Given structure, computer-aided molecular

Computer aided molecular design (CAMD) problems are defined as, Given a set of building blocks and a specified set of target properties Determine the molecule or molecular structure that matches these properties. 

The synthesis by computer-aided molecular design of new compounds that conform to various physical property requirements can reduce the time and effort required using traditional empirical approaches. This process generates chemical structures and evaluates certain physical properties. The generation process must be consistent with given structural constraints and this goal is obtained as explained at point 2. 

Computer-Aided Property Estimation Computer-aided structure estimation requires the structure of the chemical compounds to be encoded in a computer-readable language. Computers most efficiently process linear strings of data, and hence linear notation systems were developed for chemical structure representation. Several such systems have been described in the literature. SMILES, the Simplified Molecular Input Line Entry System, by Weininger and collaborators [2-4], has found wide acceptance and is being used in the Toolkit. Here, only a brief summary of SMILES rules is given. A more detailed description, together with a tutorial and examples, is given in Appendix A. 

The Simplified Molecular Input Line Entry System (SMILES) is frequently used for computer-aided evaluation of molecular structures [1-3]. SMILES is widely accepted and computationally efficient because SMILES uses atomic symbols and a set of intuitive rules. Before presenting examples, the basic rules needed to enter molecular structures as SMILES notation are given. 

What we believe to be particularly important in the result [Eq. (52)] is that the impulse speed depends strongly on the sodium current activation rate. Thus by measuring the impulse speed we obtain information not only about passive electric characteristics of the nerve fiber but also about the dynamics of the molecular structures responsible for the fiber s activity. A more comprehensive comparison of the above theory with experiment, in particular with the computer-aided treatment of the H-H model carried out in Reference (24), is given elsewhere, in which theory modifications that are more adequate to the H-H model are also analyzed. It should be noted, besides, that qualitatively similar results were obtained by Rinzel and Keller who studied impulse propagation in a FitzHugh-Nagumo model (which takes into account the inertial nature of the variable in the same manner as it does potassium conductance). 

The purpose of the final section of this chapter is to review the practical applications of molecular enumeration and to give the reader interested in any of these applications pointers to relevant codes and techniques. In particular, the numbers of isomers for a specific molecular series are given, popular structure elucidation codes are reviewed, computed-aided structure elucidation successes are surveyed, and the connections between structure enumeration and combinatorial library design are established. The field of molecular design with inverse quantitative structure activity relationship is also reviewed. We conclude the chapter outlining future research directions. 

Molecular structure elucidation. Computer-aided structure elucidation (CASE) uses algorithms that construct all mathematically possible structural formulas for a given molecular formula and optional structural restrictions (often obtained from a spectrum). This has to be performed efficiently and without redundance (i.e. no duplicates allowed). Virtual spectra can be calculated for generated structures and compared with the experimental spectrum to rank the generated structure candidates. The corresponding algorithms that we need for such a formula-based structure generation will be described. 

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