Modeling boiling points of cycloalkanes by means of iterated line graph sequences

A class of models for predicting boiling points of cycloalkanes is put forward, based on iterated line graphs L(i), i = 1, 2,., of the molecular graph G = L(0). Let m(i) be the number of edges of L(i), i = 0, 1, 2,. The models analyzed are of the form a(0)m(i)()(0) + a(1)m(i)(1) + a(2)m(i)(2) +. + a(k)m(ik) + b. Our optimal QSPR formulas contain m(0), m(1), m(2), m(3), and/or m(4) but never m(5) and m(6). Their precision is as good as or better than the approximations recently reported by Rücker and Rücker (J. Chem. Inf. Comput. Sci. 1999, 39, 788-802).     

The evaluation of spectral moments for molecular graphs of phenylenes

The evaluation of some spectral moments for phenylenes is considered. Explicit topological formulae for the fourth, sixth and eighth moments are derived. This was achieved by adopting the method of Hall [1], which was originally applied to benzenoid systems, and applying it to molecular graphs of phenylenes. It is shown that the moments considered in this paper can be expressed in terms of three mutually independent graphical invariants. Received: 17 October 1996 / Accepted: 18 April 1997     

Information content in organic molecules: quantification and statistical structure via Brownian processing

Information and organic molecules were the subject of two previous works from this lab (Graham and Schacht, J. Chem. Inf. Comput. Sci. 2000, 40, 187; Graham, J. Chem. Inf. Computer Sci. 2002, 42, 215). We delve further in this paper by examining organic structure graphs as objects of Brownian information processing. In so doing, tools are introduced which quantify and correlate molecular information to several orders. When the results are combined with energy data, an enhanced informatic view of covalent bond networks is obtained. The information properties of select molecules and libraries are illustrated. Notably, Brownian processing accommodates all possible compounds and libraries, not just ones registered in chemical databases. This approach establishes important features of the statistical structure underlying carbon chemistry.     

Quest for molecular graphs with maximal energy: a computer experiment

If lambda(1), lambda(2),..., lambda(n) are the eigenvalues of a graph G, then the energy of G is defined as E(G) = the absolute value of lambda(1) + the absolute value of lambda(2) +.... + the absolute value of lambda(n). If G is a molecular graph, representing a conjugated hydrocarbon, then E(G) is closely related to the respective total pi-electron energy. It is not known which molecular graph with n vertices has maximal energy. With the exception of m = n - 1 and m = n, it is not known which molecular graph with n vertices and m edges has maximal energy. To come closer to the solution of this problem, and continuing an earlier study (J. Chem. Inf. Comput. Sci. 1999, 39, 984-996, ref 7), we performed a Monte Carlo-type construction of molecular (n,m)-graphs, recording those with the largest (not necessarily maximal possible) energy. The results of our search indicate that for even n the maximal-energy molecular graphs might be those possessing as many as possible six-membered cycles; for odd n such graphs seem to prefer both six- and five-membered cycles.     

Rapid evaluation of synthetic and molecular complexity for in silico chemistry

Methods that rapidly evaluate molecular complexity and synthetic feasibility are becoming increasingly important for in silico chemistry. We propose a new metric based on relative atomic electronegativities and bond parameters that evaluate both synthetic and molecular complexity (SMCM) starting from chemical structures. Against molecular weight, SMCM has the lowest fraction of adjusted variance (R2=0.535) on a series of 261,048 diverse compounds, when compared to the complexity metric of Baron and Chanon (R2=0.777; J. Chem. Inf. Comput. Sci. 2001, 41, 269-272) and Rücker (R2=0.895 for log complexity values; J. Chem. Inf. Comput. Sci. 2004, 44, 378-386), respectively. These metrics are in general agreement when the metabolic synthesis of cholesterol from S-3-hydroxy-3-methyl-glutaryl coenzyme A is monitored, indicating that SMCM can be useful in discerning increases in complexity. Because the presence of substructure patterns can be directly incorporated into this scheme, SMCM is relatively straightforward and can be easily tailored to rapidly evaluate virtual (combinatorial) libraries and high throughput screening hits.     

DDLm: A New Dictionary Definition Language

A previous paper [Spadaccini and Hall J. Chem. Inf. Model. doi:10.1021/ci300074v] details extensions to the STAR File [Hall J. Chem. Inf. Comput. Sci.1991, 31, 326-333] syntax that will improve the exchange and archiving of electronic data. This paper describes a dictionary definition language (DDLm) for defining STAR File data items in a domain dictionary. A dictionary that defines the ontology and vocabulary of a discipline is built with DDLm, which is itself implemented in STAR, and is extensible and machine parsable. The DDLm is semantically rich and highly specific; provides strong data typing, data enumerations, and ranges; enables relationship keys between data items; and uses imbedded methods written in dREL [Spadaccini et al. J. Chem. Inf. Model. doi:10.1021/ci300076w] for data validation and evaluation and for refining data definitions. It promotes the modular definition of the discipline ontology and reuse through the ability to import definitions from other local and remote dictionaries, thus encouraging the sharing of data dictionaries within and across domains.     

Indexing molecules with chemical graph identifiers

Fast and robust algorithms for indexing molecules have been historically considered strategic tools for the management and storage of large chemical libraries. This work introduces a modified and further extended version of the molecular equivalence number naming adaptation of the Morgan algorithm (J Chem Inf Comput Sci 2001, 41, 181-185) for the generation of a chemical graph identifier (CGI). This new version corrects for the collisions recognized in the original adaptation and includes the ability to deal with graph canonicalization, ensembles (salts), and isomerism (tautomerism, regioisomerism, optical isomerism, and geometrical isomerism) in a flexible manner. Validation of the current CGI implementation was performed on the open NCI database and the drug-like subset of the ZINC database containing 260,071 and 5,348,089 structures, respectively. The results were compared with those obtained with some of the most widely used indexing codes, such as the CACTVS hash code and the new InChIKey. The analyses emphasize the fact that compound management activities, like duplicate analysis of chemical libraries, are sensitive to the exact definition of compound uniqueness and thus still depend, to a minor extent, on the type and flexibility of the molecular index being used.