Molecules computer representation

Some aspects, such as the computer representation and manipulation of proteins and nucleic acids, could not be covered. Even the modeling of the interactions of small molecules with proteins, as dealt with in docking software or software for de novo design could not be included in the Textbook, although chapters in the Handbook do treat these subjects. 

New ways to represent structure data became available through molecular modeling by computer-based methods. The birth of interactive computer representation of molecular graphics was in the 196Ds. The first dynamic molecular pictures of small molecules were generated in 1964 by Lcvinthal in the Mathematics and Computation (MAC) project at the Electronic Systems Laboratoiy of the Massachusetts... 

Computer Representations of Molecules, Chemical Databases and 2D Substructure Searching... 

Schwenke, D. W. (1991), Compact Representation of Vibrational Wave Functions for Diatomic Molecules, Comput. Phys. Comm. 70, 1. 

Fig. 3.41 Computer representation of the structure of acetylcholine in its free solution-state conformation, in which oxygen atoms appear on opposite sides of the molecule (top), and of acetylcholine in its receptor-bound state, in which oxygen atoms appear on the same side (bottom). (Reprinted from Fig.

When one inserts an image of molecule from the Molecule Editor into a ChemText document, one actually inserts a computable representation of the structure. As this is a new concept, let me illustrate with an example. Suppose you have a ChemBase data base of your compounds. (See Fig. 1.8) You pull out the structure of your new compound and insert it into your manuscript which you... 

Henry W. Davis, Computer Representation of the Stereochemistry of Organic Molecules With Application to the Problem of Discovery of Organic Synthesis by Computer, Birkhauser Verlag, Basel, 1976. 

The DARC notation (see, for example, ref. 228) is a system of computer representation of chemical compounds rather than a system for the input of molecules into the computer. It will thus not be discussed here. 

For generating synthetic pathways by a computer, representations for the intermediates of chemical syntheses (molecules) and for the transformation intermediates of these (reactions) have to be designed. Both molecules and reactions are represented in our model of constitutional chemistry4 5 by matrices. Internally, in the program, more compact forms are used. 

To exemplify a molecular similarity method, we employed here a 3D shape-based molecular similarity approach using OpenEye scientific software (OpenEye). A set of 27 molecules (Amoore, 1971) were compared to benzaldehyde (query molecule). The representation used here is based on the volume of each molecule. A conformational ensemble is built for the molecules in the database, whereas the conformation of the query remains fixed (the chemical nature of benzaldehyde does not entail different conformers, though in many cases the conformation of the query molecules might be complex and crucial). After the conformers of each molecule in the data set are built, each one of them is compared with the query and a similarity value is computed. For the particular program employed here (ROCS), the similarity is quantified as a score formed by two terms, one takes into account the chemical nature of the molecules while the other relies on molecular shape, such score is referred to as combo score. The maximum similarity value is 2 which can only be obtained from the comparison of a molecule with itself in the exact same conformation (perfect match). The normalized values (from 0 to 1) for the odor and combo score similarities are compared in the graph shown in Fig. 2.4. As can be observed, as the combo score increases, the odor similarity to benzaldehyde also increases. This correlation shows that part of the odor similarity was captured by the molecular... 

Computer representation of methane and ethane molecules inside one of the hexagonal pores of MCM-41. Red = oxygen blue = silicon light blue = hydrogen brown = carbon. 

Based on user-defined simple bimolecular interactions the software package simmune generates computational representations of the complete set of multimolecular signaling complexes (up to a user-defined maximum size, i.e., number of molecular components) and their reactions. The software then allows its users to perform simulated experiments, exposing the simulated cells to stimuli either through the application of extracellular molecules or by letting the cells interact with other cells. Detailed information about the intracellular biochemistry of each simulated cell can be obtained and visualized in various ways. 

The purpose of a chemical expert system is to provide fast, easy, efficient and effective access to chemical information and knowledge in a specific domain of expertise, via computer-representation of integrated reference data, theoretical and empirical knowledge (e.g., in the form of rules ), system models and reasoning mechanisms. An expert system should not only contain (integrated) relevant hard facts (e.g., numerical correlations and statistics) but also the expertise ( soft knowledge ) of experienced specialists in the field. For structure elucidation of organic molecules various spectrometric methods are available. In many cases different methods such as mass, infra-red, NMR and ultra-violet spectroscopy provide complementary structural information. This is one of the basic elements of EXSPEC, an expert system for computer-aided interpretation of combined spectral data. ... 

The most widely used methods to predict aqueous solubility from molecular structure are quantitative structure-property relationships (QSPRs) [4-6], which are empirical models that use experimental data to learn a statistical relationship between the physical property of interest (i.e., solubility) and molecular descriptors calculable from a simple computational representation of the molecule (e.g., counts of atoms or functional groups, polar surface area, and molecular dipole moment) [1], The current... 

Figure 5.14. The Keggin structure of the PW]2O40 , identifying the three types of oxygen atoms in the structures . The hexahydrate heteropolyacid contains typically six water molecules per Keggin unit. The water molecules essentially help to assemble and pack the primary structure into an organized secondary hierarchy. A computed representation of the secondary H3PW12O40.6H2O hexahydrate form is given in Fig. 5.15.

Molecular structures are represented by models. Models made of balls and sticks appeal to the esthetic sense and help in drawing qualitative conclusions about the structure and its function. Models existing as computer representations allow rapid and precise calculations of the properties of the model. These calculated properties of the model may then be compared with known properties of the molecule and serve as a criterion to decide if the model is appropriate. Sometimes the dilference can be expressed as a continuous function of the parameters describing the model. In that case, successive improvements of the model can be computed automatically by techniques of function minimization. 

The representation of trial fiinctions as linear combinations of fixed basis fiinctions is perhaps the most connnon approach used in variational calculations optimization of the coefficients is often said to be an application of tire linear variational principle. Altliough some very accurate work on small atoms (notably helium and lithium) has been based on complicated trial functions with several nonlinear parameters, attempts to extend tliese calculations to larger atoms and molecules quickly runs into fonnidable difficulties (not the least of which is how to choose the fomi of the trial fiinction). Basis set expansions like that given by equation (A1.1.113) are much simpler to design, and the procedures required to obtain the coefficients that minimize are all easily carried out by computers. 

There are many large molecules whose mteractions we have little hope of detemiining in detail. In these cases we turn to models based on simple mathematical representations of the interaction potential with empirically detemiined parameters. Even for smaller molecules where a detailed interaction potential has been obtained by an ab initio calculation or by a numerical inversion of experimental data, it is usefid to fit the calculated points to a functional fomi which then serves as a computationally inexpensive interpolation and extrapolation tool for use in fiirtlier work such as molecular simulation studies or predictive scattering computations. There are a very large number of such models in use, and only a small sample is considered here. The most frequently used simple spherical models are described in section Al.5.5.1 and some of the more common elaborate models are discussed in section A 1.5.5.2. section Al.5.5.3 and section Al.5.5.4. 

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