIMS and g‐ogram analysis

The evaluation of nanostructure is important to develop the highly controlled nanomaterials. In this study, two kinds of layered titanate nanosheets, which were produced by using hexylamine and laurylamine, respectively, as surfactants were investigated by Gentle Secondary Ion Mass Spectrometry Gentle‐SIMS (G‐SIMS) and g‐ogram, which is the latest Time‐of‐Flight Secondary Ion Mass Spectrometry (TOF‐SIMS) data analysis method for detecting more intact ions and obtaining the information on original chemical structures of samples precisely from complicated TOF‐SIMS spectra. As a result, molecular related ions of the surfactants were detected from each sample, and the structural information of samples was obtained. From both samples, surfactant molecular ions connected with hydrocarbon were detected as more intact ions rather than molecular ions of themselves. It was suggested that hydrophobic domains of their lamellar mesostructure are formed robustly by more than two surfactant molecules connected with each other linearly. After all, important information on the chemical structure of the layered titanate nanosheets, which would be difficult to be found by using typical structural analysis methods such as X‐ray diffraction and transmission electron microscopy, were obtained using G‐SIMS and g‐ogram. Therefore, it was shown that g‐ogram and G‐SIMS are helpful to evaluate the nanostructured materials. And it was also shown that g‐ogram is applicable to organic–inorganic materials which contain long hydrocarbon structures. Copyright © 2015 John Wiley & Sons, Ltd.     

Automatic perception of organic molecules based on essential structural information

Format conversion is very common in structure preparation in molecular modeling studies. Unfortunately, format conversion cannot always be executed precisely. We have developed an automatic method, called I-interpret (available on-line at http://www.sioc-ccbg.ac.cn/software/I-interpret/), for interpreting the chemical structure of a given organic molecule merely from its essential structural information, including element identities and three-dimensional coordinates of its component atoms. I-interpret uses standard geometrical parameters of organic molecules in atom/bond-type assignment. A series of elaborate considerations are arranged in a logical sequence for this purpose. I-interpret was tested on a set of 179 small organic molecules from the Protein Data Bank and a set of 1990 organic molecules from the NCI diversity set. On both sets, it achieved a success rate of over 95% in interpreting the correct chemical structures, outperforming other programs under our evaluation. I-interpret also provides users some optional functions, which makes it more flexible and powerful in practice. It may serve as a valuable tool for processing chemical structures in molecular modeling.     

New benchmark for chemical nomenclature software

We propose a new, robust benchmark, called Percentage Round Tripping of Canonical Isomeric SMILES (%RTCS), for assessing the ability of chemical nomenclature software to convert chemical structures to names and chemical names to structures. The benchmark is based on a string comparison between canonical isomeric SMILES generated from the original structure and the resultant structure from round tripping. Using the latest version of the OpenEye chemical nomenclature toolkit, Lexichem v2.1.0, we report %RTCS values of over 92% on average for a variety of challenging compound collections.     

Structure-based prediction of the conductance properties of ion channels

The HOLE procedure allows the prediction of the absolute conductance of an ion channel model from its structure. The original prediction method uses an empirically corrected Ohmic method. It is most successful, with predictions being reliable to within a factor of two. A new modification of the procedure is presented in which the self-diffusion coefficients of water molecules from molecular dynamics simulation are used to replace the empirical correction factor. A "prediction" of the conductance for the porin OmpF by the new method is made and shown to be very close to the experimental value. HOLE also allows the prediction of the effect that the addition of non-electrolyte polymers will have on channel conductance. The method has great potential to yield structural information from data provided by single channel recordings but needs further validation by making measurements on channels of known structure. Preliminary results are given of single channel records establishing the effects of non-electrolytes on the conductance of gramicidin D channels. As an example of the potential uses of the procedure application is made to examine the oligomerization of alpha-toxin (alpha-hemolysin) channels. A model for the alpha-toxin hexamer, based on the crystal structure for the heptamer, is generated using molecular mechanics methods. The compatibility of the structures with single channel conductance data is assessed using HOLE.     

Computer generation of chemical structures from known fragments

The interactive generation of chemical structures from given fragments is described and discussed. It is implemented as a part of our expert system CARBON, based on C-13 NMR spectra. As it is designed, this program can also be a useful tool in the structure elucidation process when information on parts of the structure is obtained by other means (IR, mass and other spectrometries, chemical analysis, other relevant information). The topological characteristics of candidate fragments are first chosen interactively and then the elements are connected in all topologically possible ways. In the following step, the topological building blocks are substituted by chemical structural fragments resulting in a set of all chemical structures consistent with the input information.     

Determination of Reaction Paths for Pentacoordinate Metal Complexes with the Structure Correlation Method

Crystal structures potentially deliver far more information than is present in the average structural communication—if sufficient structural data on closely related molecules or molecular fragments are available, it may be possible to infer details of geometric changes occurring along certain reaction pathways for the species of interest. This geometric information is extrapolated from an analysis of the similarities between the structures of the fragment in the various crystalline environments, by a method that is now known as structure correlation analysis. Since it was first proposed twenty years ago, the method has been applied to a large variety of chemical systems, but none have received as much attention as the class of five-coordinate compounds. Comparative analyses of the structures of pentacoordinate complexes have yielded information about the intimate mechanisms of substitution and addition/elimination reactions at tetrahedral and square-planar complexes, and about intramolecular isomerizations of five-coordinate compounds. Since its inception, the structure correlation method has gradually adapted techniques from other branches of science, in particular group-theoretical and multivariate statistical techniques, which have been shown to be enormously powerful tools for probing geometrically complex systems. This review traces the development of the method of structure correlation and the evolution of these co-opted techniques, with a specific emphasis on studies of five-coordinate metal complexes.     

Generalized two-dimensional correlation spectroscopy——Theory and applications in analytical field

After correlation analysis for general spectro- scopy, two-dimensional (2-D) correlation spectroscopy is obtained by extracting the information contained in the spectra in two dimensions, which is the function of two dependent spectral variables. 2-D correlation spectroscopy is initially regarded as an analytical data treatment method in the study of molecular interaction by using sinusoidal infrared sign[1]. In 1993, it was extended to generalized 2-D correlation spectroscopy, which used mo…     

Generalized two-dimensional correlation spectroscopy-- Theory and applications in analytical field

Since the theory of generalized two-dimensional (2-D) correlation spectroscopy was proposed, it has been keenly concerned in scientific research and its analytical method has been widely applied in various analytical fields. The mathematical process to construct generalized 2-D correlation spectroscopy and the physical meaning of 2-D correlation spectral map are described, and three examples in the fields of chemical analysis and molecular biology are provided, such as the component analysis of organic solvent, the analysis of biological molecules in the solvent with different pH values and structural analysis of protein. The theory and analytical method of generalized 2-D correlation spectroscopy are also detailedly commented.     

Similarity searching in databases of three-dimensional molecules and macromolecules.

This paper discusses algorithmic techniques for measuring the degree of similarity between pairs of three-dimensional (3-D) chemical molecules represented by interatomic distance matrices. A comparison of four methods for the calculation of 3-D structural similarity suggests that the most effective one is a procedure that identifies pairs of atoms, one from each of the molecules that are being compared, that lie at the center of geometrically-related volumes of 3-D space. This atom mapping method enables the calculation of a wide range of types of intermolecular similarity coefficient, including measures that are based on physicochemical data. Massively-parallel implementations of the method are discussed, using the AMT Distributed Array Processor, that achieve a substantial increase in performance when compared with a sequential implementation on a UNIX workstation. Current work involves the use of angular information and the extension of the method to field-based similarity searching. Similarity searching in 3-D macromolecules is effected by the use of a maximal common subgraph (MCS) isomorphism algorithm with a novel, graph-based representation of the tertiary structures of proteins. This algorithm is being used to identify similarities between the 3-D structures of proteins in the Brookhaven Protein Data Bank; its use is exemplified by searches involving the NAD-binding fold motif.